diff --git a/chapter_13_chapter_computer-vision/boundingbox.ipynb b/chapter_13_chapter_computer-vision/boundingbox.ipynb index 41c7567..cea5b63 100644 --- a/chapter_13_chapter_computer-vision/boundingbox.ipynb +++ b/chapter_13_chapter_computer-vision/boundingbox.ipynb @@ -10,19 +10,22 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "24e0d97b", "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import mindspore\n", + "from mindspore import mint\n", + "import sys\n", + "sys.path.insert(0, \"..\")\n", "from d2l import mindspore as d2l" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "7a1a229e", "metadata": {}, "outputs": [ @@ -37,11 +40,11 @@ " \n", " \n", " \n", - " 2023-03-03T02:53:14.144649\n", + " 2025-12-20T23:10:22.808905\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.6.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -68,20 +71,20 @@ "z\n", "\" style=\"fill: #ffffff\"/>\n", " \n", - " \n", + " \n", " \n", + 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\" id=\"imagedc21eac83b\" transform=\"scale(1 -1) translate(0 -138.96)\" x=\"33.2875\" y=\"-10.515689\" width=\"180\" height=\"138.96\"/>\n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -117,7 +120,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -158,7 +161,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -194,7 +197,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -243,12 +246,12 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -261,7 +264,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -292,7 +295,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -307,7 +310,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -356,7 +359,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -371,7 +374,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -434,7 +437,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -464,7 +467,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "8ebaac22", "metadata": {}, "outputs": [], @@ -477,7 +480,7 @@ " cy = (y1 + y2) / 2\n", " w = x2 - x1\n", " h = y2 - y1\n", - " boxes = d2l.stack((cx, cy, w, h), axis=-1)\n", + " boxes = mint.stack((cx, cy, w, h), dim=-1)\n", " return boxes\n", "\n", "#@save\n", @@ -488,13 +491,13 @@ " y1 = cy - 0.5 * h\n", " x2 = cx + 0.5 * w\n", " y2 = cy + 0.5 * h\n", - " boxes = d2l.stack((x1, y1, x2, y2), axis=-1)\n", + " boxes = mint.stack((x1, y1, x2, y2), dim=-1)\n", " return boxes" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "ccc2afa7", "metadata": {}, "outputs": [], @@ -505,7 +508,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "86a197f4", "metadata": {}, "outputs": [ @@ -517,7 +520,7 @@ " [ True, True, True, True]])" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -529,7 +532,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "id": "83fc656a", "metadata": {}, "outputs": [], @@ -545,7 +548,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "id": "bc963a90", "metadata": {}, "outputs": [ @@ -560,11 +563,11 @@ " \n", " \n", " \n", - " 2023-03-03T02:53:17.405465\n", + " 2025-12-20T23:10:48.924958\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.6.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -591,9 +594,9 @@ "z\n", "\" style=\"fill: #ffffff\"/>\n", " \n", - " \n", + " \n", " \n", + 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\" id=\"image8cc3f166d4\" transform=\"scale(1 -1) translate(0 -138.96)\" x=\"33.2875\" y=\"-10.515689\" width=\"180\" height=\"138.96\"/>\n", " \n", " \n", " \n", + "\" clip-path=\"url(#p88464f5569)\" style=\"fill: none; stroke: #0000ff; stroke-width: 2; stroke-linejoin: miter\"/>\n", " \n", " \n", " \n", + "\" clip-path=\"url(#p88464f5569)\" style=\"fill: none; stroke: #ff0000; stroke-width: 2; stroke-linejoin: miter\"/>\n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -658,7 +661,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -699,7 +702,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -735,7 +738,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -784,12 +787,12 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -802,7 +805,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -833,7 +836,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -848,7 +851,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -897,7 +900,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -912,7 +915,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -975,7 +978,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1006,9 +1009,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -1020,7 +1023,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.5" + "version": "3.10.14" }, "toc": { "base_numbering": 1, diff --git a/chapter_13_chapter_computer-vision/fcn.ipynb b/chapter_13_chapter_computer-vision/fcn.ipynb index 24d8c1d..a161901 100644 --- a/chapter_13_chapter_computer-vision/fcn.ipynb +++ b/chapter_13_chapter_computer-vision/fcn.ipynb @@ -18,9 +18,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "[WARNING] ME(89670:47623503916416,MainProcess):2023-03-03-02:55:21.452.349 [mindspore/common/api.py:840] 'mindspore.ms_class' will be deprecated and removed in a future version. Please use 'mindspore.jit_class' instead.\n", - "[WARNING] ME(89670:47623503916416,MainProcess):2023-03-03-02:55:21.652.203 [mindspore/common/api.py:694] 'mindspore.ms_function' will be deprecated and removed in a future version. Please use 'mindspore.jit' instead.\n", - "[WARNING] ME(89670:47623503916416,MainProcess):2023-03-03-02:55:21.667.855 [mindspore/common/api.py:694] 'mindspore.ms_function' will be deprecated and removed in a future version. Please use 'mindspore.jit' instead.\n" + "[WARNING] CORE(816140,ffff8ef9f640,python):2025-12-22-14:03:49.675.969 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n", + "[WARNING] ME(816140:281473080489536,MainProcess):2025-12-22-14:03:54.691.000 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead.\n" ] } ], @@ -29,9 +28,11 @@ "import mindspore\n", "import mindcv\n", "from mindspore import nn\n", - "from mindspore.ops import functional as F\n", + "import mindspore.mint.nn.functional as F\n", + "import sys\n", + "sys.path.insert(0, \"..\")\n", "from d2l import mindspore as d2l\n", - "mindspore.set_context(device_target='GPU')" + "mindspore.set_context(device_target='Ascend', mode=mindspore.PYNATIVE_MODE)" ] }, { @@ -51,28 +52,28 @@ { "data": { "text/plain": [ - "[SequentialCell<\n", - " (0): BasicBlock<\n", - " (conv1): Conv2d\n", - " (bn1): BatchNorm2d\n", - " (relu): ReLU<>\n", - " (conv2): Conv2d\n", - " (bn2): BatchNorm2d\n", - " (down_sample): SequentialCell<\n", - " (0): Conv2d\n", - " (1): BatchNorm2d\n", - " >\n", - " >\n", - " (1): BasicBlock<\n", - " (conv1): Conv2d\n", - " (bn1): BatchNorm2d\n", - " (relu): ReLU<>\n", - " (conv2): Conv2d\n", - " (bn2): BatchNorm2d\n", - " >\n", - " >,\n", - " GlobalAvgPooling<>,\n", - " Dense]" + "[SequentialCell(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(input_channels=256, output_channels=512, kernel_size=(3, 3), stride=(2, 2), pad_mode=pad, padding=1, dilation=(1, 1), group=1, has_bias=False, weight_init=, bias_init=None, format=NCHW)\n", + " (bn1): BatchNorm2d(num_features=512, eps=1e-05, momentum=0.9, gamma=Parameter (name=layer4.0.bn1.gamma, shape=(512,), dtype=Float32, requires_grad=True), beta=Parameter (name=layer4.0.bn1.beta, shape=(512,), dtype=Float32, requires_grad=True), moving_mean=Parameter (name=layer4.0.bn1.moving_mean, shape=(512,), dtype=Float32, requires_grad=False), moving_variance=Parameter (name=layer4.0.bn1.moving_variance, shape=(512,), dtype=Float32, requires_grad=False))\n", + " (relu): ReLU()\n", + " (conv2): Conv2d(input_channels=512, output_channels=512, kernel_size=(3, 3), stride=(1, 1), pad_mode=pad, padding=1, dilation=(1, 1), group=1, has_bias=False, weight_init=, bias_init=None, format=NCHW)\n", + " (bn2): BatchNorm2d(num_features=512, eps=1e-05, momentum=0.9, gamma=Parameter (name=layer4.0.bn2.gamma, shape=(512,), dtype=Float32, requires_grad=True), beta=Parameter (name=layer4.0.bn2.beta, shape=(512,), dtype=Float32, requires_grad=True), moving_mean=Parameter (name=layer4.0.bn2.moving_mean, shape=(512,), dtype=Float32, requires_grad=False), moving_variance=Parameter (name=layer4.0.bn2.moving_variance, shape=(512,), dtype=Float32, requires_grad=False))\n", + " (down_sample): SequentialCell(\n", + " (0): Conv2d(input_channels=256, output_channels=512, kernel_size=(1, 1), stride=(2, 2), pad_mode=same, padding=0, dilation=(1, 1), group=1, has_bias=False, weight_init=, bias_init=None, format=NCHW)\n", + " (1): BatchNorm2d(num_features=512, eps=1e-05, momentum=0.9, gamma=Parameter (name=layer4.0.down_sample.1.gamma, shape=(512,), dtype=Float32, requires_grad=True), beta=Parameter (name=layer4.0.down_sample.1.beta, shape=(512,), dtype=Float32, requires_grad=True), moving_mean=Parameter (name=layer4.0.down_sample.1.moving_mean, shape=(512,), dtype=Float32, requires_grad=False), moving_variance=Parameter (name=layer4.0.down_sample.1.moving_variance, shape=(512,), dtype=Float32, requires_grad=False))\n", + " )\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(input_channels=512, output_channels=512, kernel_size=(3, 3), stride=(1, 1), pad_mode=pad, padding=1, dilation=(1, 1), group=1, has_bias=False, weight_init=, bias_init=None, format=NCHW)\n", + " (bn1): BatchNorm2d(num_features=512, eps=1e-05, momentum=0.9, gamma=Parameter (name=layer4.1.bn1.gamma, shape=(512,), dtype=Float32, requires_grad=True), beta=Parameter (name=layer4.1.bn1.beta, shape=(512,), dtype=Float32, requires_grad=True), moving_mean=Parameter (name=layer4.1.bn1.moving_mean, shape=(512,), dtype=Float32, requires_grad=False), moving_variance=Parameter (name=layer4.1.bn1.moving_variance, shape=(512,), dtype=Float32, requires_grad=False))\n", + " (relu): ReLU()\n", + " (conv2): Conv2d(input_channels=512, output_channels=512, kernel_size=(3, 3), stride=(1, 1), pad_mode=pad, padding=1, dilation=(1, 1), group=1, has_bias=False, weight_init=, bias_init=None, format=NCHW)\n", + " (bn2): BatchNorm2d(num_features=512, eps=1e-05, momentum=0.9, gamma=Parameter (name=layer4.1.bn2.gamma, shape=(512,), dtype=Float32, requires_grad=True), beta=Parameter (name=layer4.1.bn2.beta, shape=(512,), dtype=Float32, requires_grad=True), moving_mean=Parameter (name=layer4.1.bn2.moving_mean, shape=(512,), dtype=Float32, requires_grad=False), moving_variance=Parameter (name=layer4.1.bn2.moving_variance, shape=(512,), dtype=Float32, requires_grad=False))\n", + " )\n", + " ),\n", + " GlobalAvgPooling(),\n", + " Dense(input_channels=512, output_channels=1000, has_bias=True)]" ] }, "execution_count": 2, @@ -215,11 +216,11 @@ " \n", " \n", " \n", - " 2023-03-03T02:55:29.793557\n", + " 2025-12-22T14:03:56.603480\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.6.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -246,20 +247,20 @@ "z\n", "\" style=\"fill: #ffffff\"/>\n", " \n", - " \n", + " \n", " \n", + 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\" id=\"imagedbbbf73c0f\" transform=\"scale(1 -1) translate(0 -138.96)\" x=\"40\" y=\"-10.455579\" width=\"180\" height=\"138.96\"/>\n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -295,7 +296,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -337,7 +338,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -371,12 +372,12 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -389,7 +390,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -430,7 +431,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -466,7 +467,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -513,7 +514,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -569,7 +570,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -606,7 +607,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -677,34 +678,16 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "c2a710e0", "metadata": {}, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "[WARNING] ME(89670:47623503916416,MainProcess):2023-03-03-02:58:17.413.36 [mindspore/dataset/engine/datasets_user_defined.py:805] GeneratorDataset's num_parallel_workers: 4 is too large which may cause a lot of memory occupation (>85%) or out of memory(OOM) during multiprocessing. Therefore, it is recommended to reduce num_parallel_workers to 1 or smaller.\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[12], line 6\u001b[0m\n\u001b[1;32m 4\u001b[0m num_epochs, lr, wd \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m5\u001b[39m, \u001b[38;5;241m0.001\u001b[39m, \u001b[38;5;241m1e-3\u001b[39m\n\u001b[1;32m 5\u001b[0m trainer \u001b[38;5;241m=\u001b[39m nn\u001b[38;5;241m.\u001b[39mSGD(net\u001b[38;5;241m.\u001b[39mtrainable_params(), learning_rate\u001b[38;5;241m=\u001b[39mlr, weight_decay\u001b[38;5;241m=\u001b[39mwd)\n\u001b[0;32m----> 6\u001b[0m \u001b[43md2l\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_ch13\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnet\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_iter\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtest_iter\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mloss\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_epochs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/python/mindspore/d2l/chapter_computer_vision_jupyter/d2l/mindspore.py:2117\u001b[0m, in \u001b[0;36mtrain_ch13\u001b[0;34m(net, train_iter, test_iter, loss, trainer, num_epochs)\u001b[0m\n\u001b[1;32m 2113\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (i \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m) \u001b[38;5;241m%\u001b[39m (num_batches \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m5\u001b[39m) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m i \u001b[38;5;241m==\u001b[39m num_batches \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m 2114\u001b[0m animator\u001b[38;5;241m.\u001b[39madd(epoch \u001b[38;5;241m+\u001b[39m (i \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m) \u001b[38;5;241m/\u001b[39m num_batches,\n\u001b[1;32m 2115\u001b[0m (metric[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m/\u001b[39m metric[\u001b[38;5;241m2\u001b[39m], metric[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m/\u001b[39m metric[\u001b[38;5;241m3\u001b[39m],\n\u001b[1;32m 2116\u001b[0m \u001b[38;5;28;01mNone\u001b[39;00m))\n\u001b[0;32m-> 2117\u001b[0m test_acc \u001b[38;5;241m=\u001b[39m \u001b[43md2l\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mevaluate_accuracy_gpu\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnet\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtest_iter\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2118\u001b[0m animator\u001b[38;5;241m.\u001b[39madd(epoch \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m, (\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;28;01mNone\u001b[39;00m, test_acc))\n\u001b[1;32m 2119\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mloss \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmetric[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;250m \u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;250m \u001b[39mmetric[\u001b[38;5;241m2\u001b[39m]\u001b[38;5;132;01m:\u001b[39;00m\u001b[38;5;124m.3f\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, train acc \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 2120\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmetric[\u001b[38;5;241m1\u001b[39m]\u001b[38;5;250m \u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;250m \u001b[39mmetric[\u001b[38;5;241m3\u001b[39m]\u001b[38;5;132;01m:\u001b[39;00m\u001b[38;5;124m.3f\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, test acc \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtest_acc\u001b[38;5;132;01m:\u001b[39;00m\u001b[38;5;124m.3f\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n", - "File \u001b[0;32m~/python/mindspore/d2l/chapter_computer_vision_jupyter/d2l/mindspore.py:482\u001b[0m, in \u001b[0;36mevaluate_accuracy_gpu\u001b[0;34m(net, dataset, device)\u001b[0m\n\u001b[1;32m 480\u001b[0m net\u001b[38;5;241m.\u001b[39mset_train(\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 481\u001b[0m metric \u001b[38;5;241m=\u001b[39m Accumulator(\u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m--> 482\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m X, y \u001b[38;5;129;01min\u001b[39;00m dataset\u001b[38;5;241m.\u001b[39mcreate_tuple_iterator():\n\u001b[1;32m 483\u001b[0m metric\u001b[38;5;241m.\u001b[39madd(accuracy(net(X), y), y\u001b[38;5;241m.\u001b[39msize)\n\u001b[1;32m 484\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m metric[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m/\u001b[39m metric[\u001b[38;5;241m1\u001b[39m]\n", - "File \u001b[0;32m~/software/anaconda3/envs/mindspore2.0/lib/python3.9/site-packages/mindspore/dataset/engine/iterators.py:145\u001b[0m, in \u001b[0;36mIterator.__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 142\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIterator does not have a running C++ pipeline.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 144\u001b[0m \u001b[38;5;66;03m# Note offload is applied inside _get_next() if applicable since get_next converts to output format\u001b[39;00m\n\u001b[0;32m--> 145\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_next\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 146\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m data:\n\u001b[1;32m 147\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__index \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n", - "File \u001b[0;32m~/software/anaconda3/envs/mindspore2.0/lib/python3.9/site-packages/mindspore/dataset/engine/iterators.py:258\u001b[0m, in \u001b[0;36mTupleIterator._get_next\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 250\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 251\u001b[0m \u001b[38;5;124;03mReturns the next record in the dataset as a list\u001b[39;00m\n\u001b[1;32m 252\u001b[0m \n\u001b[1;32m 253\u001b[0m \u001b[38;5;124;03mReturns:\u001b[39;00m\n\u001b[1;32m 254\u001b[0m \u001b[38;5;124;03m List, the next record in the dataset.\u001b[39;00m\n\u001b[1;32m 255\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 257\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moffload_model \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 258\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform_md_to_output(t) \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iterator\u001b[38;5;241m.\u001b[39mGetNextAsList()]\n\u001b[1;32m 259\u001b[0m data \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform_md_to_tensor(t) \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iterator\u001b[38;5;241m.\u001b[39mGetNextAsList()]\n\u001b[1;32m 260\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m data:\n", - "File \u001b[0;32m~/software/anaconda3/envs/mindspore2.0/lib/python3.9/site-packages/mindspore/dataset/engine/iterators.py:258\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 250\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 251\u001b[0m \u001b[38;5;124;03mReturns the next record in the dataset as a list\u001b[39;00m\n\u001b[1;32m 252\u001b[0m \n\u001b[1;32m 253\u001b[0m \u001b[38;5;124;03mReturns:\u001b[39;00m\n\u001b[1;32m 254\u001b[0m \u001b[38;5;124;03m List, the next record in the dataset.\u001b[39;00m\n\u001b[1;32m 255\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 257\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moffload_model \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 258\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m [\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_transform_md_to_output\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iterator\u001b[38;5;241m.\u001b[39mGetNextAsList()]\n\u001b[1;32m 259\u001b[0m data \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform_md_to_tensor(t) \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iterator\u001b[38;5;241m.\u001b[39mGetNextAsList()]\n\u001b[1;32m 260\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m data:\n", - "File \u001b[0;32m~/software/anaconda3/envs/mindspore2.0/lib/python3.9/site-packages/mindspore/dataset/engine/iterators.py:189\u001b[0m, in \u001b[0;36mIterator._transform_md_to_output\u001b[0;34m(self, t)\u001b[0m\n\u001b[1;32m 187\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_output_numpy:\n\u001b[1;32m 188\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m t\u001b[38;5;241m.\u001b[39mas_array()\n\u001b[0;32m--> 189\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_transform_md_to_tensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/software/anaconda3/envs/mindspore2.0/lib/python3.9/site-packages/mindspore/dataset/engine/iterators.py:194\u001b[0m, in \u001b[0;36mIterator._transform_md_to_tensor\u001b[0;34m(self, t)\u001b[0m\n\u001b[1;32m 192\u001b[0m array \u001b[38;5;241m=\u001b[39m t\u001b[38;5;241m.\u001b[39mas_array()\n\u001b[1;32m 193\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_do_copy:\n\u001b[0;32m--> 194\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mTensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43marray\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 195\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m Tensor\u001b[38;5;241m.\u001b[39mfrom_numpy(array)\n", - "File \u001b[0;32m~/software/anaconda3/envs/mindspore2.0/lib/python3.9/site-packages/mindspore/common/tensor.py:196\u001b[0m, in \u001b[0;36mTensor.__init__\u001b[0;34m(self, input_data, dtype, shape, init, internal, const_arg)\u001b[0m\n\u001b[1;32m 194\u001b[0m Tensor_\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, input_data, dtype)\n\u001b[1;32m 195\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 196\u001b[0m \u001b[43mTensor_\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minput_data\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 197\u001b[0m validator\u001b[38;5;241m.\u001b[39mcheck_value_type(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mconst_arg\u001b[39m\u001b[38;5;124m'\u001b[39m, const_arg, \u001b[38;5;28mbool\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mTensor\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 199\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconst_arg \u001b[38;5;241m=\u001b[39m const_arg\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + "loss 0.299, train acc 0.902, test acc 0.859\n", + "1.4 examples/sec\n" ] }, { @@ -718,11 +701,11 @@ " \n", " \n", " \n", - " 2023-03-03T02:58:29.712147\n", + " 2025-12-22T20:10:05.676534\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.6.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -754,16 +737,16 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -793,11 +776,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -837,11 +820,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -889,11 +872,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -928,11 +911,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1099,16 +1082,16 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1154,11 +1137,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1174,11 +1157,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1194,11 +1177,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1246,11 +1229,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1307,11 +1290,11 @@ " \n", " \n", + "\" clip-path=\"url(#pe8985ad786)\" style=\"fill: none; stroke: #b0b0b0; stroke-width: 0.8; stroke-linecap: square\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1325,32 +1308,76 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1572,14 +1599,14 @@ " \n", " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1594,7 +1621,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1627,7 +1654,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "dda3d2c7", "metadata": {}, "outputs": [], @@ -1647,7 +1674,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "44757494", "metadata": {}, "outputs": [], @@ -1660,10 +1687,500 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "2807d7a6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " 2025-12-22T21:44:05.230980\n", + " image/svg+xml\n", + " \n", + " \n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n" + ], + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "voc_dir = d2l.download_extract('voc2012', 'VOCdevkit/VOC2012')\n", "test_images, test_labels = d2l.read_voc_images(voc_dir, False)\n", @@ -1680,9 +2197,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -1694,7 +2211,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.5" + "version": "3.10.14" }, "toc": { "base_numbering": 1, diff --git a/chapter_13_chapter_computer-vision/ge_check_op.json b/chapter_13_chapter_computer-vision/ge_check_op.json new file mode 100644 index 0000000..3730649 --- /dev/null +++ b/chapter_13_chapter_computer-vision/ge_check_op.json @@ -0,0 +1,49 @@ +{ + "graph_id": 14, + "op": [ + { + "error_type": "infer_shape_error", + "input0": { + "data_type": "DT_INT32", + "layout": "NCHW", + "shape": [ + 4 + ] + }, + "input1": { + "data_type": "DT_FLOAT", + "layout": "NCHW", + "shape": [ + 21, + 21, + 64, + 64 + ] + }, + "input2": { + "data_type": "DT_FLOAT", + "layout": "NCHW", + "shape": [ + 32, + 21, + 10, + 15 + ] + }, + "name": "Conv2DBackpropInput15", + "output0": { + "data_type": "DT_FLOAT", + "layout": "NCHW", + "shape": [ + 32, + 21, + 288, + 448 + ] + }, + "reason": "InferShapeFailed!", + "type": "Conv2DBackpropInput" + } + ], + "session_id": 14 +} diff --git a/chapter_13_chapter_computer-vision/multiscale-object-detection.ipynb b/chapter_13_chapter_computer-vision/multiscale-object-detection.ipynb index 595c75f..7a7246e 100644 --- a/chapter_13_chapter_computer-vision/multiscale-object-detection.ipynb +++ b/chapter_13_chapter_computer-vision/multiscale-object-detection.ipynb @@ -22,6 +22,13 @@ "id": "966c6017", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(156275,ffffbe20b640,python):2025-12-21-08:02:52.765.555 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + }, { "data": { "text/plain": [ @@ -36,6 +43,9 @@ "source": [ "%matplotlib inline\n", "import mindspore\n", + "from mindspore import mint\n", + "import sys\n", + "sys.path.insert(0, \"..\")\n", "from d2l import mindspore as d2l\n", "\n", "img = d2l.plt.imread('../img/catdog.jpg')\n", @@ -47,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "7ecf0b02", "metadata": {}, "outputs": [], @@ -55,7 +65,7 @@ "def display_anchors(fmap_w, fmap_h, s):\n", " d2l.set_figsize()\n", " # 前两个维度上的值不影响输出\n", - " fmap = d2l.zeros((1, 10, fmap_h, fmap_w))\n", + " fmap = mint.zeros((1, 10, fmap_h, fmap_w))\n", " anchors = d2l.multibox_prior(fmap, sizes=s, ratios=[1, 2, 0.5])\n", " bbox_scale = d2l.tensor((w, h, w, h))\n", " d2l.show_bboxes(d2l.plt.imshow(img).axes,\n", @@ -64,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "209a5648", "metadata": {}, "outputs": [ @@ -79,11 +89,11 @@ " \n", " \n", " \n", - " 2023-02-26T21:31:06.186710\n", + " 2025-12-21T08:03:21.683903\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.6.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -110,9 +120,9 @@ "z\n", "\" style=\"fill: #ffffff\"/>\n", " \n", - " \n", + " \n", " \n", + 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- " \n", + " \n", " \n", " \n", " \n", @@ -928,7 +938,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "993bfdd8", "metadata": {}, "outputs": [ @@ -943,11 +953,11 @@ " \n", " \n", " \n", - " 2023-02-26T21:31:06.665550\n", + " 2025-12-21T08:03:23.999991\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.6.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -974,9 +984,9 @@ "z\n", "\" style=\"fill: #ffffff\"/>\n", " \n", - " \n", + " \n", " \n", + 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\n", " \n", - " 2023-02-26T21:31:07.272562\n", + " 2025-12-21T08:03:26.295026\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.6.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -1514,9 +1524,9 @@ "z\n", "\" style=\"fill: #ffffff\"/>\n", " \n", - " \n", + " \n", " \n", + 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\" id=\"image7a6056815d\" transform=\"scale(1 -1) translate(0 -138.96)\" x=\"33.2875\" y=\"-10.515689\" width=\"180\" height=\"138.96\"/>\n", " \n", " \n", " \n", + "\" clip-path=\"url(#p2bfa26b6c3)\" style=\"fill: none; stroke: #0000ff; stroke-width: 2; stroke-linejoin: miter\"/>\n", " \n", " \n", " \n", + "\" clip-path=\"url(#p2bfa26b6c3)\" style=\"fill: none; stroke: #008000; stroke-width: 2; stroke-linejoin: miter\"/>\n", " \n", " \n", " \n", + "\" clip-path=\"url(#p2bfa26b6c3)\" style=\"fill: none; stroke: #ff0000; stroke-width: 2; stroke-linejoin: miter\"/>\n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1589,7 +1599,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1630,7 +1640,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1666,7 +1676,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1715,12 +1725,12 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1733,7 +1743,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1764,7 +1774,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1779,7 +1789,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1828,7 +1838,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1843,7 +1853,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1906,7 +1916,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1918,6 +1928,36 @@ }, "metadata": {}, "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "Exception in thread Thread-5:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python3.10.14/lib/python3.10/threading.py\", line 1016, in _bootstrap_inner\n", + " self.run()\n", + " File \"/usr/local/Ascend/ascend-toolkit/latest/python/site-packages/tbe/common/repository_manager/utils/multiprocess_util.py\", line 91, in run\n", + " key, func, args, kwargs = self.task_q.get(timeout=TIMEOUT)\n", + " File \"\", line 2, in get\n", + " File \"/usr/local/python3.10.14/lib/python3.10/multiprocessing/managers.py\", line 818, in _callmethod\n", + " kind, result = conn.recv()\n", + " File \"/usr/local/python3.10.14/lib/python3.10/multiprocessing/connection.py\", line 250, in recv\n", + " buf = self._recv_bytes()\n", + " File \"/usr/local/python3.10.14/lib/python3.10/multiprocessing/connection.py\", line 414, in _recv_bytes\n", + " buf = self._recv(4)\n", + " File \"/usr/local/python3.10.14/lib/python3.10/multiprocessing/connection.py\", line 383, in _recv\n", + " raise EOFError\n", + "EOFError\n" + ] } ], "source": [ @@ -1935,9 +1975,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -1949,7 +1989,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.5" + "version": "3.10.14" }, "toc": { "base_numbering": 1, diff --git a/chapter_13_chapter_computer-vision/ssd.ipynb b/chapter_13_chapter_computer-vision/ssd.ipynb index 80d6164..bdd38de 100644 --- a/chapter_13_chapter_computer-vision/ssd.ipynb +++ b/chapter_13_chapter_computer-vision/ssd.ipynb @@ -29,11 +29,22 @@ "execution_count": 1, "id": "e6901d6d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(503527,ffff9d2cb640,python):2025-12-22-00:20:08.955.715 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + } + ], "source": [ "%matplotlib inline\n", "import mindspore\n", "from mindspore import nn\n", + "from mindspore import mint\n", + "import sys\n", + "sys.path.insert(0, \"..\")\n", "from d2l import mindspore as d2l\n", "\n", "\n", @@ -90,8 +101,8 @@ "def forward(x, block):\n", " return block(x)\n", "\n", - "Y1 = forward(d2l.zeros((2, 8, 20, 20)), cls_predictor(8, 5, 10))\n", - "Y2 = forward(d2l.zeros((2, 16, 10, 10)), cls_predictor(16, 3, 10))\n", + "Y1 = forward(mint.zeros((2, 8, 20, 20)), cls_predictor(8, 5, 10))\n", + "Y2 = forward(mint.zeros((2, 16, 10, 10)), cls_predictor(16, 3, 10))\n", "Y1.shape, Y2.shape" ] }, @@ -103,10 +114,10 @@ "outputs": [], "source": [ "def flatten_pred(pred):\n", - " return d2l.flatten(pred.permute(0, 2, 3, 1)) # flatten不改变0轴的size\n", + " return mint.flatten(pred.permute(0, 2, 3, 1), start_dim=1) # flatten不改变0轴的size\n", "\n", "def concat_preds(preds):\n", - " return d2l.concat([flatten_pred(p) for p in preds], axis=1)" + " return mint.concat([flatten_pred(p) for p in preds], dim=1)" ] }, { @@ -175,7 +186,7 @@ } ], "source": [ - "forward(d2l.zeros((2, 3, 20, 20)), down_sample_blk(3, 10)).shape" + "forward(mint.zeros((2, 3, 20, 20)), down_sample_blk(3, 10)).shape" ] }, { @@ -211,7 +222,7 @@ " blk.append(down_sample_blk(num_filters[i], num_filters[i+1]))\n", " return nn.SequentialCell(*blk)\n", "\n", - "forward(d2l.zeros((2, 3, 256, 256)), base_net()).shape" + "forward(mint.zeros((2, 3, 256, 256)), base_net()).shape" ] }, { @@ -296,7 +307,7 @@ " X, anchors[i], cls_preds[i], bbox_preds[i] = blk_forward(\n", " X, getattr(self, f'blk_{i}'), sizes[i], ratios[i],\n", " getattr(self, f'cls_{i}'), getattr(self, f'bbox_{i}'))\n", - " anchors = d2l.concat(anchors, axis=1)\n", + " anchors = mint.concat(anchors, dim=1)\n", " cls_preds = concat_preds(cls_preds)\n", " cls_preds = cls_preds.reshape(\n", " cls_preds.shape[0], -1, self.num_classes + 1)\n", @@ -322,7 +333,7 @@ ], "source": [ "net = TinySSD(num_classes=1)\n", - "X = d2l.zeros((32, 3, 256, 256))\n", + "X = mint.zeros((32, 3, 256, 256))\n", "anchors, cls_preds, bbox_preds = net(X)\n", "\n", "print('output anchors:', anchors.shape)\n", @@ -357,13 +368,18 @@ "output_type": "stream", "text": [ "read 1000 training examples\n", - "read 100 validation examples\n" + "read 100 validation examples\n", + "250\n" ] } ], "source": [ - "batch_size = 32\n", - "train_iter, _ = d2l.load_data_bananas(batch_size) # " + "# 将 Batch Size 设为 4\n", + "# 后续的 multibox_target 函数包含大量基于 CPU 的 Python 循环操作。如果 Batch Size 过大,CPU 计算压力过大导致流水线阻塞,NPU 长期空闲,程序会表现为卡死。\n", + "# 改小 Batch Size 可显著减少单次迭代的 CPU 负担,快速跑通代码。\n", + "batch_size = 4\n", + "train_iter, _ = d2l.load_data_bananas(batch_size) # \n", + "print(train_iter.get_dataset_size())" ] }, { @@ -398,7 +414,7 @@ "def calc_loss(cls_preds, cls_labels, bbox_preds, bbox_labels, bbox_masks):\n", " batch_size, num_classes = cls_preds.shape[0], cls_preds.shape[2]\n", " cls = cls_loss(cls_preds.reshape(-1, num_classes),\n", - " cls_labels.reshape(-1)).reshape(batch_size, -1).mean(axis=1)\n", + " cls_labels.reshape(-1).astype(mindspore.int32)).reshape(batch_size, -1).mean(axis=1)\n", " bbox = bbox_loss(bbox_preds * bbox_masks,\n", " bbox_labels * bbox_masks).mean(axis=1)\n", " return cls + bbox" @@ -417,7 +433,7 @@ " cls_labels.dtype) == cls_labels).sum())\n", "\n", "def bbox_eval(bbox_preds, bbox_labels, bbox_masks):\n", - "# return float((d2l.abs((bbox_labels - bbox_preds) * bbox_masks)).sum())\n", + "# return float((mint.abs((bbox_labels - bbox_preds) * bbox_masks)).sum())\n", " return float(((bbox_labels - bbox_preds) * bbox_masks).abs().sum())" ] }, @@ -493,7 +509,7 @@ " label[:, 1:], anchors)\n", " bbox_mask = ops.tile((anchors_bbox_map >= 0).float().unsqueeze(-1), (1, 4))\n", " # 将类标签和分配的边界框坐标初始化为零\n", - " class_labels = ops.zeros(num_anchors, dtype=mindspore.int32)\n", + " class_labels = ops.zeros(num_anchors, dtype=mindspore.int64)\n", " assigned_bb = ops.zeros((num_anchors, 4), dtype=mindspore.float32)\n", " # 使用真实边界框来标记锚框的类别。\n", " # 如果一个锚框没有被分配,标记其为背景(值为零)\n", @@ -525,7 +541,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "(32, 3, 256, 256) (32, 1, 5)\n" + "(4, 3, 256, 256) (4, 1, 5)\n" ] } ], @@ -547,8 +563,8 @@ "output_type": "stream", "text": [ "output anchors: (1, 5444, 4)\n", - "output class preds: (32, 5444, 2)\n", - "output bbox preds: (32, 21776)\n" + "output class preds: (4, 5444, 2)\n", + "output bbox preds: (4, 21776)\n" ] } ], @@ -567,21 +583,13 @@ "scrolled": true }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[WARNING] KERNEL(269803,2aecc71afd80,python):2023-02-23-20:56:28.763.896 [mindspore/ccsrc/plugin/device/gpu/kernel/cuda_impl/cuda_class/cuda_class_common.h:51] CalShapesSizeInBytes] For 'Argmax', the shapes[0] is ( )\n", - "[WARNING] KERNEL(269803,2aecc71afd80,python):2023-02-23-20:56:28.763.965 [mindspore/ccsrc/plugin/device/gpu/kernel/cuda_impl/cuda_class/cuda_class_common.h:51] CalShapesSizeInBytes] For 'Argmax', the shapes[0] is ( )\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "bbox_labels: (32, 21776) (32, 21776)\n", - "bbox_masks: (32, 21776) Float32\n", - "cls_labels: (32, 5444) Int32\n" + ".bbox_labels: (4, 21776) (4, 21776)\n", + "bbox_masks: (4, 21776) Float32\n", + "cls_labels: (4, 5444) Int64\n" ] } ], @@ -601,7 +609,7 @@ { "data": { "text/plain": [ - "Tensor(shape=[], dtype=Float32, value= 0.69856)" + "Tensor(shape=[], dtype=Float32, value= 0.705361)" ] }, "execution_count": 22, @@ -616,18 +624,34 @@ }, { "cell_type": "markdown", - "id": "9c78354a", + "id": "11899268-b5c4-4b96-bfbb-3a372813b9e4", "metadata": {}, "source": [ - "# BUG 直接运行的话,这里会卡住" + "#### 13.7.2.3. 单批次试运行\n", + "从数据集中取出一批数据,完整走一遍全部过程,旨在验证各环节的张量形状和计算逻辑是否正确,只跑一轮就退出,不进行参数更新。" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "id": "5e0d0317", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 3, 256, 256) (4, 1, 5)\n", + "output anchors: (1, 5444, 4)\n", + "output class preds: (4, 5444, 2)\n", + "output bbox preds: (4, 21776)\n", + "bbox_labels: (4, 21776) (4, 21776)\n", + "bbox_masks: (4, 21776) Float32\n", + "cls_labels: (4, 5444) Int64\n", + "[0.713037 0.70012754 0.6992287 0.707439 ]\n" + ] + } + ], "source": [ "#forward\n", "for X, Y in train_iter:\n", @@ -650,12 +674,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "id": "6ef20694", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 3, 256, 256) (4, 1, 5)\n", + "output anchors: (1, 5444, 4)\n", + "output class preds: (4, 5444, 2)\n", + "output bbox preds: (4, 21776)\n", + "bbox_labels: (4, 21776) (4, 21776)\n", + "bbox_masks: (4, 21776) Float32\n", + "cls_labels: (4, 5444) Int64\n", + "[0.7040471 0.70199287 0.7137333 0.69965523]\n" + ] + } + ], "source": [ - "X, Y = next(train_iter)\n", + "X, Y = next(train_iter.create_tuple_iterator())\n", "print(X.shape, Y.shape)\n", "anchors, cls_preds, bbox_preds = net(X)\n", "print('output anchors:', anchors.shape)\n", @@ -677,7 +716,7 @@ "id": "6912bb2d", "metadata": {}, "source": [ - "#### 13.7.2.3. 训练模型" + "#### 13.7.2.4. 训练模型" ] }, { @@ -730,9 +769,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -744,7 +783,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.5" + "version": "3.10.14" }, "toc": { "base_numbering": 1, diff --git a/chapter_13_computer-vision/10.transposed-conv.ipynb b/chapter_13_computer-vision/10.transposed-conv.ipynb index 14c3057..ae39eba 100644 --- a/chapter_13_computer-vision/10.transposed-conv.ipynb +++ b/chapter_13_computer-vision/10.transposed-conv.ipynb @@ -2,14 +2,24 @@ "cells": [ { "cell_type": "code", - "execution_count": 18, + "execution_count": 1, "id": "3aa6ec79", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(181125,ffff8841b640,python):2025-12-21-09:16:19.929.378 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + } + ], "source": [ "import mindspore\n", "import mindspore.nn as nn\n", - "import mindspore.ops as ops\n", + "from mindspore import mint\n", + "import sys\n", + "sys.path.insert(0, \"..\")\n", "from d2l import mindspore as d2l" ] }, @@ -22,7 +32,7 @@ "source": [ "def trans_conv(X, K):\n", " h, w = K.shape\n", - " Y = ops.zeros((X.shape[0] + h - 1, X.shape[1] + w - 1))\n", + " Y = mint.zeros((X.shape[0] + h - 1, X.shape[1] + w - 1))\n", " for i in range(X.shape[0]):\n", " for j in range(X.shape[1]):\n", " Y[i: i + h, j: j + w] += X[i, j] * K\n", @@ -57,7 +67,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "id": "e59b8fa4", "metadata": {}, "outputs": [ @@ -70,20 +80,20 @@ " [ 4.00000000e+00, 1.20000000e+01, 9.00000000e+00]]]])" ] }, - "execution_count": 7, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X, K = X.reshape(1, 1, 2, 2), K.reshape(1, 1, 2, 2)\n", - "tconv = nn.Conv2dTranspose(1, 1, kernel_size=2, pad_mod='valid', has_bias=False, weight_init=K)\n", + "tconv = nn.Conv2dTranspose(1, 1, kernel_size=2, pad_mode='valid', has_bias=False, weight_init=K)\n", "tconv(X)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "5f87c940", "metadata": {}, "outputs": [ @@ -94,7 +104,7 @@ "[[[[ 4.00000000e+00]]]])" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -107,10 +117,17 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "id": "b358a901", "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "." + ] + }, { "data": { "text/plain": [ @@ -121,7 +138,7 @@ " [ 4.00000000e+00, 6.00000000e+00, 6.00000000e+00, 9.00000000e+00]]]])" ] }, - "execution_count": 9, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -133,7 +150,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 8, "id": "5bbb56ac", "metadata": {}, "outputs": [ @@ -143,7 +160,7 @@ "True" ] }, - "execution_count": 16, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -151,7 +168,7 @@ "source": [ "import mindspore.common.initializer as init\n", "\n", - "X = ops.randn((1, 10, 16, 16))\n", + "X = mint.randn((1, 10, 16, 16))\n", "conv = nn.Conv2d(10, 20, kernel_size=5, pad_mode='pad', padding=2, stride=3, has_bias=True)\n", "k = (conv.group / (conv.in_channels * conv.kernel_size[0] * conv.kernel_size[1])) ** 0.5\n", "conv.weight_init = init.initializer(init.Uniform(k), conv.weight.shape, conv.weight.dtype)\n", @@ -165,7 +182,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 9, "id": "afeeb44d", "metadata": {}, "outputs": [ @@ -177,13 +194,13 @@ " [ 5.70000000e+01, 6.70000000e+01]])" ] }, - "execution_count": 21, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "X = ops.arange(9.0).reshape(3, 3)\n", + "X = mint.arange(9.0).reshape(3, 3)\n", "K = mindspore.Tensor([[1.0, 2.0], [3.0, 4.0]])\n", "Y = d2l.corr2d(X, K)\n", "Y" @@ -191,7 +208,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 10, "id": "f0dabb00", "metadata": {}, "outputs": [ @@ -205,14 +222,14 @@ " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00 ... 0.00000000e+00, 3.00000000e+00, 4.00000000e+00]])" ] }, - "execution_count": 20, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def kernel2matrix(K):\n", - " k, W = ops.zeros(5), ops.zeros((4, 9))\n", + " k, W = mint.zeros(5), mint.zeros((4, 9))\n", " k[:2], k[3:5] = K[0, :], K[1, :]\n", " W[0, :5], W[1, 1:6], W[2, 3:8], W[3, 4:] = k, k, k, k\n", " return W\n", @@ -223,7 +240,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 11, "id": "fab9c18a", "metadata": {}, "outputs": [ @@ -235,18 +252,18 @@ " [ True, True]])" ] }, - "execution_count": 22, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Y == ops.matmul(W, X.reshape(-1)).reshape(2, 2)" + "Y == mint.matmul(W, X.reshape(-1)).reshape(2, 2)" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 12, "id": "33584d70", "metadata": {}, "outputs": [ @@ -259,14 +276,14 @@ " [ True, True, True]])" ] }, - "execution_count": 23, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Z = trans_conv(Y, K)\n", - "Z == ops.matmul(W.T, Y.reshape(-1)).reshape(3, 3)" + "Z == mint.matmul(W.T, Y.reshape(-1)).reshape(3, 3)" ] }, { @@ -280,9 +297,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -294,7 +311,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.11" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_13_computer-vision/12.neural-style.ipynb b/chapter_13_computer-vision/12.neural-style.ipynb index bec555a..b6637f6 100644 --- a/chapter_13_computer-vision/12.neural-style.ipynb +++ b/chapter_13_computer-vision/12.neural-style.ipynb @@ -2,10 +2,17 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "ebb23efa-622c-468b-822b-3a1ca8f8d1d3", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(186460,ffffbead6640,python):2025-12-21-09:26:27.952.965 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + }, { "data": { "image/svg+xml": [ @@ -17,11 +24,11 @@ " \n", " \n", " \n", - " 2023-03-05T11:44:27.193342\n", + " 2025-12-21T09:26:34.157258\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.5.1, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -36,9 +43,8 @@ "L 250.345337 164.997876 \n", "L 250.345337 0 \n", "L 0 0 \n", - "L 0 164.997876 \n", "z\n", - "\" style=\"fill: none\"/>\n", + "\" style=\"fill: #ffffff\"/>\n", " \n", " \n", " \n", @@ -49,25 +55,25 @@ "z\n", "\" style=\"fill: #ffffff\"/>\n", " \n", - " \n", + " \n", " \n", + 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\" id=\"imagecdcc191f9c\" transform=\"scale(1 -1) translate(0 -130.32)\" x=\"39.65\" y=\"-10.799751\" width=\"195.84\" height=\"130.32\"/>\n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -188,12 +194,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -250,12 +256,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -265,12 +271,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -280,12 +286,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -323,12 +329,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -360,19 +366,17 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", "\n" ], "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -380,12 +384,14 @@ "%matplotlib inline\n", "import numpy as np\n", "import mindspore\n", - "import mindspore.ops as ops\n", "import mindspore.nn as nn\n", "import mindspore.dataset.vision as vision\n", "import mindspore.dataset.transforms as transforms\n", "from mindspore import Parameter\n", "from mindspore.common.initializer import initializer\n", + "from mindspore import mint\n", + "import sys\n", + "sys.path.insert(0, \"..\")\n", "from d2l import mindspore as d2l\n", "\n", "d2l.set_figsize()\n", @@ -405,16 +411,16 @@ "\n", "\n", - "\n", + "\n", " \n", " \n", " \n", " \n", - " 2023-03-05T11:44:27.914710\n", + " 2025-12-21T09:26:38.524579\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.5.1, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -425,42 +431,41 @@ " \n", " \n", " \n", - " \n", + "\" style=\"fill: #ffffff\"/>\n", " \n", " \n", " \n", - " \n", " \n", - " \n", + " \n", " \n", + 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\" id=\"imageda527086f8\" transform=\"scale(1 -1) translate(0 -136.8)\" x=\"39.65\" y=\"-10.636231\" width=\"195.84\" height=\"136.8\"/>\n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -583,17 +588,17 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -601,12 +606,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -796,41 +801,39 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "\n" ], "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -861,15 +864,15 @@ "def postprocess(img):\n", " img = img[0]\n", " #print(img)\n", - " img = ops.maximum(img.permute(1, 2, 0) * rgb_std + rgb_mean, 0)\n", - " img = ops.minimum(img, 255)\n", + " img = mint.maximum(img.permute(1, 2, 0) * rgb_std + rgb_mean, 0)\n", + " img = mint.minimum(img, 255)\n", " img = img.asnumpy().astype('uint8')\n", " return vision.ToPIL()(img)" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "288f41b8-af2a-4660-8920-38c2850d360c", "metadata": {}, "outputs": [ @@ -877,27 +880,22 @@ "name": "stderr", "output_type": "stream", "text": [ - "[WARNING] ME(176498:281473357277760,MainProcess):2023-03-05-11:44:28.109.735 [mindspore/common/api.py:840] 'mindspore.ms_class' will be deprecated and removed in a future version. Please use 'mindspore.jit_class' instead.\n", - "[WARNING] ME(176498:281473357277760,MainProcess):2023-03-05-11:44:28.143.843 [mindspore/common/api.py:694] 'mindspore.ms_function' will be deprecated and removed in a future version. Please use 'mindspore.jit' instead.\n", - "[WARNING] ME(176498:281473357277760,MainProcess):2023-03-05-11:44:28.146.711 [mindspore/common/api.py:694] 'mindspore.ms_function' will be deprecated and removed in a future version. Please use 'mindspore.jit' instead.\n", - "WARNING:root:This parameter `keep_prob` will be deprecated, please use `p` instead.\n", - "WARNING:root:This parameter `keep_prob` will be deprecated, please use `p` instead.\n", - "[WARNING] ME(176498:281473357277760,MainProcess):2023-03-05-11:44:32.774.459 [mindspore/train/serialization.py:1024] For 'load_param_into_net', 1 parameters in the 'net' are not loaded, because they are not in the 'parameter_dict', please check whether the network structure is consistent when training and loading checkpoint.\n", - "[WARNING] ME(176498:281473357277760,MainProcess):2023-03-05-11:44:32.777.162 [mindspore/train/serialization.py:1026] classifier.6.weight is not loaded.\n" + "1153300480B [00:26, 43410981.76B/s] \n" ] } ], "source": [ "import mindcv\n", "\n", - "pretrained_net = mindcv.create_model('vgg19', pretrained=False)\n", - "param = mindspore.load_checkpoint('./1.ckpt')\n", - "net = mindspore.load_param_into_net(pretrained_net, param)" + "pretrained_net = mindcv.create_model('vgg19', pretrained=True)\n", + "# pretrained_net = mindcv.create_model('vgg19', pretrained=False)\n", + "# param = mindspore.load_checkpoint('./1.ckpt')\n", + "# net = mindspore.load_param_into_net(pretrained_net, param)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "1adbb1d0-161b-467b-af1b-f92c3b9a071e", "metadata": {}, "outputs": [], @@ -907,7 +905,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "73458d34-f497-4580-baaa-0cf86a5688f3", "metadata": {}, "outputs": [], @@ -918,7 +916,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "e7d49ec1-d395-4021-8fb9-277fa92edb87", "metadata": {}, "outputs": [], @@ -937,7 +935,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "77d3ec15-df0c-4da1-8d0d-9ffc76f4e87e", "metadata": {}, "outputs": [], @@ -956,7 +954,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "5773c5f2-6ad8-485a-b55f-fe8b02a1d609", "metadata": {}, "outputs": [], @@ -964,12 +962,12 @@ "def content_loss(Y_hat, Y):\n", " # 我们从动态计算梯度的树中分离目标:\n", " # 这是一个规定的值,而不是一个变量。\n", - " return ops.square(Y_hat - Y).mean()" + " return mint.square(Y_hat - Y).mean()" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "087cf0b7-7097-494f-9ef3-f66a04d81e2c", "metadata": {}, "outputs": [], @@ -977,34 +975,41 @@ "def gram(X):\n", " num_channels, n = X.shape[1], X.numel() // X.shape[1]\n", " X = X.reshape((num_channels, n))\n", - " return ops.matmul(X, X.T) / (num_channels * n)" + " return mint.matmul(X, X.T) / (num_channels * n)" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "934ffff3-4418-47cd-b492-d261cbf6a1f8", "metadata": {}, "outputs": [], "source": [ "def style_loss(Y_hat, gram_Y):\n", " #print(ops.square(gram(Y_hat) - gram_Y).mean())\n", - " return ops.square(gram(Y_hat) - gram_Y).mean()" + " return mint.square(gram(Y_hat) - gram_Y).mean()" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "51e7fbac-23c1-4a27-a793-6a50299e28f2", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] DEVICE(186460,fffe7a14d120,python):2025-12-21-09:34:27.364.681 [mindspore/ccsrc/plugin/ascend/res_manager/mem_manager/ascend_memory_adapter.cc:127] Initialize] Free memory size is less than half of total memory size.Device 0 Device MOC total size:65464696832 Device MOC free size:3987701760 may be other processes occupying this card, check as: ps -ef|grep python\n" + ] + }, { "data": { "text/plain": [ "Tensor(shape=[], dtype=Int64, value= 13)" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -1014,29 +1019,29 @@ "a = d2l.Tensor([[1,2,3],[4,5,6]])\n", "b = d2l.Tensor([[5,6,9],[2,3,4]])\n", "#print(ops.square(a - b))\n", - "ops.square(a - b).mean()" + "mint.square(a - b).mean()" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "f8cd43aa-2cd3-4c29-a70a-f18c501fd50b", "metadata": {}, "outputs": [], "source": [ "def tv_loss(Y_hat):\n", - " return 0.5 * (ops.abs(Y_hat[:, :, 1:, :] - Y_hat[:, :, :-1, :]).mean() +\n", - " ops.abs(Y_hat[:, :, :, 1:] - Y_hat[:, :, :, :-1]).mean())" + " return 0.5 * (mint.abs(Y_hat[:, :, 1:, :] - Y_hat[:, :, :-1, :]).mean() +\n", + " mint.abs(Y_hat[:, :, :, 1:] - Y_hat[:, :, :, :-1]).mean())" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "id": "524f0f4a-5962-450c-860e-6cd7ae58f8f6", "metadata": {}, "outputs": [], "source": [ - "content_weight, style_weight, tv_weight = 1, 1e, 10\n", + "content_weight, style_weight, tv_weight = 1, 1e3, 10\n", "\n", "def compute_loss(X, contents_Y_hat, styles_Y_hat, contents_Y, styles_Y_gram):\n", " # 分别计算内容损失、风格损失和全变分损失\n", @@ -1053,7 +1058,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "id": "7145a240-1a1a-462c-83e7-a909fd5c4c2e", "metadata": {}, "outputs": [], @@ -1061,7 +1066,7 @@ "class SynthesizedImage(nn.Cell):\n", " def __init__(self, img_shape):\n", " super().__init__()\n", - " self.weight = Parameter(ops.rand(*img_shape))\n", + " self.weight = Parameter(mint.rand(*img_shape))\n", "\n", " def construct(self):\n", " return mindspore.Tensor(self.weight)" @@ -1069,7 +1074,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, "id": "3936bb7b-5337-47ce-8531-51f927c98a5b", "metadata": {}, "outputs": [], @@ -1086,7 +1091,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, "id": "aa61c248-216d-4983-872e-de00b00852a3", "metadata": {}, "outputs": [], @@ -1101,7 +1106,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "id": "820e2f4a-1057-4721-91ad-8bd14e04b535", "metadata": {}, "outputs": [ @@ -1111,16 +1116,16 @@ "\n", "\n", - "\n", + "\n", " \n", " \n", " \n", " \n", - " 2023-03-05T12:21:46.770935\n", + " 2025-12-21T09:48:03.939646\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.5.1, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -1131,43 +1136,42 @@ " \n", " \n", " \n", - " \n", + "\" style=\"fill: #ffffff\"/>\n", " \n", " \n", " \n", - " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " 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id=\"image650de2a67c\" transform=\"scale(1 -1) translate(0 -118.8)\" x=\"260\" y=\"-16.55625\" width=\"177.84\" height=\"118.8\"/>\n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2125,14 +2124,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2140,14 +2139,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2155,14 +2154,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2171,43 +2170,43 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2216,39 +2215,39 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "\n" ], "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -2261,7 +2260,7 @@ " network = Network(X, X.shape)\n", " lr_list = d2l.tensor([lr*(0.8**(i//lr_decay_epoch)) \n", " for i in range(num_epochs)])\n", - " trainer = nn.Adam(network.get_parameters(), lr=lr_list)\n", + " trainer = nn.Adam(network.get_parameters(), learning_rate=lr_list)\n", " animator = d2l.Animator(xlabel='epoch', ylabel='loss',\n", " xlim=[10, num_epochs],\n", " legend=['content', 'style', 'TV'],\n", @@ -2309,9 +2308,9 @@ ], "metadata": { "kernelspec": { - "display_name": "MindSpore", + "display_name": "Python 3.10", "language": "python", - "name": "mindspore" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -2323,7 +2322,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.10" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_13_computer-vision/14.kaggle-dog.ipynb b/chapter_13_computer-vision/14.kaggle-dog.ipynb index 979b1e8..40e0268 100644 --- a/chapter_13_computer-vision/14.kaggle-dog.ipynb +++ b/chapter_13_computer-vision/14.kaggle-dog.ipynb @@ -307,9 +307,9 @@ ], "metadata": { "kernelspec": { - "display_name": "MindSpore", + "display_name": "Python 3.10", "language": "python", - "name": "mindspore" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -321,7 +321,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.10" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_13_computer-vision/4.anchor.ipynb b/chapter_13_computer-vision/4.anchor.ipynb index 73c3d28..712e385 100644 --- a/chapter_13_computer-vision/4.anchor.ipynb +++ b/chapter_13_computer-vision/4.anchor.ipynb @@ -4,16 +4,27 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(174300,ffff851dd640,python):2025-12-21-08:59:08.526.788 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n", + "[WARNING] ME(174300:281472915068480,MainProcess):2025-12-21-08:59:13.244.000 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead.\n" + ] + } + ], "source": [ "%matplotlib inline\n", "import mindspore\n", - "import mindspore.ops as ops\n", "import mindspore.numpy as mnp\n", + "from mindspore import mint\n", + "import sys\n", + "sys.path.insert(0, \"..\")\n", "from d2l import mindspore as d2l\n", "\n", "# 设置使用设备\n", - "mindspore.set_context(device_target='GPU')" + "mindspore.set_context(device_target='Ascend')" ] }, { @@ -38,25 +49,25 @@ " steps_w = 1.0 / in_width # 在x轴上缩放步长\n", "\n", " # 生成锚框的所有中心点\n", - " center_h = (ops.arange(in_height) + offset_h) * steps_h\n", - " center_w = (ops.arange(in_width) + offset_w) * steps_w\n", - " shift_y, shift_x = ops.meshgrid(center_h, center_w, indexing='ij')\n", + " center_h = (mint.arange(in_height) + offset_h) * steps_h\n", + " center_w = (mint.arange(in_width) + offset_w) * steps_w\n", + " shift_y, shift_x = mint.meshgrid(center_h, center_w, indexing='ij')\n", " shift_y, shift_x = shift_y.reshape(-1), shift_x.reshape(-1)\n", "\n", " # 生成“boxes_per_pixel”个高和宽,\n", " # 之后用于创建锚框的四角坐标(xmin,xmax,ymin,ymax)\n", - " w = ops.concat((size_tensor * ops.sqrt(ratio_tensor[0]),\n", - " sizes[0] * ops.sqrt(ratio_tensor[1:])))\\\n", + " w = mint.concat((size_tensor * mint.sqrt(ratio_tensor[0]),\n", + " sizes[0] * mint.sqrt(ratio_tensor[1:])))\\\n", " * in_height / in_width # 处理矩形输入\n", - " h = ops.concat((size_tensor / ops.sqrt(ratio_tensor[0]),\n", - " sizes[0] / ops.sqrt(ratio_tensor[1:])))\n", + " h = mint.concat((size_tensor / mint.sqrt(ratio_tensor[0]),\n", + " sizes[0] / mint.sqrt(ratio_tensor[1:])))\n", " # 除以2来获得半高和半宽\n", - " anchor_manipulations = ops.tile(ops.stack((-w, -h, w, h)).T,\n", + " anchor_manipulations = mint.tile(mint.stack((-w, -h, w, h)).T,\n", " (in_height * in_width, 1)) / 2\n", " # 每个中心点都将有“boxes_per_pixel”个锚框,\n", " # 所以生成含所有锚框中心的网格,重复了“boxes_per_pixel”次\n", - " out_grid = ops.stack([shift_x, shift_y, shift_x, shift_y],\n", - " axis=1).repeat_interleave(boxes_per_pixel, dim=0)\n", + " out_grid = mint.stack([shift_x, shift_y, shift_x, shift_y],\n", + " dim=1).repeat_interleave(boxes_per_pixel, dim=0)\n", " output = out_grid + anchor_manipulations\n", " return output.unsqueeze(0)" ] @@ -89,7 +100,7 @@ "h, w = img.shape[:2]\n", "\n", "print(h, w)\n", - "X = ops.randn((1, 3, h, w))\n", + "X = mint.randn((1, 3, h, w))\n", "Y = multibox_prior(X, sizes=[0.75, 0.5, 0.25], ratios=[1, 2, 0.5])\n", "Y.shape" ] @@ -174,16 +185,16 @@ "\n", "\n", - "\n", + "\n", " \n", " \n", " \n", " \n", - " 2023-02-17T21:30:45.644199\n", + " 2025-12-21T08:59:35.014540\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.5.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -194,87 +205,86 @@ " \n", " \n", " \n", - " \n", + "\" style=\"fill: #ffffff\"/>\n", " \n", " \n", " \n", - " \n", " \n", - " \n", + " \n", " \n", + 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" \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -449,12 +459,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -495,12 +505,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -559,12 +569,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -758,15 +768,15 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -782,15 +792,15 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -806,15 +816,15 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -833,19 +843,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "\n" ], "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -878,8 +886,8 @@ " areas2 = box_area(boxes2)\n", " # inter_upperlefts,inter_lowerrights,inters的形状:\n", " # (boxes1的数量,boxes2的数量,2)\n", - " inter_upperlefts = ops.maximum(boxes1[:, None, :2], boxes2[:, :2])\n", - " inter_lowerrights = ops.minimum(boxes1[:, None, 2:], boxes2[:, 2:])\n", + " inter_upperlefts = mint.maximum(boxes1[:, None, :2], boxes2[:, :2])\n", + " inter_lowerrights = mint.minimum(boxes1[:, None, 2:], boxes2[:, 2:])\n", " inters = (inter_lowerrights - inter_upperlefts).clamp(min=0)\n", " # inter_areasandunion_areas的形状:(boxes1的数量,boxes2的数量)\n", " inter_areas = inters[:, :, 0] * inters[:, :, 1]\n", @@ -889,7 +897,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -900,18 +908,18 @@ " # 位于第i行和第j列的元素x_ij是锚框i和真实边界框j的IoU\n", " jaccard = box_iou(anchors, ground_truth)\n", " # 对于每个锚框,分配的真实边界框的张量\n", - " anchors_bbox_map = ops.full((num_anchors,), -1, dtype=mindspore.int64)\n", + " anchors_bbox_map = mint.full((num_anchors,), -1, dtype=mindspore.int64)\n", " # 根据阈值,决定是否分配真实边界框\n", - " indices, max_ious = ops.max(jaccard, axis=1)\n", - " anc_i = ops.nonzero(max_ious >= iou_threshold).reshape(-1)\n", + " indices, max_ious = mint.max(jaccard, dim=1)\n", + " anc_i = mint.nonzero(max_ious >= iou_threshold).reshape(-1)\n", " # box_j = indices[max_ious >= iou_threshold]\n", " anchors_bbox_map[anc_i] = 1\n", - " col_discard = ops.full((num_anchors,), -1)\n", - " row_discard = ops.full((num_gt_boxes,), -1)\n", + " col_discard = mint.full((num_anchors,), -1)\n", + " row_discard = mint.full((num_gt_boxes,), -1)\n", " for _ in range(num_gt_boxes):\n", - " max_idx = ops.argmax(jaccard)\n", - " box_idx = (max_idx % num_gt_boxes).long()\n", - " anc_idx = (max_idx / num_gt_boxes).long()\n", + " max_idx = mint.argmax(jaccard)\n", + " box_idx = (max_idx % num_gt_boxes).astype(mindspore.int64)\n", + " anc_idx = (max_idx / num_gt_boxes).astype(mindspore.int64)\n", " anchors_bbox_map[anc_idx] = box_idx\n", " jaccard[:, box_idx] = col_discard\n", " jaccard[anc_idx, :] = row_discard\n", @@ -920,7 +928,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -930,14 +938,14 @@ " c_anc = d2l.box_corner_to_center(anchors)\n", " c_assigned_bb = d2l.box_corner_to_center(assigned_bb)\n", " offset_xy = 10 * (c_assigned_bb[:, :2] - c_anc[:, :2]) / c_anc[:, 2:]\n", - " offset_wh = 5 * ops.log(eps + c_assigned_bb[:, 2:] / c_anc[:, 2:])\n", - " offset = ops.concat([offset_xy, offset_wh], axis=1)\n", + " offset_wh = 5 * mint.log(eps + c_assigned_bb[:, 2:] / c_anc[:, 2:])\n", + " offset = mint.concat([offset_xy, offset_wh], dim=1)\n", " return offset" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -951,13 +959,13 @@ " label = labels[i, :, :]\n", " anchors_bbox_map = assign_anchor_to_bbox(\n", " label[:, 1:], anchors)\n", - " bbox_mask = ops.tile((anchors_bbox_map >= 0).float().unsqueeze(-1), (1, 4))\n", + " bbox_mask = mint.tile((anchors_bbox_map >= 0).float().unsqueeze(-1), (1, 4))\n", " # 将类标签和分配的边界框坐标初始化为零\n", - " class_labels = ops.zeros(num_anchors, dtype=mindspore.int64)\n", - " assigned_bb = ops.zeros((num_anchors, 4), dtype=mindspore.float32)\n", + " class_labels = mint.zeros(num_anchors, dtype=mindspore.int64)\n", + " assigned_bb = mint.zeros((num_anchors, 4), dtype=mindspore.float32)\n", " # 使用真实边界框来标记锚框的类别。\n", " # 如果一个锚框没有被分配,标记其为背景(值为零)\n", - " indices_true = ops.nonzero(anchors_bbox_map >= 0)\n", + " indices_true = mint.nonzero(anchors_bbox_map >= 0)\n", " bb_idx = anchors_bbox_map[indices_true]\n", " class_labels[indices_true] = label[bb_idx, 0].long() + 1\n", " assigned_bb[indices_true] = label[bb_idx, 1:]\n", @@ -966,15 +974,15 @@ " batch_offset.append(offset.reshape(-1))\n", " batch_mask.append(bbox_mask.reshape(-1))\n", " batch_class_labels.append(class_labels)\n", - " bbox_offset = ops.stack(batch_offset)\n", - " bbox_mask = ops.stack(batch_mask)\n", - " class_labels = ops.stack(batch_class_labels)\n", + " bbox_offset = mint.stack(batch_offset)\n", + " bbox_mask = mint.stack(batch_mask)\n", + " class_labels = mint.stack(batch_class_labels)\n", " return (bbox_offset, bbox_mask, class_labels)" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -983,16 +991,16 @@ "\n", "\n", - "\n", + "\n", " \n", " \n", " \n", " \n", - " 2023-02-17T21:30:53.492089\n", + " 2025-12-21T09:00:31.672935\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.5.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -1003,105 +1011,104 @@ " \n", " \n", " \n", - " \n", + "\" style=\"fill: #ffffff\"/>\n", " \n", " \n", " \n", - " \n", " \n", - " \n", + " \n", " \n", + 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miter\"/>\n", " \n", " \n", - " \n", + "\" clip-path=\"url(#pa9d424491b)\" style=\"fill: none; stroke: #00bfbf; stroke-width: 2; stroke-linejoin: miter\"/>\n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1276,12 +1283,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1322,12 +1329,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1386,12 +1393,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "\n" ], "text/plain": [ - "
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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -1741,18 +1746,9 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 18, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[WARNING] KERNEL(40,7f0da30be240,python):2023-02-17-21:30:54.351.680 [mindspore/ccsrc/plugin/device/gpu/kernel/cuda_impl/cuda_class/cuda_class_common.h:51] CalShapesSizeInBytes] For 'Argmax', the shapes[0] is ( )\n", - "[WARNING] KERNEL(40,7f0da30be240,python):2023-02-17-21:30:54.351.713 [mindspore/ccsrc/plugin/device/gpu/kernel/cuda_impl/cuda_class/cuda_class_common.h:51] CalShapesSizeInBytes] For 'Argmax', the shapes[0] is ( )\n" - ] - } - ], + "outputs": [], "source": [ "labels = multibox_target(anchors.unsqueeze(dim=0),\n", " ground_truth.unsqueeze(dim=0))" @@ -1760,17 +1756,17 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Tensor(shape=[1, 5], dtype=Int64, value=\n", - "[[0, 1, 2, 0, 2]])" + "[[0, 1, 2, 2, 2]])" ] }, - "execution_count": 14, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1781,7 +1777,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -1791,7 +1787,7 @@ "[[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00 ... 1.00000000e+00, 1.00000000e+00, 1.00000000e+00]])" ] }, - "execution_count": 15, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1802,7 +1798,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -1812,7 +1808,7 @@ "[[-0.00000000e+00, -0.00000000e+00, -0.00000000e+00 ... -1.00000012e+00, 4.17232332e-06, 6.25820398e-01]])" ] }, - "execution_count": 16, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1823,7 +1819,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ @@ -1832,22 +1828,22 @@ " \"\"\"根据带有预测偏移量的锚框来预测边界框\"\"\"\n", " anc = d2l.box_corner_to_center(anchors)\n", " pred_bbox_xy = (offset_preds[:, :2] * anc[:, 2:] / 10) + anc[:, :2]\n", - " pred_bbox_wh = ops.exp(offset_preds[:, 2:] / 5) * anc[:, 2:]\n", - " pred_bbox = ops.concat((pred_bbox_xy, pred_bbox_wh), axis=1)\n", + " pred_bbox_wh = mint.exp(offset_preds[:, 2:] / 5) * anc[:, 2:]\n", + " pred_bbox = mint.concat((pred_bbox_xy, pred_bbox_wh), dim=1)\n", " predicted_bbox = d2l.box_center_to_corner(pred_bbox)\n", " return predicted_bbox" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "#@save\n", "def nms(boxes, scores, iou_threshold):\n", " \"\"\"对预测边界框的置信度进行排序\"\"\"\n", - " B = ops.argsort(scores, axis=-1, descending=True)\n", + " B = mint.argsort(scores, dim=-1, descending=True)\n", " keep = [] # 保留预测边界框的指标\n", " while B.numel() > 0:\n", " i = B[0]\n", @@ -1855,14 +1851,14 @@ " if B.numel() == 1: break\n", " iou = box_iou(boxes[i, :].reshape(-1, 4),\n", " boxes[B[1:], :].reshape(-1, 4)).reshape(-1)\n", - " inds = ops.nonzero(iou <= iou_threshold).reshape(-1)\n", + " inds = mint.nonzero(iou <= iou_threshold).reshape(-1)\n", " B = B[inds + 1]\n", " return mindspore.Tensor(keep)" ] }, { "cell_type": "code", - "execution_count": 198, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -1876,20 +1872,19 @@ " out = []\n", " for i in range(batch_size):\n", " cls_prob, offset_pred = cls_probs[i], offset_preds[i].reshape(-1, 4)\n", - " class_id, conf = ops.max(cls_prob[1:], 0)\n", + " class_id, conf = mint.max(cls_prob[1:], 0)\n", " predicted_bb = offset_inverse(anchors, offset_pred)\n", " keep = nms(predicted_bb, conf, nms_threshold)\n", "\n", " # 找到所有的non_keep索引,并将类设置为背景\n", - " all_idx = ops.arange(num_anchors, dtype=mindspore.int64)\n", - " combined = ops.concat((keep, all_idx))\n", - " unique = ops.unique(combined)\n", - " uniques, _ = unique[0], unique[1]\n", + " all_idx = mint.arange(num_anchors, dtype=mindspore.int64)\n", + " combined = mint.concat((keep, all_idx))\n", + " uniques = mint.unique(combined)\n", " # 统计未重复的,mindspore的unique无法统计同一个元素出现次数\n", " counts = mnp.bincount(combined)\n", " non_keep = mindspore.Tensor([int(uniques[i]) for i in range(len(counts)) \n", " if (counts[i] == 1)])\n", - " all_id_sorted = ops.concat((keep, non_keep))\n", + " all_id_sorted = mint.concat((keep, non_keep))\n", " class_id[non_keep] = -1\n", " class_id = class_id[all_id_sorted]\n", " conf, predicted_bb = conf[all_id_sorted], predicted_bb[all_id_sorted]\n", @@ -1900,16 +1895,16 @@ " for j in range(len(conf)):\n", " if below_min_idx[j] == True:\n", " conf[j] = 1-conf[j]\n", - " pred_info = ops.concat((class_id.unsqueeze(1),\n", + " pred_info = mint.concat((class_id.unsqueeze(1),\n", " conf.unsqueeze(1),\n", - " predicted_bb), axis=1)\n", + " predicted_bb), dim=1)\n", " out.append(pred_info)\n", - " return ops.stack(out)" + " return mint.stack(out)" ] }, { "cell_type": "code", - "execution_count": 197, + "execution_count": 36, "metadata": {}, "outputs": [ { @@ -1925,7 +1920,7 @@ "[2]" ] }, - "execution_count": 197, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -1940,7 +1935,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -1954,7 +1949,7 @@ }, { "cell_type": "code", - "execution_count": 130, + "execution_count": 38, "metadata": {}, "outputs": [ { @@ -1963,16 +1958,16 @@ "\n", "\n", - "\n", + "\n", " \n", " \n", " \n", " \n", - " 2023-02-17T22:01:10.766754\n", + " 2025-12-21T09:06:35.133650\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.5.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -1983,78 +1978,77 @@ " \n", " \n", " \n", - " \n", + "\" style=\"fill: #ffffff\"/>\n", " \n", " \n", " \n", - " \n", " \n", - " \n", + " \n", " \n", + 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475jGgc3NFf/9/+n/zHd+7Ve4vrrkvXff5ebFp2jp+c5v/RaP3jjDD1ukV9hYsC5L9vvIWbsm9lsWdc2vfvMtzpc167akqCtWF6eEqCjrlnfeeZdyveJ/9l/8Y9794MecnBS0yxN+93d/H+8mSmPoQ2DY7SiUYhwmpqRYWc3aSk5WS5rFkrJd8sMfvUt/29HoinXT0FaWVVOwXq+5vLwk+oH97opn/+L/xaM33+K3/8E/5K2vf4OmXVLVGR/QWsPcjyDkq8f15QmSSPGqaSTI1w8/baB3Pf1nG63+vPU3y9BT/kJ+6onDnjDscOPA0O24ef6Ymyfvo8KWRSlItiY2NUNf0jY1yWXgJ8ZA33d0/Q4XdhQisVyWnJxW+NFzc7Xh8ukLYEAqiy00RgkgMg49ul2QiIzese337HqHSxofBuqmYLGosYVFKoXzCe89VWGQMrLfb7CmIATQRlOUhnHsKYt7gMTHiIxgipLBRcbJsR8mTtoKYxuSj4RxJKpsqC8NfUadZUTEV0kyCoVML8NK5ocn+bIcd7jwktCvIOXyrreX8hVlHPGK588gISkiUiCFmDGSyTHse4b9LbvdlheXl3z00Uf84R//MacnK4zf8uB8yVtv3ufXfvO7lKXFiQoJeCbWp49olxc8vbpiugy88fAep6enPLp/xrIpCQl0UaF0QVFPfOvb30QJxXe/+11uti9ol29wdX1LTJGT1Ypvfv1t3k8RSeL+/ftcbbbcPLvha994g7OThmXboIxm0ZT8xq//KtFFbq5veHBxzmJZcu/ePTabWwqjePjwAfv9nuA9KTj6/Zah26OVJoRAjA3WFj+V6wshiK+E3ZF8eu5smvN5Qf40yPp5If9nw/hfdEj/VzT0fDGnGAljx7h7gdtd4votw/Ul0+aKko6q0pTWEJJESsPYVQx9T3Cewhgmv2dNgxBnhOhIKQARJSVVaZB4SnPGdrNBpIjWEq0jQglCmJjGnqJe4r2gTopkHLe3O9pFwbLRFKWiris6n1DKsFis6XrPNOYIATSbzZ6z0xUhjigN0+TZdQOSSCk1RVXw+NlzklScnN9D2wmpW7rdgJuuiTKXkORd4xMQFTMd9uWJV9nUEZDbYu+UxPJT84WXqQfZo+fyFgg5bwLi5W/ueJHDivHQBxAIfiI6RxwGxv2W3e0t2+snPHvyKR988gQjPc+ffQqx5z//zkO+/Y03efToDZq2JiiNLBtEkqyLJSenJ6xONf918T/l/Y8/RCtBXRY0iyVN25AQuJjQtuSkbPkn/+3/GpBYIVm0Cx4+uk+zWPHrv37N2WrF22++wacff0RTl9y7OOP65obSaoyCVdtADJwsF/TDnrPTcx5cnOCGPXWp+cbX3qQoCgqTN0utNX5SPHpwgdIGIwVu6El1gxSW4ANBveR3yENk9FOVjwOg9+pKUkD62djK55XmfhYT8qsuz30xYFyKRDfg+xum3VPG3SXT5gY5OUojsWWBMBoZE1pZYszU0OA9SkpkTMToUEoQk8cHh4gph+sxUNc1KTq0XuL2A0oLjFHIQpEKi5ipptWqpQ97xBhoqoowjRibPb/zDigJAfpuBFEwTRNDP3F9dcPTJ5dcnJ9QlhpbaMbREwUUJSyamn4aGEZPkoZdP3Ja1wSnefzsKYMCoQVaWpSSKJn73IUUCCOPfe4vwSGFkuqYYx848shXL6LcE5+71z4bZr7i3X8qhyeXuOY+/GkaCePAuLlmvL1m2N7y4ukHXD5/jHGe7759ip4ueOutB/z2dx+xahqaWjG5HmFaUlIMLrA6OUEZBUnw8M37FKXk6uqKxaKlalps3eB9QgqJLUt0YSnrirpq+Lf/4l+yPllzfn7O+b0HPHz0NRZFwdNPP8YqhUyRk+USRaKtStw48PTxJ5ydrDAKLu4/oGlX/PhPf8j56ZJ75ytOlhVCGvw4YK1ls9mgRGK5XmGLkqHb4oYVfuqp6ooEhBCOnvwuG/Nw3+EYf56Xzrwg8VOg3F3a8937DufyLvZy+P1V1+C/AEMXECPRT4jQI8IO110hgkNKsGWFtAXJGGRMSCGQJrOptJTZSIVFKoOQCSUTaRrAJxIhe1gBZVFTaEvUBpUmIIJIeXMg5/h2ueb8UUtT9Wyf35LSBOE2A2/jgK1bfFI8/vQppmgJybJoF3gfkEKRYqCqLUZLgo+UyrI+aZBxx/Z2oFkuWRSnNGcXCOn50Y/e58NPBryNKKPQqkAphUCgtMJojZYCaz8jbKE1QhmM0Qgh8v1ak6RACjl77fybeUM4tL2+/P3y9vFM3MEH4h1Dd84Txx7X7+cqyA24jnurCq0EisS933jEN77xFqZIGB2xKrLt99jyDKEsi+UJzgdMDCzWS66vrvn4w/d59OgNFqsVZVmjiwJpMgHHlJbVyYqyKXn/3Q/4+JNP+Pv/2W+xXC7RtuS+bQhdx4vHHzP2exZNg9EyE6SC4OzkPgy3LJqKi/NTTi/OCAkEnm98/U1O1i1lYfjD//Qn3Lt3D2EUSiTKqqRpaibn+eiD9/na17/ONPQEN4EuOQiRHDx5Pm7i6N2zEWa847MrisP/7lz94mWfxufl7nfv/7wN4ataX0COHnOtOXpkCBiRw1LKOoNR2iKlRiDntuqEUpqkPWEum1hlETJ7qJgCgUhIDiEDKUZcdGipSAKaKrPenBtIk0AR0IVDmBHpJ2y1QK5bApHlhUGLC1y3w2iLMYpmucSWBbtNh3c9QgbWtue3v3nCG/dK3r7XsF5ZrFWs6xI1ecbYo1cV+2kkhsRPfvgRf/L9H/DOO5/STwpRGJSIyJBPqpwN2hpDZQ2LdpFDzFm4QmmJNRkJ1sbMqHCOUJRSOQVAZjaZkjDXjOXR4BVJ2VkA43A/SCGPrbK5CSjmUl6KRB8JUQKBOLxgoUaIASkTVWW5d7qmLvLmixRMYWIKEis9vYsUZYUWirpaMHWOD9/9CFu2LNenWGtIMZDcmIlSQrNoWkpTMu48//Jf/KtsgMs1RbVEa0NRVgzTnr7fsd12nJ1f8PGnj9FG8Ma65cG6Jk05mhIIhFG8/+N3GHc7xOqEjz98wp/96Ce886c/4J/8k/+GGHq0jJyfnLJ3gvff/wA3jKRpwoVZaSglRMxULiEkkphfW+ZUB9KdiGruUbh7qc+baorpZXqWIomDtNjdSoogRfJGfCfc/7x+gr8ZHl0IhFIoY0koRNIYXRHmg2SszeFL8CSRy2LZ2CXJJ0IYsbZ8eSCCQGtD8g6hRGafyVzSmtmVKFuA0rkGPHm0zqScNPZEaTCm4vz+KcLv2G9uUUW+SK1WxDRS15LClIz7jrF3/L3vPOC737zHYlWyWFdIrZAyYvQt0zRyuXP8q//wQ/6H773DfpAk5xgmh7IlQhfosUQGjxZ5Z5+miWEYcNNEoRVNU88gkMAYQ9NUNHVNUZZUZUlRFFhrkCbNhm7R0gBzy6tWaKWysQuJUApMgdIareZNQinMnDJIMW8M4oAVBFLSJDeQ+h0pbDFMGYFWgvOLE1x0qELjxwBComyBSoaQZoxAG4y0jJ3jk48/5eZyyz/+n/+XBD/hp5HgBsIUEbakXdSZR+ES//z//s/56INP+Lt//++gTIEtaowxpJRwEQYHCQNJkZyjLTRv3lvz9sNzxm6LCx5I/If/8Pv86fe/jw2Km8sr3vnoI56+eM5v/fq3kESMiizP1nT7HZ8+3/O93/09/v5v/XrunVCaECMyxhm7CAgxe3QBMsrswefN8mCQh9vHle4An1IeugPIpeXPNC6hOTBExVwKPTz6VfP5akC6LyZHlxrdrJHVitDfZMMXIl+IWmdU3vscVgqB8x4tmNtBPc65Y61TqRzWJ6Nxw5RzqRAQQpIIDMOI1tnzHUKh4ANME0oPSFWQfEQbjYgjhRIUpUUkCNHl1ICYowXrMUqipcE7x3Il0XYi4Qhh5Hbn+eEHl/xf//s/5IOn4EyLLiTrcmC1XmFsgdI2l1xiJHrHNE6UWmBlwluJkRKtwKp8gfW7ntvNLUIZpJRorTHGYI2mLAS2sGhTopRBCI0WCq10zunFfBFJQVR5s1RKz5p3GqP00cMfjqVUEhQkH2HYU7NhZRPTNJFkomhypKHROf82BbKsqdYXyLhgO1QYJZDRkKLgdnvL++++y2/+1m9RlSW73UQInn4YkCSmfsTYmqoKfPDBB/zgBz/g3r17PHz0EGMMQgi0zpt0Pwn+7Mcfst+PtHbLvcUJ5cmKs/UKNw60VcWm6/nD//j7/ODHP6aua9YnZzSLitN1S1NbvvbmI7QEN44QYBgiP/ij/8Tu5gVtXeDGEVPU+BCQ40AKfsY5ZPbQQsx9Afm4JSkyLpIO+Mgd5F3dwUMOIfzcE3A3bZIzpnKg+yNmTYH5vT6P0fhly4J9IYaeUMhqhV3dY9o8nY3y5d51yE0n52dCTcJ5hxYvQZDP8rhBZIpjSozDgCgMpGws3r98XCZCCFJIjPuOaXTADIQll3nWxpAEKKNz3p4CwTtE9IxDT/KOxmpSGNlsPUFWvLja82++9xP+7e99yBTWLE/O0UuBrRxL0VJoAySsVnPEEhl7wUCk7x1CS5QtaSpLSgmjTc65ge0YCEjCTD1N0dN3I1cvtiQEUUiSMihjKWSBnTeFDPDNOboKOZc/GLbS6Pk4a6WOHkcIiGkidjsaMfEb33pAUokQPKUtKQpLjBFTGJIU2LIlKYNUCqst7B1KWRSJbr9hs7lmvSy5d7Gi7ztizOcw+JAJJVIfo5qPPvqIR48e8c1f+Rar1eoV7YFpmri+es562fK1t99g2l4hk6MuFfvtDQ9OGm6unjOFRAqOv/vd32DfDSSRCEw8uFhnbn1wPH/ymPOLE5SxXD17wrIyfPOth7z54BxiICUYhhHl4xwx5Q1QKXUsrWUjv2PcSZKkehkVASne0fA7GDEz6j6DpBlUnY1+jrBSfhBi3kgO+MDhmr/byvwXUQz6H7O+kNA9IkjJYhdn6GqBqGqcn7Jg4/yjlEIncNNEiBEREz75GTRyP4WEAkees9KaFCMx5Jx9mqZ8v1KzoWu88wgCYprmC1/OlafI5B26LBBJELyfa8sQQ8RIjVIJ6aAfAs+HxP/v9/6QP/rRcy43hrJ8xPmqZrms0CpRFDVGKwqtECkgoqPQOjd7CAuuz942JbSWFAqqskZKgQ8BrTRFASEJQog4N+G8RxhNodb0ztP7wHYY6Lc7iBot9SxGKY5IvVQcyTNqvmi1kEcQ74jci0ilJs6sYH1W05iEG3NaocSA0AK73XJSrHMKpSqCABEmCjNwUmuu91u2YyAFT2E93/j6GVZPRFUShqyuG+Z24mbVklJiv98RY+T+/fs8evSI9XqV+exzJNb3HbVx/Oe//S3eumj5d//237CfdiyaAt93dNsNbVVwtdnx9bffott7PnzvI7713W9jS0UaJ2QIlFWVy2yVZr/raeuK00XNt7/+Jo8e3CMZwxA8YRjQckJphZKvVkLEfBwFzMdXIT5LmIkRTzxe0wc+fkoQQjxuGkpmx6KVRauMv0iVN2KUJOmsOpyv25fRVzalLy+M/8K47hFQqsLWK/qNyf3Z3hNi1neTUmKtzCy6OLeAhLwbOhdy+SulY3lKEHPoc0cbbpom3DSilZrRZEdZloCYRSo8RilUiiQfcN7ncFQrRjciTU4jFDmkFiHhBoeIMI2RF3vP//v3fsT3/uwSp89Y3l+xbCWrVlLKRKNPKfQCio7gB7SQaBRhGlApYESiNBIjK6ZpygAZEaOgaWqcm/A+oIAQE1EkolREk4+BUhZpDGLyJK1Qk2PfO3ofCM7NpSF59OSHyEeIedOTCnW3tx+wWvCtBy3rtmDdWFRyTGEkxsg4jqCA60jVlEhl0CJhrSRNHck7KlWhli1TUKSQGHowxuPchqI5Q8qGbXTcu/+A/XbLcrkmItnt9txubjk/u8/JyZpm0SAP7MAUCW6kVAOFnait4803Lpj8QAwTJ02btQekyhFHcPjJk1Lij//4j/jub/waJ3XFus7v9cknn1CWmtXqlIcP7/PWm2+xXC2RWnPTD+z7CDbkCoNSqBnXUHPk85K5OINjSFLKERcpO5xh6NkPHZvtlt12y77r2O72bLY7bm+2pJS9dGEthbXEKFit1oBgvV6jteX07JTV+Zqzs1PWJ6csFgvqpkHJDOAeuvLSne68L8r0v5DyWkYvI1JYVHHGZEogIqQi+ikbpDXEEEkiIRX4EIgxa74lAZNzGCXwk8+1SiIiubxhCHCTRyHxgPd+3iAcwzBQlmCtRUgDQjDNoZEyBu88fphIKVEURUaU/ZC7znyknxJTUOx6wb/5/if8+x/fopt7PDo5Yb2wKA3L5QIzc6ULkyBohK2xWqCFIHrHfnfLfrcjGsGUAkInrDE5NA8jkoLSKvZuwNoCF8C5iJQZnQ++p1SRwkhkiOiYKLWgqAz70TP6yCQEISZCBB/iK4w44SMah5ECSUKLDNi3VcVCSUqVaEqNnwZIIZ83JdAqA6XXz59RGEUIETmpo8fqup6QLFVZ021uaBcLVhePiMkxTddYU9HUJdMQadpzks/lRDd6Ls4vWJ2u6d2AiQV1UVEIwdjdsHn2E0T3FBUjchqptcaqCiVLCpGYxpFdt8f7QDVMbLpAJGGFor/eogZHHBwxRJDQtvdJQrA4aUlSEnRijJF+GNn3e4TYI01O87Q2s5dVCKUQSnKgKOcqBYSQS7aHeQDDMHC7u+HqxXNePLnk2YsXXO537EdH1w2IlFgvWs5P11ycn/H48WPOzi7QuuTm8gXvvfshEHj0YMWjN97k7W98k2//2ne49+ABZ/fOqJoGJQvgs4IgX8z6gjz6/NFSDrOlUiSXkfIDueMgWJCChxhQs75IjCGH/8HhfMRqQb/vESIz7qaxz6zw6HMLo/M57NQaawzTOB6lnKy1xBCJ3iOUxMXAOA7HIQ3TMBLDBGEgkRinyJRKbsbE//f33+OP37/ENvd4cP8Bq0JRF5K6qaiq6hheaaWQUSJJKBGZ+o6x79BS0NYVwU1MQ8Aokev/VYHRBj23U7Z1zX4cc7lPF0xjBinLwjCG3CdQWUOmxSV8SkST82+rElMI+BDx8Y7kFiLn6EJglURLgZaJwmiWTUlVGJrCYrWGMM5ln6wL4KeRqmwQKbK9vqasG0LIzUn9MLDf7TF1S7eNFErQ70dMbXPbsRtR1ZLT9QPiokLbJj+v33NytuLhW28ilKZqG1ShMEjG2yt+/Ce/z/7mY5aVJGJICdpmwc3mhuVqzbrJXWrO5b73aZpYisBbD85p65LgRgoRwA8UdcHJ+RlVW+DCxPXtFVWzQji4vr1mv5/Y7EdiFNnQhcBai7VZG1BoNac6s2JPjFkkJeaQPMZAihlT8tOEGyeIkbP1CRNQVImlnUjBs1o0rKuaX3nzTdZVCcC9ew9JSbC7fMrNzTWn6wX3L86orCFMI/1uR99USK0p5Awyz1b119DQX67M+so+ngQyZaWYEAQ+elL0SCI+hlxCI+aQTgqSD0yDg+Dx0RGcy11wk0OECFJRFQViDuXlnBP1+30uZc2lPK01Q99RGJ1PjsslGqU0+AH8QAqJPmg6NL/7x+/zg48H6tM3ODm/T1saloWktDKHeBK0zCFVih43jogUkSkSXa5HBzfivcNqSV1a3OSoqyJHGoduMyCIRFOV+JSQIiPl0+QJPmGVZIwOJQSFlsSocDEQRK7HaqtQXjLhKDT48BKtLWwWdyiUojAKJcAoQaUlyY+URUOY5qhpDEQCurZEEei2nnbRMBKRwVOWOfWYtrdoQKaRuikojQQZGfor8AN13WOVZ7rx6DYDX123RynJycpSVBZtapQ1JBm4ffacm08/Ytq+wMYBEQpcVASf6PcDSln6fmJRtSA0dVOzWKqczgEpOhZ1jZ8Gbq5fEFOgvX+CLUuEMsTRkaSm20/c3Fxxu93T9w5pLeMwcWhQ09pgjcEWxezlczkyU19z96WUOjOLZ0oywTN2HZfPnqExrFdrnt/esttvefPiAfvNLSYlWmswMXKxXBBi4KwtGYaRi1VJbde8+egBVaEh+lz6I28mzHm/lJGcT6VXEP+/6vpiDV3knPsAdIQQiCFLR7lpQpmcB3k34d2AlolxHHPOJJg3AkeKnuhG/DQRnMOPU9YyS4LJhRk5zRTaQhuMVOx2O/w4oY3BaJ0lqmIkTp7kZ9APxzR0hCmTQZwu+OHjS959NnBy9gbn9+9lL2wFRSkp5gsi59r5s8bg0SkRo8893TGgREIbjVWCISWwBoKnLoqZuZa9iPceBAzeZ2/hJ6Q0FEaTQsCFgLCGyQdiyq9rlUBazegiPjEDcgJlZa49kze9qiwotEKRNwyRAkYKCpX/XRpFdD197wgR2mVJWUiUlhgjqazGWEVME5OLFEVB05Y4N5FkJAWH1BqtDViNS4F+8wLX7yjbNYQ90VbIlHAxYWyLEBNWBvwucnv7jMcffcrVkyfg95RGIKUmRMnQj0hlmPqOy8tLXjy/oqoqAFarNTEEvv72G/jR8+L6Bi3h/sM38NFh1xXKFMSkcWnkxYtbXjy74cnjZyQhUCZXE7RSmQxEBoatzZuwsnrmKWiUzqxGISRJhpcXdUp459je3rDf7qh0hTmR7Ddbrq8ueXh2ymq9oDSKotDs9huUtFxdX3P/3gNW6yUPHl3Qdz2LOgt0FEaRgoPgGPqOxcmaRCbuJJWQX6g//zIUZoRAKU0IiRQibsig1RQj3nm0FrnnPOaL3iqJCx5BQkmBH102qmHIANTkmIYRQkAgkNIyDQN1VePGiTh5lM6eMXiPlYp+32GsyWiwc4Q7Ob1zkXGSiHLJ+087fvK0pzr7OqdtTYGnKBRlXaCswQiJFlkiyk8DRknKugXv8OOAiAGUzkBRzPmDlonBT9SlRctEWRYZUyBgdTZ6pQukc3ifG2GmKUcCguzBMYoYE0EJUhIokQ3XpeyltQShEkrnVtdcvlMs24YwDvPmIyiMotACayRKwu52i4lQVi0pRpRUlNbMCD5ARFhJUolJTCzPFrkU5gVECNOIkgldaKQpSTpHSnG8wflt1gUoSrQqqHREe4G77RjHid3TDxhe3ID3XFzcQ6pACoHb29ss2iE01pQIkY0fkdOXx09e4J2jG0YEkboqcGPHFKEsLRfnFVW94sXVjh/+2Yf85L2PqGyFd5HRjZlPYRTWaNDZfIIXSJGQIhKiQmlFVOpIU5ZKZxmsuUzmg2e/23J9ecXYDfg4sV6fHiXQnl4+59vf/AbeDXR+oFUt1zc7XlxtWT5+zt/5u7/BPSK73ZaHDx5kHMRa6tLS77fIssR7j7Z8sfH6nfUFGbrMJBQcUTiStLnsIyVSKaLLCHT2aLneaI3FT0MO86csRlFZi5aS6Hw2MBKBmFmgKMZhwKUJrQ3T2B253MpWCGVwCabdDimgv+3B5TwfUvbyIeT7KPnJ4z0/edZhigarApqJqqioqwJjLdoaZBQZWTcaSGijUFKQgiIWKpNknCMWBjd2uLEnWUXTlCgps4fEoa0ixpzWpAiCSGEyxzwGT2kkQQlKK5m8oxsdQSaSFmglGSePIqKTACSl0XlTmUs0SkliTDRaMHnwKWWOvdYoJZEiYYwiWoOfJvZ+JPWwbDWFkfg4EZOmMhVJxMzis3nMVVGVNMrihhE3KkbnwPWZrahyy6c1lhACxliUqtG2QksLwTNNI7e3N3gmykXB6YMHlNUCHxJPP/mUx8+u8R4Skt3uhpQiRd2gtCYGR1sXKFlmbcEU6HYTD+6doVWiXbYk3dB5wX/64z/lxz9+j653DIXDKIXUOv8ohfc5wgEyK3PWrdTzZm6UPnIR5NyPoFSmbl/f7Pjo4yfsdgNSW7qu5/HzpyghWNUtcXJURUlSkuBGbq+u2e093k88/vRT2rahaSq6/cSuywIbdVUjguPFixcUiyXRz63EMs508b92Hv0ldJBEIIkEosgZ6Vz2SSEbvJaamPzMaFOAyKw4JQla4dyU1Y1Dph8GHxm6Mdfcp4nSFsQYcNN0DImrwubpKyJRaEEM2ThUlPTTPtc9gRQiIUEQBe892fGTS0cslrSFoS0EqrYorRFSYrQmuoBUFqMtzKqnxIDzgbIskYXN0lEzuIgrGHvDbrclBgckqqpAGpk7uqQm+ERKEi0CITqMghgF3kV0SjgXsEqR7HwRKs3oHEYZRh/wMbethiiPJRk9E3akVEgCqlD0YZppsLn0lqsTPYnIFEYgYiZBdJZxiJxcrGHOSa3JbkVpi7IWjCVJhW0LioVEjSNCSGICqaCsa4ytAUMSCqWrHN5LifO5E7FdNiyKNUpaBJbdduTj9z/h6nrP5AXjlAE3IWGxXCBNgZ+FQo0UjP1EXddAroBUpWa9XqCtwtYt77zzHu99+CHdMKCNwUeHMhKtJYvVMpdmxxFjzCxLpaiqOofuKgO1GZybGYhag869BLc3O37y3odcX12DzKmANI7b7QY/TcgUKXR5vG5VEkxdj0xwelJTloax37Be1Tz59BMmN/Jbv/EbaCWxpsZPOUVVQmSybEyIzxvL+1dcX5ChZ6MjSaQwKFUSUCANQmeOsRAgYkIJQXAJQsygmRvxPtMoCRFN7vgZh3EmLkjGqUdG2G132KLAO49SGqXyexYyK7kopfEzEUYpSVmXRKHpvWDv4fGLax4/u2EfKoJtUdpibSbMWGtnw8mHRKrMdhqcoyxtLkXpvHm5KCi1pbC5fBj8gDUFhU0UpWZyA5Dr+i6DtFijMNbiJp8lrzl0mDGrouaowQ9jrh7MfehqGAghYWwiIIlJ4Hzg0J1qzJ1TGMklPeNIKeWTGxNRzcBOipRa0SwaVPQ4N7EwLSkFrCkzpbcwKFtQNAuwJSiDtA1SGpQUlCnhppEQHDEMiIxUomyFNjVp7sk/zMSzVYlSmikItpueyxdPub7ecX294cWz55mZRv7xCZIPJD8Q/ERpsmBE1ohrIEXatqFsaxyCtlkQQuC9995jv9/lOnZRQEwzdqMhRFaLBTQt49hlcHRG3suyxBTFEYXPjLkZX5J589xsPmGz2TCO47ypQl0WTOMIVrNeLanblq7b05QFzo0IKWkqRVEahIg0tUIxopXn8unHPDtfc+/+A+qmpl0t0UbnjVmKzx0C8kWsv7Jm3MvfAlAIYdGqJtqSqXfI2SMGBDFMxOBn6ansabXWhPCyjW/yGXzrusze0lKRoiCGhJ7LUePokDJ3ZTmXmXVVWRHGiNCWJA0Rxabz3O5Gnt3suOkcmz4yBIsqCiKCUuW+dmMUZVnlkF1rvPecnJzQdSPGWIqqwFiFUjlCKU2FURI/7UgqoUqDRRGdxhhF29b0/YCQ2St7F499yZnooufZFblGm1LM7CqtqWrJ5CNWqlxuNAoXp1xNUJJEZv3F4PE+kLzPaUk+gIgUKY3OnmvGPaTM7bDLtsb3nlIG2kWNlIGYPM6PFKJCaokqy6wQU7UIXaOrFmEXedMOjhRGlNDEscvAphuxsp43Xou1RabdxoAwmuQCNzd7PvzoGT95913KsqYqawSSXTfw+PETmqahrutMBkq5QqGUIsSAHwaaqoAUKEtDEokoJbZdIMuKDz7+BO89RVGSoqQsy6xlENNcTowoIanbOuNDc1uwtTafb1Pkppc0dwUKCUrlY51lZTK2M6vWlNZQWI1MmjANFEYxjiMvnj3jO7/6bYwxBJ+Yxh6YWK3XWCMQMvLWG/cY+gElPEqBix5TVZRVkzsRhfwpzf8van2hobsQClSFLVqCzl6JlGM8oQ0yGuKU2WF+zOotcRYCEAi0MbgwIYVAa4ubAl03QpSkGOewUr0UN7A2XxCq5tpLrm537KaRbox0Y+DmssdHEMriYiJiUBqszIIWOklCUFBVFEXBYlYhVUrRNA1lHanbNnt9LUlp5gCMDnxPqSaEyhd/vx9QIod/RWFJKee6o48IoRiHESFyzheTJ4lICImyKPE+EEKWjhZSEYJjcgEhNYUxyBgQSiN0gQtZQZZk6fZ7xnFAkWvCLjpSjBijiSH39mfKdQ5Jm7JkmLbURmIUKKOoaovSAiETxmqCEgSp8Wi0KkFVhGRIQSB8IjnPsMuimIOLbLqO/dOJnb9kcfqQuq0prMYISX+z5fLxU4hwu9vz5PE163VEnmZ+fdMssMUtN7db9v3I6ekpzrsZKEssmwors/yzdwOmLTClZbFe06xP2XRZjnq322UvPXvnNHlizH0VwYcsXx8TTd2QSMeoLaWUjZyciqSQ0AiiT2gi+/2eq+srdrst4zhxtmworEIRGaYBQcS7ES8M292WZ8+eUlrNyXqJVhkXGvcTO7vno/c/ZrFo+MbX36BulxSlQVtD2SxZrpYYfZAM+3LaVr8QMO4Ovx+URVULbLVkGnv84AGBkCrnbtFADIzdnsMAgbwLeqZhmhtePOMwMPQDeRpQQpAYhh6lJe0i11ljykDJT55c8fi252Y3MEaJMCW2qokElBFo5dAISI6myvpnTb1AGUvZLHj01tcoq4K6rgkxUJUVUkqWpkCo3FqrJNkg3YAY9zOYNkGaGKcsz5SwDMPAOE6UZYXSCl1Wc+ju8T7ifSA6UErnWewhzkII6VgZsMYglaEfRpLIY6NCTHg3EsKc78dEjAnvA6Qp9wXEgPeZdCNIyLn/P4TIZrfjzZMTpC+QyZGiwpiSFBNKWbTSM3lJIaQiz2VXpJSR/egdYeiJ455xvyV6T8Kw6x3/7g9+wJ/8+BOUbVmdrXjrzYe8ef8BC2PZXm4zwJoSShVstx3GlgTv2HUdQmu2XYffbOnHKbfvaklVZiWiwlqaqmC5sCzXC3TVUtUNg3N0w8But0eIPBxCCp174xFMIeKmiaZp8N4x9FBUc+//LPSR23Ql2pZMk8PNLDsR8miaJ0+e8s6P32G33QICq5cUOlNjqyoj5W3TcLXZo4Sg7ztEKrh8ccnZyYq6qFFKcXV5wzhOvPXoIWerhqJtqRYLHIK6XVK3C6TOrM5Xdf++uPUFGLq8838y5apckKpzTNehpp4QHGEmiGhZgYKyrPGuhxhxLqGkxcvI0E90Q6YeapkIwaG1PPLeo3RMytA7wwefbHnvw0ue3+7QVQGyobKamBIFII0khkCpDYvFMrdyWsv69ISyLKirGm0si2WLB5Qh53Ui9zDDQHKZFBPiXFIjIpgQumCaRowSmKKhKAa0sSiVWK+WKGmyrIEt8mAEnwcmjMPIbjfgXdanzzldQEtJSmouPSZKrYkiM+GENggZaaxlHEcSgn4M+CBQukRIyTDOLb0Ygg9oIwiup7AFeMN2iPRJcnJ+Sho28wWV0LJCREsKiuAFOAlaEUdPYCC6LNgwDF2OgkTGMzCG7dUt3//RR3zv+x/y9HKgMo7r6w4tKhrdYs/WoAS7bk8IkevbGzabDdt9x2KxoOsdIUrKKufatqjQxlJVBpEC0zShMIyjwN4/QRQ1tqqZfMAHz/XzS9zgKXQJfqRpmtwCqwQpjiAkppQ435GSwuoGITN+isyahFqB1gJtK7p+Iqqch3fjwOgcMQXqKrc5VwaWlWYMiX0/zYzPSEngpC45Wy6Oop4WUCGTYrRItCcrlouGsetQuuQ23mIW5xhbI21DlPYoL/ZlrL+yOORh57nblopUmNV9pmFPHPeIMJDGPd7PkzdSwhgLyTENE9H7zK2eyTXRe6KPTM6jpMbHw8tauklzddvz/kefcHk70Y1gC0PbVhit8TM3ubQSo3Mot1guOD05pSxLXAicnp/nPvmY8+Jp7MBYptEfa6khZRXvFBzBTxnsk5BCmIE5RfSSEDx1VXF+cUFCsFrnhogYEpML2Caju1lbLV/Q19db3JSJP5eXl/RdT4gRNzoQIXeniYCxEhElSutMsAkeP40YWyAJ1KVmGEamqcfqrEwDhhAn3DjmFMFngU2E4fKm4/43L7C1RRKZJg9SZv58SrnvPyaGfsBWGnsQYQDatsmMRD8RpoH9dssnnzzhxz95j6cvrnCxxKjcdrvb7bm6uuZ8vaBtW7QUbLZ71FyrPpRFi8ISYqCpy5nuOrDfbpiakqo01CdrnHPUZUHfDyzWSxBZfPP25oanT57y4ulVPsdNPeMtGi8Ckvq4mcUYieTPHpXA+YlCVHglkMoQtaEqCmxRMrq8wcQUOTk9zSzBYSRMjue3O5IqWK0WCJnr+m1tKIsl1lrefuvtI7K/qivqsiQJ8DPnuFkvSRK6aFmv7nH2xtepVuegcrXnri7gF72+pNlrEooF9cXb9NHhrkbE1CHJF9Q0TUzDnuB7onf5AnKe/XZLt92x32zxo5sprZbJBXxMXF5veXKZeHF9y+g8zXJJvZzbTAkIGWhLi7UtWisWy5rTk5Ocu5kcGg2TR0SPVYbbXUZqY0pUy1yGESpfHLYoGMceN42URpN8zhuHaaRYlLOYQGZMjZLM70+5nu1DJPiEkArvHMYYqqpiHEeKouBkvWK329O2LUVh8N7x+PFTlPJ4ByEGrJH4ELFFJo70fqIwmvp0wd0pL20pcU7nLr6kmKbAMMCYEvu9Y9dtcY1DhAoVHaerim99/RTpB8pakiS4GDBlQVIaWxZoW2OKGqkkQqtMRoqZeOSco9/vePb8Bf2YeHG1YdsNubV1HrdVXRVcrBfEGCnLlm63RSnFvXv3jpJa1trMpCRhtWS33aFEQs2U0BgVfd9z//yMtm2pqjorsybJ5eUNV1e37HcdgohWIm9mCPTcyqutQspDc04GRY2Sed5fyqxEN0SUyuVErTV1a3NerSWb26v5M1+wu73Fp8RujAzPb/BJYGVkUVeUhaatFlnBRgv6qaOua8YQGLY7lidrFssFPkV03XJy8RBbLyjaNeXyDFXUR7D0y1xfmKH/1DQQBLJcYE8fEkNPCCOSHSpNWRVFa0RS+CgZ9x39vmPYd7h+gBBnppvg8vqWYYps+pHnlxsCLUVRUjeKxbLJ78dEYQ2L5ZKyKCirCmstLjimqcMagTVZ9bW0WURQJI+WiWnKM8SS91m5JXgKa3JOPg5UhUHESAieYeqpSktZFMQQ8LPmndYKF8jyVikhFHjn8M7T2JL9fk9RFHRddxQZKErDMOyJcZo9REIIRQyRfujZ7/ZUtWFzu0WQOFk1d3qgE6v60MOskbImBE9MQKkYbYFzmnVT8vzykpv9Nktra8NNH7kdA6dNQXQOU1i0UiBlvj3nrkVRgLL4COM04tyYWYZumvvPI7u94/q2x0dBlAmXHDrBbrfj5vqa7W7Lw/MTUko8f/589va7I3i2WmY9fiWgbUraRaaJDkNPWRjO1kvatpmbiizeJ7bbPTfXGz784JMMwClFUxSZAx9mjoYSOY2SCj8rymilETH/LUUY+z22LAg+p1ZplyPSsm6oCkvbtvT7PQ8fPuT502dcjS8Y+4Gd25H8iJZQFRl8rRdLpBCMEyzaltvNFVpmxmcXIo+qmuXJipOL+1TLc5p2ha1aiqKYqyJfvpzUl+PRSQg8CIluTinCQPADxIhOEe9yCSHOqCgJtJRYqfAic9jDGJkc9L1jOwZ6LyiaFVoltFK0TZPJBQmksaxPl5yfn1MUmXKaFVRL+mGg73u2t7lEVbcryjLLP0Xv0BIKqwnkltGqMCwXDd2+gxQoTO5IczEPfSiswRjLdnOLkBI/DUyTwEWBkgakwnuPLSvcviOlnNM654gxsdlssNbSNA1RwjAOFGVBWVqEyJvGw0cXDMPAbrvjtq1I89CJg+CB9wGBPIJ3WZlEE+LEMHToShALRYqaqr6P2W7YXI9c3XZc3vac7ktWTUtdlqBk/u4qpwhS5gpH33UkFUhoXAwoJSiKgikF+hhBSCIqS2ALSRJZIDWRaJqGBw8fIoU8RjHGGLouH49hGDJvIvm8cZYVi3aRteSCp64r6qqksjlnTSR2u46467jZ7ph8zLqCKdK2NctFm9WAQxbErEtLVZVM04ScUtbjkxIjFP04ZAajFEgsYRoRKs+f8z6rw65OTjlZr7McmpDcv3cvR5nTiAyZaTk4iErRlg3jKCjLgs1mZLvNQGy7LNG2oFosEEZnUFbkkp1zE5EdWgusVpAsiC/JFOf1Jb56AhRS1NjqHr7Z4NyQS0DTjiTn2nsEiUeJfACVVMik6ENkNzr6aURrw1lbk4TINUwOckSORdtSLxqkUUxDT4oea3K76th1LJdLCmPY7vZziARFoem6gSSgbluqZkEgey5bZXBr8hPK6Kwcqg31csU0DgSpmUKY5YcMSTgimaUmUlaxlSKR4sTJumW33VMWNZvNnr4bssZ3cljtEVJSlw0kkWviyWF0AwnKokQrzbJp8G5it9sd9cGncSK43HShVXlsVw3R4GrDNDmCz6h86QSBhhrF0I28+6P3MSJybhv0EgojMEaSRFYz9a5D61wBUOisDaBtziNTJNIRUwApeOfTG277CFiI84hkozGl5vnlc4xMFFpi1UuZsLZtkTJvAMOYGXyIiZhg++wFdVWxWFmWqyXdfkdT1myHnqfPL1HKYKzi9vY6NxcpQbu6l7UOYiSQRSK0LhAi0Q9dplsXmVU3TY7JTzRNhZAZPQ/TmIHL4Ai9Q7pIgaJoGpaLFms0Fw/u8fTx4xn3YJbPklhrEGQyVAqesizndMwiJdRNnancPo/PMkoR3MSLzS3GltRVSZat+2mt+C96fWnz0RMCkWSuoMkK26xw3Q3R7MFsMzFgZtP56OnH/hh6KWNQXiADNMbMMsllJrOEXOY6hJdlmVsNbVnMZAhNCLmJJTiHGyfadjHn+QJblFnKxwaqpmV5cpZrqGTWWFGW9ONAJCvYKmNmtRiBI4/jDZMjxERVVbkdtqyYXM79pBDYMqPjUiaKogQkJ+tTUsylrsJaun1HVdeURUWY1WwRCTc59nGPnzvu6gO7qimPIptGS1w/HQ1c6VxrlkJhdU1h/FGRR8rE2htM8AwyMvTw+MNLnpydslreI0oQMuZWz1lmOqVADI6YJErPbK00N+QYm+fT9Y4fffAElxRaWZpFy8miobTkKkMKVFWNEIquH46evO/7ozhkCIH9MIBUXN1s0FpxetZkfMQ5dv3AZt+xub0loiD2rNctgkRTGc7P1pSmRCuJTzM3QuW+8n23R0qRwUCjczRBYrleIqXM4pguoq0BmCMuz+ATmwjV5GjP1pjlgjfeeMRH7/yEm+sbYhKEyVM3NXVhsthoGKnqmvUql/K2mww8FtZkKvWsl6DniE3WNUHIHJnJl3JWX+b6kjz6TIk93JQS3Z5i+i3BTWg/4seBOEaUSchQI4uETg6Eo1Ia2yjWcxh8MOwsMJkvkMxu0sTo2dxuaELLYrEgJYf3OZxdrlcM44RPEVtVqAjaGEbnUcbSFhWL1QlXNzcZHIKXYg4iK7KGuSIQQua4xxgwJnMBAMy8q+c25pdil4ec3OiCfthRFiXLVZtBJy3mGW8d1i4Y+w4fHE2TkeK+73P4b3MDRZ5Skxl7QJ4jXhRHTb3Dmma9PKVy7dtaS1EGtB7nKCOgpGAaPT/+yXtUjeKbv/YGVktGH5Eqt9oKIXEh5r52Y0HbPOJI5A62JBve//QdPn1+SUiZLhy9o9vdsgsDq+WCk2WLsYbFYoFaLHDTyMcff3xMNY4NTl7R9SNCCB4+fMjtdofUin03sO/2bLdb+r4nRUldlRSFoqkKTlYt1pojgeMAThqjSSkeAVCl1HHUspkVf/b7/Yz6FyQhGMdMwxZC0/UT4zRSB4csFaYqs8pR9GgpMCoTc9brJSfrdR4MMr/u1dXVkeVntKZpGqpZgCJfxx5dzJ9Ta7q+Z+Ec9ssxwlfWlxa6i0NlXZJJGKKhXL+BmzwmOeI0IKaIcOCjw0QJYkDZQJkS0YP36ag0kk9kQso0c8UDEKjqkjGMJDyILJFkjGQYR0TQCKNR1qDFrCsnJcPo0NZm2qTMU1MgXxyHXPjA1suhoD5uBNZaSFOWpU6Rqqrw3hFCxBblcQqIc46UIkrLPGJKgohQlJah7ymshQMJSElmG85zyqfpKGXtpwFr5PEzKZUBuxjjTB8OR5DuILx4t4RFipSFQi4bCq24vd2i5lr940+egnS8/a1HLNdrEBJpFAiFERZlSoS2mKLEGM24uWXsHbtR8Z/+7BP6KZHE3FLrRpQxR832aRx59uwZhZJokb9X27YIIbi9vc3fT1v6cWK73WILi9BXpBRwMR/zm5sbnj9/nlF0kWmpMQamKRtV21Ss2tWRQn1gSo5Tl0t3ITAMw5HyejgmhyYWrTU+RpwDYxXOhZnPnpj6HU8+mVBlgesHosucCW8kpTUM/Z7L4Dg9PSX4XJJbLpfHDeWoYDMru/q5YlGJedaBzpvDMIw0qy/LCl+uL8XQM+HtjmC9EECBKk+wi47oO1K1RYwTwkNQCaEt2g4kP2bhiSkiB09KIYeSMSKkoKwsVVXNul4e5x2LZT0zr8RxsGBRGvbjQFG1mLLAC4HVFqktw9ShTEkSCh8S1pa4aYsx5pgrtW1Lt9sBHA0nfxVB3w/zABUJs9C/mcdMDcPw8uBqg5rVaL2fZtXa/FgpBU1T0Q/9ESkWQhyjlXHMAo6FteQ5jIK6rmd9fIFKr8pjH2SDD78PP6SEEoGqVBhVYaSg64YMKo0DN08eo8WI+frXaVdrolZobXML6ny8gpD0w0ByEyTBH//gA378wQui0OjCAhIlAyeLBlUYyqrO9Wwfjp2KSikuLi549uwZQgjKssQLxe5mQ+880hZ51Hbfz51vjnGc2HYDZ2fnrJqGaeh5/vwFIk2crlsKq0gpbyJZwCSfg37YsVotEUKw3W5ZLHKpz8xpYNYlyBUTYgARZwEOyzA4gnfsNzu6q4kxZsKVO1C2/UQMmdpdNlVmeY6ZmZgbX/RR/eggWxXviJv2/cBiuaSoSrrBfRm09s9dX2LoDnk+2kFESSCEpmzPiNMtjBvEOCBCYhKBNCunTEMgjLntFBEQMmGLPNM6CwHmLp8s8mcpCst2v8vgypybx5SymoiI+Pk+awuUKQhJIpRGWwtznVUqmXvcJzeHf9mz5zlqLyWoi6Jgu90gRcqobwjZyG2WMTrwlKdpmmvFmmkaqOtcYjOmJgQ3G38ipUBZ5HzdaEUMgWJWoonBI0WJlBmABIGbcl7uXdZkP2AHiRz5hBgw2oDgGKZ6P6Fn8V0lYbVsaJsa5QMpDBQVxHFgd32dG1PMKbrUGFvm6TtC5ggiRFJI/OTdD/md3/uP9EHMHrxACklrJWVR5G4saymNZhx6hr7Dtnk2+TiOuTlE5PTg8vImbyApz5+/3WyJMbDrFNWMyTx8+AhrLdvNBpk8q9UpSmRS0zhMdF2XI5voGaeBorCcn59njCYEVqs1dV1RltWxpXeaqbHTNOU07HjO00xAGpiGgXEa6dyEKHMoXlUVpshRQzX3R6S5Bn/AjKzNOv6rkxPKpuH65oZ2uWC33eZhoSnmNmelsVZQ1fWX0sTy2fXlYvp8lrcrkKbGLC5wU4fyAaLEKEHsFT5EIpqERIiANKCSnIEgiSrN7MUSzuWuL4CT9ZKb2zw+SduCgKAsKuhv50GOWarYFFU25CIj/kZJBAE1l4qcz6Fb7sIDYwXBja+M1p2mkfXSZikpCS5GjC6ZuiEDLlozTRPjOFLXFRCYxg6tc/ceySOTzA0Uh90fcreVzSXHSIQwC2h6T5Sw33eYGaeoihJpNHVhSKQsqxXC3BGXZbtSSujCUrgS3JQpuPOG1fc9qgRr6txY0VZMwrIdArVTaK8z5zs6TKEoVBa0eHbj+Pd/9A6f3NxCoWhSLjeWZYk1hvXFBSJ5jAQjBM2yQWpB3daEyfHs+XNG5xkDbHYbbnc7xmlkuVwSYmC1WrFctCSfj59MWaFo6jtSdFzcO6eqStzYEzxMU0QbRV0XLJYVMXms1dTVElA45zDaHFOsGHN+dCj3CZGBxqIsj9iINuD9gIiRtig5WZ7QjQ5VNmhGzuZI4erqCmszQHqQvVoul1lCG0hK8cnTJwgSZVVQFRZCmEd+5xFRbdNQ1tWXJSrzyvrSUPfDjbtfIofxkqJekcYzhqGDacIyEvxIdBpswehzv7OSEmElOdUUM4iTw7vDyer7nr7rWK9WXN9u8D7ktj+paBfLOTwPIDQhkcf5OnesSWshjs01BzLLcdJmjEdp6UNYWBTl3M+chRqyJ83llqxmI5gmj55nrBut6fuOqqqYJk+MQJgHSMzhtZoji6IoGIaBNDdNhOCpCss4jJTz981e2nGoxhhjMicg5XKaUpqqaWbWXqb0VnrJMPRsdzvGfsBWJaURmYlmDVIbirJkuVqRVBYEYQ47EYK+3zL0Ez/48bt8/4cfABVNVWLIqrir5YK2bairEqLPclcC6rpivVqy3+/x43gEVoUQLBYrqqY5et5DOO29J4wTpycn9H3uTuv7keUil8isNawWLSlMLNsFSmq0slkOKzGnC2FOpSAmN0+tjceU6NAvn1LC2ALnHdOUZ9GdnKwpi5L9bZenxxYVIe25uLhAiswlePfdd0kpUZYlCbBFRVEW9H2PkIKqqri9uSKkyHKx4OZ2Q4iJcrFCSI2Lkbpdsjg5J2sliy/d2L9kj/4zligw1Qmu3BDGDul0Rq99AX4kao3GzsqquetLinmWmMzh0SGHzR50pKwqyqpimDxKZSJJvciSRUmAtQWJTC89KMUeShoHDvYhXI9zqydzvf5gYHDotJvQKoNpKYKbAikJQsibh7XFjO52lIXNCrgeQBKjQAHTNL6Skx+wgRDyPPjb29tM/plzSSkl+33u1KrqGhC5Zm1yeSiPBZIzPZYZIHNM08h+e5tJSdbQzuUkwkRMnuAdfkyo0rIferQqKKqX/eBuckxu4NPnV/zB939M7yRWV5iipDA5KjlZteQGGVDa4KYRIQ6DD0aausYLiZ37CCbnGaeRNIuJ9n2PtbnzrygsVgqur6+PCPbbb79N8CNhGmZDKqmKBUoIdrs9m82W84tTpMzodid7hOyzUQtJ0zQzdpGOaZVzLlNVx4HNdnsE0qSUKLlFJYGQmuvNlqI0FFJT2JJnT5/l0FtKttstRVmyWC7Y7zdUVZXFLIzl2bNnrE9OIEakUizWJ5ye38OFhDZ5sqw0s6z3V7C+QkNPCJl7qVPSqHKNXe6Zhhv0aIiTJkhxzJFdmICMMkuhcS4ew/VMesmU1rZtub7JoZ4tK6a5FbRuW0IK6KLER0UU2evJxDFsO3jUw3tmuV05I9g6K7HeUbSFfGEmDzkfl1nob9aCIwmCz683zt1kQ5yoqpJxyJ5lv+sprWa/3x9D6WMjzWz0wBEYDLOM1W63o67rOdwPCCWOyPwhR4xCMs1DBxABoSW2rpCFxbmJEGalHyGQOksaa2OoFi26sAitZm83M/EICGnY7x2/8+//iB+9/4ykawql0TJQVyUnp6ecnpyw2WwIYWK36YDE+clJxjHmykKYPD747KGdZxgdUklCDMfps1prpnGkWWTFlgPI2Pc9Z6crhj2QchqTgqG0BV03MA49bdvSthXOBYb+NmseeI82hs2mp2lqpOR4fJumwTnHvusyFfXO9J8YA1JBIrBctfgkQEimIUddJycnx9dxbmJyA+uTJWenpwzjyO3t7TzCeUGzOsPWLRcP3yIIRVVU6KJAFyUIRc6Rvnzr+0o9eh7ZkBs9hTDoeokoynlEjiZoTbKWkBzJa0TK1Evvci5GyjnyocYMzLlwTZilqQ517Kqu2U0jPgaUKRgmj7GGkF4Opr875O5g0AewJoRA8C8NDzheBEZqUsrqsCnJmW+eGJ1DiKzu0vUjpycnDP2eulY4NxxDxml0KKWOZcNDvdc5d/TuRZGFF4uyoN/vqevcZDKOI8Ya6qqax/hkLxZiRFmLKQvMXNMvqgo3Tfi+R+lcT5YqT4bxU0dRZOZbJOFDwBqbNy3mDchaJhf5wQ/e5Uc/foIwSwpbU9nEo/trLu49pCor3nvvPZ4/f567yBZLNtsNIQROT05YL1t22y3dmDe2pmkokTgf2O63yCjn85dLX9M00Q89Uiq22y1SKp4/f57bSQVshg6rFNEXxDISA4yjZ7PZUhSW6+sN3X5kmnIZbeivSSly7/45VZ2vC6U0T548yYSktp35EXlEVd/3DH2PkZKirFAip2KmrHBuYL1eM45jlhf3nslNaCspywJmDYDFouViveRktaJZrajWZ9iiImlDu1pTlDXM5Ku8/saDcT+95rktRAHKNpj6jLD5hKgPM7BSZjpZwxQ8IQYCge3NDTEk2qpl7Icc4rYN+76nLCuSTAQUy5OLXKYZA2XVst33WY01ZIRakplbar6gQ8xKrFJmrvch3xVSIpREq1weCSkRZvqjkpKQBNMUZrFG5kmcedTU6N08M95Ar7KUFJowcwNskfNgIcBoRTW3aR7q7VpKjNVZbksKbJXluCY/UTU5PJzG4cgkhAwC6rJGF+Vxs0gxIhAYUxCkR+mcbhRliV61DGMWU6zqOg8fNAW6WmfNcRK9C/zJj9/nd/7ghwTVcHK24q1v/gp/7+//HdbLms3lc957971cm9aacRhZrjSr5SnrkzWmsIxuRGlJ2dTI3ZYQPQmRe7PHjmmKjMMACExR4qaJfTccByFaK/EBPv70RVbWVWLWkpN0/R4fHF0/4C5viNry+MUtN7c9WhnqCrabbSavDJ4xCPpp4MnTWzbbLY8ePkRqR989z7p20wTkiorSlmH0IHOV4/Zmgzb5PO1222OKdX9xjinyJu3dxKJpchlVaVRZUtQVMUUgsF6d0tT1S6RdZIv4KtZXbOivfikhJEXR0AlmNpPGK8HYOxACXRQgcjNI09b0+45pGHI+HQKBRNXUFEXN5CMxZgEBTTa+Qhq0CkipMSbmGeiLJV3XH6OIaZqYnCOSDdyYPDI4c7w1KWQRRT9rummtid4xy5LhQ8RYRQg+j/chYwLr0xOmY8NJBuuGIWvQJQIHXbSizBpr4zhkaWYpsgHOc+WVyqj1drulqAqKqmAYc62+KIvjdJoQAh6IIWQQk9yamUIiipxeHCKAECKmWbBYnBBiQJosjiiNRRUtpMg0Of717/4B/8N//FMmZ2iWa/7ef/YP+V/8L/9XLNcnfPjhhwzb7UzVzVNFpZRUZe4czCqrBhEdLnq2+x1t29I0G6RSdF1HaSTDPo+ISkLhJo+fJbXKRZ3JLhpAcn2zRSrFsq4Z+p4QoG0qhinThW0S2KplCrAbJurGUmsNWtOsFgitGKbAi6sXXF9fs1qtuN2NbHd7dttbrLWcnpzOeE1ku9vkDj4hcJPDakNRFoSYKIqMcxzSx74bqOt61ulTWFNS1jX1cskUI1aAEInoszpwDAGlP6PM9CWvr9yjHwbISRKECdftiMFnfvQ8VlgUBaN3WXLSZPXY0edRQf02q9KYqkQKQV03+JBz2snlxpiyLNnte8oDip4iVVnRDWNWUFWaQB47HIXAz6yzQ85src1y03e85YF+mkhHthy8bEhIMR3z6kOIenN1RVXlUlxMAR8ySKW1hmSOYOJhmN8xL7/DxjNG0XX7I+trGOZZcjZ7YkE2XD3LaR9EOo5sLO84UNW9d2hjqOuGoDSybKnLAiCLYxqLD5Kr6y3/+t/8Pv/hD3/C8uwbOJH4x//lP+a//af/O6TQfPr4MY8ff8zj9949hrAHvKPvOuqyYOw7oi8wCgojsVrlkdUxME4DRgpUWRCaHIXsuoHRhTyuahpnUDN/5223xQdHnEZOV4usJqwE6/WSXSeO9fCiKFiv10wB6rpBicRy1VJXxRFl996zWq0QQvDixQu2mz0pwenpGfv+BmsNVVVQlgIOirbk4Za+66iqeq6Hz9eBMTSLBdoYCmvR8zlcnZwglSaMjnEY2Ow63rAltuvQtqTVBiVfpoVf9voFePRcShDJQxgRvs/qpWQSjDSaOIkZ9Y0E52eN2TzbvG1bJpd50iklur7L2meI2UgihS3yhA6R2weVKRgnP+uNK7TOJ15oCyER4nCkSh5Kawejv4sHKKWY5vLMAZw7AGl5TFSmWt411hD9sa6diTKH+V7pSMs8vOcBEDpctBnt98dQ3DmXqZvGgJZMc6+1Ley8oUlKaY6bkHNu7tLKWIOQ8wRRKanqJk8SlbmaoU3WWvvok+f8X/5v/09+/P5z3nz7OzSL+3zrN77F/+af/ne0qyXXV1eMU892c82zZ8/YbDacnp6y2+1IKbHb3lJoyVtv3keRIHiaqqB8eD8LURTmKOi433Xo1QJb5fLU1dXtcShmjPF4LCGzIIvCIETg9GyF1YrlakHdVkckXSnFarXClDkVGfY7vAOlBctVS9/lnoFDie3m5pYkLftuZHxxQ9u0FFExxQlb1aD0MR1LKdE2bZYoH4bj5mJskQHg4EBoyqqgKPO8NWMTUgq2u452dXIcuPHV+fGX6ys09FnSmYO5B9LUk1w29MNjpJQYbfAxYrQmyOztQswHe+h7lM6he6ny3KwQ8khdpQvEzGtOuw4gD6bXGh8TbsxacLrI4R/KIHXKyLwPVJU5dlcJkWV+BRw9VjYWgUzyiNYfvH2uDuTvkWvm+eLzo0drmcGwMfP2pRBZMHGmzB50xQ+vlWe+c9xsDmDRYSNIpFzqnnGFKDL2oWbJ4MNmcpji0vsRqyTWaJLILbXBZUIKKiGFJQyeq+sd3/veD/izn3wC5Sn1ySlvvP2A/+0//e84uXefFFxWig0TbVNSlgX7XS5Ntm2boyGleXBxzrKpWbUlWqVZFTefl3vnZ7nDa7dje7Nls92x3fdopem7/lhPd84dUytrLe2iwRpNu6hZLBqaqqCuS1brE7quOzLSzs/PCQI2m1tkcpA0y0WDmxxSilc46AiB7D0UI+M0ctNtodty7+KUcTJ5zNRMlDpwHMYhC5UsFot8nn2gmwJ1XeW58P2Ai7kXQ7s89FErRVPXx3Mjv0RtuJ+1vtLy2isbWSKzvryfNd6z6lwIEWU0zOGblCIPfRAvGUUhRVzwpBk4yeKdeXSSi3lYgbFZu6usLeM0kVJuYd13PeeLE0KIOB9m9U0F+KNhSylyXu491WF22myYzI0umYKbD19MMRtR8HM4npl1kYw7aJVH7KQ4t396j7Q2y0zZLF8kRY5YDjVeaw0heIzJyqYHRLisSmxZEiSoO11yo3OI5CBJqpnyqfTc0FOXCJE1yXLFQTBNjlJJNBGLZ7/tuH5xzbvvfkK7OkfWJzx48yH/k//6v+D8/gVC5gm1XdchUqTbbWnqhitxxTAMrJYrur5jWZacLFvOT9aI5AlTTzdOJJUjjbK0BC9ZtA3y4UOcT1zd3PLxp0+43W7Z7TvSHL0JIem6PWVZcnaypl1UnK7XeTzxcsGD+/cpq3aWnkpHZ9CPud5+slwQ44RMiS51GQPwHjsf46auCdqxGzt23QYpFU3bkpTgerMjhmzAbdtmooubKEs7tzpbtrsd1zcbxgDrk8Dp6Wnm+VtDimEechEQymQKbLM8VnSIiTR3an8V6ysO3eM8JVIAGqFbkmqZx3GTJKS5nCakwI/jcR61kdl4J5n145gio/PYWuPDlGWOlUCZApccqlCZsSYlApkVTpXOg/Fiompabm5uMFKhlMH1I2HymVcfc/NClkyem3PmPN7oPNk0xjT3x09oPY/REQBZo93YOUUJBcbIPCJX5iktWinCMGC0QoeA3+8pqhJTGJwbUEoDOX83Orfq3m42VG2NaarMF3eJCOy3u1xuK8o8ZVWrzOGXCW3ziGkTmTe/EmVLhFSYJKitoZGem6eP6bYdN1dbXmw7pC75zq9/m9/6u3+HB2//CgiDHydCP9LfbtldXuP3fZ4xdpsVZR89egQx8vVHD/nagwc8efKE58+egstDMEcN9+/dY71sqUpDoXK9rKwKHi5ritUCJ8H/4Ec8f7El9j1100AMLBYN61XFycmSi4tzVsslZVlxenGRpXvJnIhElvCy08TJ+oyx3+OnHj+OjIPDhYG6qTNDcB7RZJXk4vSEqiwZRkdIgheXtwTX01QVZdUSHOxcx3LZILVlt+/Z7rssR11WnFYLFqsVi/UKW5V5CImPXN/kqNIYQwyJ2+srZNXOIFyaK1B/C1F3MX81AKRAaInUYi6riZncn+WADuDONE2Eacq00fn5ZkaIu2GkdJmI4rzDB4+yReZ/K5VFAMkgWRISF/Lt/X7Pcpk5y8OQ+4lDB4hMaS1LSwj+2EN8kEGKMeZwT0qkPOTAGZDzziHnqCMPewhEL2AGjpCSEBzGKPw0IkTCaIn3c6+0zqONhFC5z5pDr0PKAFddI++AgnpuSV2tVseQ3gcHISP8IkXGaaJuGpRQs7iGRAiJVJrGWFQKPHvymM3zZxhT8unjx9iyRNqGt99+i29961uUZe4P6Luem+trvHO4KQ/NdM6x32ePe3FxwYMHDzhbLvneH/4Jf/AHf0A3DDif6cZGS9569JCvvfUG9y9OefTwAbo01K2gqBsuzs4wv1nQNgt++GfvsLm9YdEULIsFy7ZluWq4uH8+N6nUtG1LWViiKo5pyiHdSlVNcA6IKJlHSC2WK3xSPH78mP1+fwz1lYRFUbCo1uz6gRdXN1RWMoks7bXb7fFDnv12fX1NItI0TR6UWBcslyskCoRgGsc8zz5FUsgdkIc0oWkayrLMVRKZG4XkV2h9X3GOfjd2D6Q0ktJ4FA0QZOAjGxRHEkUOO6Hv+jzzOkFZtxRzGG2spiwK9sNE3SqGfqCqm1z+cnn8TQ6pLcHHV3Lj/X6PmbW85cyFPgze894zjuOR8ggcQaIsVCCQs6Ejcsgu5Rz6H0A8mXkB29sNWuf6u5RgVBbNOLStkgt8CJnQRh7f10+esqrY7nZ5DHKRqbxjP1DO+nh932dAT0lkymONrM5A1jAMiCQwtsDOWnlCgAiO6xeP+fT9d2nLgqgLfMhz0dcXF9y/f5+zszPKWTiBRCa+zEIQ2+0WyAyzYRj4+OOPefDgAf/qd/4d++0OH+Dk9BxZFVzeXOO3ez5+/Jzdrue99wx//+/+Hb729TeoyphFG7XkdH1C892Gt994yOXzZ1w9f4obeqqyoGpqlk1DYVRWek0BkWKODWdANKV0TO9GCaWsSYWiqgpubm65vt1SzIIdBydSWQGBrLB7suJktWTb9Vzf7gg+YwWVLfLUlxixVh83iRAC280GITRFWeKiJ0lJWVeYuRuy67ojYFvU7czf32PKKhtfmr36l+zYf0F19ATJE0NPwiHErMwyDzn0UwbA9MwW0wjM/LcphNzWWWTiSIjgnKcoC5QPGUyz1ez5snpITIqiWrHZ9egyDwA4lG/yzK9MgSW9FJ8oy5e0VMg1U8i1YqstYZ6YmhH6kC84nY03xPzabhoxRtLv91ibxzFtxz0x+fn7yiOttet7hMpdVofgRimBm2vaxprjRNEYczltdycENcZk0otWeXzT/FnlrH564J7bMufr3faKZ598gGZulZ0mbFFyelpyce8+9+/fP9JrAZTW1HXN048/zDPNfaBpGrquO/K+y7JEK8V/9Q/+If5mx9feeBO7bPlX3/td/ujPfkgInn4K3Fxv8P4P0VpgdJZltqXEFAZZFJjzc07WK/YPLri9viIFj5KZ2y9iIEwDk0h5vLOpXwEfs0ZApBDlHD0J+uAQWnJycpoHcc6Ap3OOYb/F+YkkFUmqXI6UCj232Rqp8nUW8sYCzMSaw9zAQIqRyTkWqyVCyUwfDmnma6jjplA0LfXBAmKctec4MjW/zPULMPTMjAthoutu8b6fv3Q8nixjNH6Yw3Rjctg+ixUI73Ghp+97Wlsg5vys6zrqqmE/jAgVUNogpcYKcN5jUmSxaLndD5kTP03HvuLoPUPMUku5/DIcOehZhHI61rvLIo8xSjN77jAzLZ/Q+aAevLVSuHFAyERpLbvtLSFMKAmIOPfV5750Y2XmeIqI81mw8OrqBUZVpCQpy9wK6Q41a5fTijydJIf6KQamMbf3CpX75UNMKATSGARZwml0PbfPnxLGjkLkGfIhZBpsCJ/TygmUZZGHVLiBfnvNfrvBjVlh5aOPPqLrOtq2ZVUVsLml3vTE6SNejAPi8XNurresTtZYIylsyW4/8P3v/ymSrLq6OjljdXJG1bYkY9ElCGMxVUPyjjhuEfPEmxA8cvbo+RjK42adexgCmZ6eiFEzuMylz6OUqqNHvr6+ZoqCF7f7zHBMu5k9mI3v5OSU5H1uMDImU7MJx/biXBkwTGPeuJ33cw2+xCiDtcWxXJpSorDFLG3lmJzDhIDU+m9wm+rPWPOkclLy4AfElH+kUgShCCH3YYdxAD9iVKQwApdSLp+prH7SasWu6xmHDmMqjDIkQZ6BrTXBOcYEWhcgFVIobq9eULdLjBQQPVZZ/JioKo1UCWUUfdfnDrDo8VPudjook4TDMEgpCDPDKc3z0hI6h/1+oK5KUgxHhN3HEWsVbupIfkTFcGTAaa1nVZMJITVGaBSCJAUhxkzOIaKMpahLhnGciUUzGGgsWtsjpGNs5lubskJqS0RhihKl8phf53qkzFJVw+4WYqRoFxhbkro9hdasTy9oFpmPXRQlJBApkZwjOpf5/9rkKaRzX8CBb3BycsJ333yDT//T9ykLqKNgGh1mGFioSGE0N/2I1QqR4KMPnnLenlGmkr0DSUCXAlSDVhqMIYYCYQyi0PipI/Udzk24YcQZgSxrlFUkqUEbopDo6FAhT0hxSKp6gZAmTwUKMXe9bXekmLi82nC7GTPeonSWam5rqqIgxcR2dOiiYHABqTS6bIhC0fU9zk3YokCqgqapiSnS7/cIIBYFJJBaI41BaUPRtpl+rPOY5JhSnvyqvnxQ7iv26NnQSYHkJlQMSGBKAiUVcdYaw3skua9YKwgyl90EuelYSKjKIjcfaIsUBuaaso/MdUqFmxzGSorCMgw7+m5H0TRM00BTN4y9Z5IOpQLKqCxyGD2kjAsoLYm8FJM4hLEhuNnzqTwqWOfdXmo1D4EIiBSyJLFR2bOGPNZJxpAH2ZQFWhnc5CAJpFAQApP32Ko4suVsmSm5cTYmyNyAA6kGOJb+YnKzcEYO05UxWXFGaupG57bfcaDfXOHHgaZtKesWHxJSCE5WS/Tia5zee0RVN0iVm15IHF/XeZ+ptDPt9lDnP+AZf/aDP2WZYPKeq2fPWJyuWdQN3334kOdjYOsim92eUic0infe/wQZ4N69NaaU9E1BdaIREuQ83MGHmJV8yhpSwA07xn6X5byqJUpLZFETiFmfMCVS8HnEFIKiyAMgptIxDSP7zSbjDLstJIGWmqTmmXIxIEPI6kAzIDu4QEiJ5XLB6CPO91R2Hk2tMuV18u7ojIL17J2jbrLEWT9NtEWFUPrYEq21Rh1Sja9g/WL60SFfKN7D3Oed0svw3XufCQ5koCXGXIMWIs1jnQJSQFWYPFpnzGCTm0a0LfEpEZzHmALnPEhHWea5Wlkh1uKmAak0zo1H1RoEKKFAZU2wAx32sKZpyiUzkfOwuq6PJ0oiqKsqCyyME1LkudxumvKgPaUJQmCrkqIqKCvLNOVacVmVHEYHOe9II7lUpvKkETWrpQCzUkoCoY5Mq9wFR45syMMDlc2abwCC3Djihg4/jYz9HqkltiqRViOiQI2eellw+vWvU7YrqrbJ2lP57ICEsqkyh396wHa3ZXt9Tdd1nJycMI4jP/zhD/nNb36TYBRn9x/w4U8+5J2PP2bnB0xZ8t033kJsP+TTfoJKMcrE0+0t/gPHbXdKBLwXPLAtImStOWvm0djJI4kkoSiqGqsze7Hf3RKCp17l8dDSMHcVvtTOA454gywFyXv63T4LewZFP04Mo2O/z5u5NYqyyMe/aVtCbpyfU7qAVQKKTGG9qylQliWLxSITlYzO5zUJ9sN0BE3LfqCsW5T6atpTD+sXYugHAEOq3CeejTvM/ebZ4KSSRJeJKlVVoVVuIyR5rJKM3hOCRxuBkZKxH4hJsNt2VO0y85QLmeWIvJvbSnPziK0UcfbaIbhcC5fZcysiwTMbU3oFKDlokQvBMc/z3qN1bv2MkydMDmJuVxz6IY9+UrlTTVmDKjRVZRmHnr7PAhaZGJJVaPq+p5ISUxZzn3tCWXXk1B/6ts1Mnz2osggh0EZgixwBeO8RSeKHkf1uz/b2hkVTUag8UMGhsFWJtSXT5GlXS+T/n73/erYsu/M7sc+y2x53fZoyKKAANNBsM2RrSIlizINe9KB3vetdf9Y8TEgRE0FRMZI4JJvkNM20IdFouAJQVVlVaa87bttl9LD2OZlAA00SplBozorIzJs3zT337L32Wuv3+34/X284feftKXY6f4NlJvAx9e2zMqeazyirivliwTiO9H3P2dlZsvRmGc/uXrE8remF4H7f0Loe0/T83ld/h6Gq8Js1vS545Tu66Hh6v6YdRrouIFWOMIaT81PK2QxTZMkFGBUER1ZUjAR6n+KhYrOBSQoshEB5lww8k5hIvLHzUDHgxEjMC+bzBcEFlGkZ/IjzPX3Xk+XpKKeVTm5Godi1fVLFDT3OCUxdErzHZHniGKpw7BC1bZsKo1NrNwqFMVn6v2Kk7VqytqWsZ2j7+TnYfjMr+oRRErxOqBCTg+1wUQ5yWCZXlM2SLHXoh7Rt9o6xS/1170hU1xBRSFw/YLLJf60NMUySUSHwfiAGR1QOazL6YSSElMqilCKMqXjixuFoYDn41KWUOO+R8TVqGSDGZNgYhxYBycPctqgp3M/7EWU1IrMUZU673zCMPYd22r7ZkmfF0Y9ubTp350VOiOn7Vkqx3+8JIRzTTg4e6kMRahyG1NdXhhAFzqU0FNd31GXBvC4Zu5bokzcfJYlSMIYEmJjNlyxOlkhbokzSeSdQSFIjuhCQWlPNZ2ll3+6QQnB/f09d1+lBnFt6Jfl3//E/slmv2fU9ffRUtSW3iqsyo6lqXiJ41Y6MOITRvNw29MMrrh6+xa79IO30hKAyClsWqQAqBMoERPT4MSWc4nv2m47Ru4nkoqcWojpKlA+BDUeEFMl3cMiUKwrLycmS3UT9nc1qirLAjenIleAXHc4PmLI4avAPwA+HOpJyDlX20qbiZ9t1LFZV0mpMfvu+7+mHgaycKGZ/28ATxzHpfcPB4EHqn2tt8KNACJU+JuJdmMQoqUdtjWYI6ewW3Eg3esrK4BgQyqZzqzRHayiTNLbrR0afwIt935FnFqJDSxgm8so4DEQ/kplk6XT+NUPu2CKxluDStjKJRdJ5ehg7Cptii/zokEIgkASfrKpIyEziwPkxyWDd6FFCJxlQTNimejZLeoIxOc0S6lrgtaZp2oQrKsqJWjswm8+OphepkvmjHx0+AkJR5BlZXWOkwLuedhzQSmDLEiFVqhdkFucFEYm2OdV8AZOzKk2aFFoopaAn4FzP6dkZu+tr1vf3aK0S6efuDiElVw8esLlrcFazMwYnNKLKCQRmmeVqseDF82vGbUMbR/KTJdLmrB485D9+7/usipjagsZgihxhNEJrlDIgIlqkM3hwDtG7afWVjN2esctRWYXQB9x46n8LJYk+pKMAgr7pyPOCXdMSfNJALCYRVZHnFEVJrwZkP6QgxTJHioJEiPbYKrn92i657mazGXoy1hRlmYJChh4lJ8eh0lQ2FejCRA9+Pb//thXjplgfKTO8tAhtiUoRRLoQXkiMqeiHgJcQVAQRiNExDD0Ej/AeEVO4gjxU6iU4HBJNjB6iTnraINBaEmPyqfddhyJDegFuII4Nwg/EcaB3/XFHIWVOiIcqNkfEVJh6n95JvI8Mg0fKAaUlVutjgSqhmgx4l44hVqMyjfCOYbeDdkT0kVwaxOARMdJ1W6I2GCVp9vsE+e9TNV7Z1EnwIZCXFQFJ3w0pbEFJnIxIHREh5cFlmSFGpocUaF0Q/Mg4uomNbwipB4dkJLMSFSvM4oK8mGNsebz10nQXk3hZoqRBitS69HhMrvDrka7ZEYael08+5b95+IhL6TjLBDKzvFSawmToAGOI1HnGxarmpW9o9nvWN3suHj3k6tFD/sOLT3lx1yLymqxIK6vIJJmoEChCVESZoQqBcRERApmSqMwSZETENsmdZap4K5MQZdKDJuCCAyWo6jlCGawt2GzWtG1L3/Usl0u0NfTjQLcfkAosAiUz8IEizyknNpyShtxKylwm+29RYjJLINL2QypmAloCYaTdbVA2cH52gfCB6DwocXwo/TrHb6aPLkRK+BAKoXOUMukMoxR+JKWb9GHShWt0pmjGVNVVMTHGD6YTrdJZOcszRg/DOFJUFdrm7IaRrChTbJBMqrKuaTGToaTxfqpkR7q+/YkzHXDstQNHK+mhteWcmyrxpMlo9CRyUXifYBZKpB67VGkSDl2LiIlYkhycLoll9nuiEJhKsdulivDSrFKFO5NIAs4HlvM5UoAbU1GQEAgxccd8ACMVhHg8u6et6+SH9ylaKsSIUSkmWUk18dEUtpxR1CuUTtrx14bipNlLohSO7sJIZLaYM/QdXTMjjCOr1ZJXt/dJudf3XJ2ccb8PxADdmG7s4DyFzTitZpzu9rRjhIk/963vfpt932Ci4McffcTl+QkP3n1A0Q8INEYZtJlyz4WinNc4NRJ9Urll1jJuW0QhkdIkpaASKG3TNtylnZuUgqquUFphlUIpQVUlHFkMgbbvknvSmKMqsu97RIgE5yethznivtwxtsvR96CnzL7D1h6SASkvckxeThl804LwOUQmw+c50Y/q1wTaM1mBtyVhKJAqQ6meqDRhil2SCmJM22YRYtoyjwOuazlE7Yij7U9OcMgZQkl2ux2r0zIVt7oWZTIESbo6dP2xYt627RvMOH08Yx3Iqgf6qzHmOHGkUPRuPKZyHG7+EDzDdP4XwU9KuCkpxerEcMsyYgj0cKyiG5OcaXlZYowgRoc2kpQh12NMaospnRI63dDj3IjNLBKLNgohTdqqR6Z4KH98X4zRKC1oh1S0IyZeX1XMEFoSPHgMxs4w5RKlf/4t4Zxjt90ytDvcVCjNi4KyLLh9tccozeXVJfXpCZvFCkRLLmAePFGrpJMPPr0/UjFTmkpIZF2wnFV8/8NPWM4rZjJjv1vz/OYVN7e3zFc1SmoyY5AyYkxqpY6jJ1ibsu1DZLvZ0+0bTN2wPBcQPCaLGFsQo8fhCXFESIGY7rG8sJyerthut1P81wAyY9g1iVdv7dFynBJRNbNZinh+M+7JWgtapd2b1gkp1qeOzkGk451DTJFfZnqfY/xcjuift6kl7d4lAnSGKWe4doOUFiUNjnQBhAxoLQleJNWWc8Qpb2wcx8ljbpIjKYyIYUDYDK1VivoVgrZtUGXihh8UYUqqpM2eDCqHKnrCQ78GPBxgEwfW+ptRR3pKV01FHZecZpFJ1ZfMJiIAhBTKZwqGOBInRvzYtbiJI55l2RF1rLUiyy3DOJAbQ4gOYzVj35KXGslBKCOoZjXCRKSKBB8QRLKsgjAiea3oO/jn227HIcVGmYyyKFHaEiUoVaBkgc4WFLPTdDb+KUmmmLTY1lryPKNvElVmv9uTZxkXl5e4fqBtGhCCbdezePttug+fMEhHjD15ccrNbgNxRHrB4JL0dl4VPHz8mE9uXlIpRSEEMoIymsYNoCTtbg8CstwgvEQqlSauG2j2HQqoiyrVRKZ9SHN/hyt6bD5AFRh9QoolJWJkGHrGMVlYs1yj9IzNeg3Ck5cFHjkx5VuAZGKxOflkC16v10C67t45tNGpNQtTLt/03k3dgHEcMTa1RhMhyL6xov9trLrH6aiORNkSYQuEMBAPUH2PlK+12YTI6Bz4Q47Xa/pInle0TaKFpCd8qiZnWYaf/OeeCfMsE9dNTyCKQ8TS8+fPWSzmFEU+tcpeww4O5gd4rUf2wR9ll0xOMyEFPjiknDT0WmHUa96cyQ1RKrq+PW75DwIcN3nQlZIMQ39cUYU4JLsGrJZH6+PgAsZKFAorkxQzz3OEUGS5gZAIKofX23Utbd+QGYvNLJm2KKGJYdLCa82ABVMgbeLF/6yLdihGHqrNwzgSidyv15zMl7z19ts02x3rXUM7jlxdXdJtNuizGnnvyeYVm35PVRiQhmFwYBWXy0t6AdJ7VjbnfLbAB0U+z3n0ztssTlbM6pqsLFJ/nBQ9jYhIBPOsQhuDzTNUXqDqGrfZ0Gw2NLs9yubMFgPtMFDOF0nQFGISRpGurfcu6SkIFEWWtvpBHjkEi8UCYwzbu/WRFnQY5o3t+TCMDG1LXjq0tRhtp7jvtDgonTErCxbLRfIcKHXc6P66p/rnK4GdCCyHbyrEgDQKbwReQRSCGAQ4kYJRQ8ANI0oInEsfGylBCkaX+HBZkeGkwUVJbnM659E2pvN+CNi8ILrIOPikce97tNLHc+68Kghjj8gKstymIp/KGN2ANfb4UIH04BEkTTMiUOYWayRKBKxVBD+ilECJ1CmI3qEVtJttyk0bBsI44ia9wAE5NQwDoxuobY2UYVqxpix0Zaf3QLHe7cmKir7pqfIlQliMLrCmIMsqIn1qP8bX4YvSWOZ5gYoBFQNCGoSyyCgmLh5EbVE6R+nsr18zSARcn0IX+rZnGBO/r6znhAD7tuP9L73H+u6e2+9/G4qcMNeUX37Aeeaxd3dgSj784QfU84qLiyvuvvsBs8WM6vSEH338hEeXc5bLxzx4cIXJS4pVzeXbV9TzEiYTkFIQR0e775AxYJUiNxKsBJ0Kc4VSjFISlWQ3tozdSGdgs9mx395NMmp9XGm1ULjRJ8inEDgfGNzAOOXwzefz4y4viHhMu4XUrciqEq0VfT8kR5qUmCzJXAUQoyT4iECR5QXnl5fMV6sEEpXiyFD8dY/Pb6KL6RBJii+OU5hCjBCUBK3TWVpb4tjTjw4pJEqktkj0ARkTMF+IBIvwpKxqKXM6L3ARdJan0AMJvXPgApkt8CFNgmEYkXmqqodxoCpLhqFLCGiR7KqHA+/BxJLO5ofSVGR0/SRxjeCTRHTwY4onFpGx78iMRkhJ32wI3pMLiSOdlcsip5/acwe2nBCCoenIlguIyUhSFAUSPT1cfIp5jhEtFc4FrBXHOkI/9ETGpJ9WKcnUGEVuc0IQSN+DS9SeKMGKlB7qhSCr5hTVDGXMz77tJgtvnmfgR+5etpR5QX55yasY6ZqW9f2aWVVzfrrEWMFAj68Mi/fewuxWiQ67KqhsRm4sXy00+XzBy7tb/o/vPaSsU4hElILFyQlSS3SmQIPzAsYRt28Sgmu/ZzNl7WVFzuLiDAbN2PbcP39Fv9mw227QueXs6hKtQInA/u4mbaEn2+hsNmfXdPgASluq+QJrTcpa0wnw2ffpPauqMrWAbfJVCCEw1jJ6lyS4WjH6gFaWbhipZAq7DD6Cmjj9Qk3ahDeEWH87CTPwerJLosrRusDJDKlzlMkISk0FuVQVdnFIkAWt6NuQFLMiQfcCgnbfonJNXs4YfTi6ypTWWNKW6RDn1LYNw+jRWRKV4APd6LBZzuh6nHBHJxQc2HZMxBlP8KnXHVyfetFGQ0z4KWslwQ/E6Mm0QonEi7faIJVmfXfPbr3BakOM4ljgO8QFjeNI1zXMlwvWmw02zygzy9APKGXRNsPhQGpskWEygbaBYdzjxx6tc5Q+MONI/d6QYqKMMUjhGV065kij0crgp66HyRaorPy5N50gSZD9OOKahnZ9B37g9uVnGG0oteLl0ye8jHBxseKjD3/E9TiymM/TroHIzXbNdujo8fj9hssHFwzOsbg8IS8L8qpCWY02FluVKRPPjzAOtPf39Lt7iJ75bI7venb3aza7HSovuNnsGNzA/d0dt69eEfqesig4Oz9PKbpCo6RGCEXTbHFul45vQaCNQahU95gvl0QhoekQJqHFRjfiRoGQcHV1xd3d3VHYdKiFpDZmRGio6wqpTdJBTEKrQ71EaTU5BZPH42+xBPbNE4kEYbH5HGdqvGyIMrV9PIEo4jHy+FjhzQuCsWl75QMuRqSxjM4xNnukzsgzmbzFISC0JMsO8Mb0rfajoxQ6VbClIziPkBqbpd3CsR2iFAQIPvVex2FIYgc34oaGvMrR0qMkaBkQwTP2bUI32VSgE9PkGEePDKReskra6mqeJnhdJ6RVOvvmx1W+KIpEw2k6Bg+Z1KAUOrPT1j6kM71RSZqapVWDGJMl0wcya9A64YdlTA9OpESpJEAJGEy+QmVLdFHDZHf9a1ctpow5haDfb/mz/+Vf8uqzJxgcJycnvP3uu1ycLLm9vePuxQvO5gvu7++x2vDDH/0IpRX7IekUaj3jK19/P1Wz2y5xBIxGWYvUCkdAGIGIEeEDu/U9Lz76iLa55+L8jH2A5y9u+OjDJ9xvdmz7gbLMUQqqOme+WrCcL1kulpRFwcnpOdvtlrF37PcdTdMTfCDLJF03YiIUdYUtipT1LhW1MbDfI7qA0oJg1cRtj5PXIBVyD/CNPLOUVY002aTrSLwASLLqQ9oqpIKmED8NYfn1j9/ARH/9GBNRgygwtmZUW5CaQNoGSzG1t0SK7xEkj/ToPFpI4jASXSRM9JS0245TASvlisUQ8HHE6CylrOY5m6bHxQRSCAh8FIQoUFMK5qHCLhDJ2DJ6mr45Vt3bZo8fO7S0SOHRMvHlQgyIEJAiEnzyKff9yPZ+jVaase/TzoDkPru/v09Hgymyt8hLIglgcOjPCiFQWuORRCXQ2hBIUc21qae8d421FZmtUk3Be4wGKTzGpGq+8yNuGIjek9k8Ffy0QqkCmc2RdpYKceLnUMxiAiXcvnzJ//O//+/54Ft/yqrMOT0/RQ0dzd01n338I2yW0e87zk/OUj59jLz11mNevHzJq2fPUVrzzW/+LsuTFT7G9CASk2BEglACEdIDEu+nDkXP6nRFXeeMznPz8p5Pnt7w0bM7mn4gxAhecrqs+PKX3uPq7QeYrMAoS24sXZ8q88GDGwNdOxAjeA9FEchqkx6eRuFJxFrhAzMJITi6rqOqEgyk7zq2291PILqrqsJMzr5DoXL0nmyS3h7qMFVVTd0O9Te2MH9d4zcigT2U5AQRVEoHUTpHSoOQCjXdsIiY8ExFxth2+DEQo6AfhsRnN4oQBb3z+CgwuUouNp/ENlmWcLyRtLUaxx5tbDqfh0iel+zHEUhn8OMkF2mrNnQjMtmhGPuOrmvZ7zYsFhVlkaFkAvwpyXSuFhRZhhYRN/aMQ493I74fkBP2yg0j26Ylr2qc8+x2++NxQ2tFdEnQ4X2yS5Z1RTe4pL0OAmMsWV5iTA7CoKQlL2YolTEOY7LDTox4ISTD4HCuT5Qem6GMRRmLlxJlc1RWorIKZXI8ByXc6yFiAnJ851t/yR//T/+E5vaWTEmq3FIWOYvlAikEbuiTzLbvuL+94eLhA65fvqSdVvKz5YKvff3rLOqKbrejHwfGfQPeI6REGglCkOUJI53EZD1SCvbdntvre25u1tzebbnbdrRj6v+fntQ8OD3h/fcec/XWOU6H6ehmuLvf0Gx39E3Lbrtlv2/Y7xtG5zg7PU16fw4hYQIhJYNzE/BEpbO3kswWc7zzDIlTSt/3bLZbyqk/XpYFxuZ0gzvSfxKp6BDYaDHWMlsssFnBG4fCz218zhP9jdvoeEhRUJwgszuMMgSVM5oZImaEfosb90TRE6RnDJ6x9bgQiDJiMouSCpnleGHYdz3aS5RJDw2PQchkPtFZRu89VVkmo8kwYDOT2PAxmWFSe0sdgRLeQ+dGghuwOnC/fYmVkdl8mVjtSiQHFHrqx2sikhBHQvSEkJhkXTuw2ewp8gppNFU5Q+sMgUqfr0pcSIo3Yw3SKAY/ooVFyIjNNcooiAptirSSy4SiSsq9MNFWXBKECI3ROd6DEhEh0vEEmxPzGqcmIIepUKYkyyuQ9mdfMsDtt/zpv/if+Vf/33/G++884g/+8O+xmGXkdUW1mPP8+TPuNzv8riErC2yVEYXn4dU53/nOd7m+veb+/ob33n3E3YuB7W7H7e0tu02DFOJoOZ5VBXVdpdaUmdhvbcuL58/5+JNrdm0CTeoIb12uqGcVs5nlwYNLVmcrokmAxmE/cLe/4cmTF2w2OwIDWicthcktpalYnCxTtp7JyYt5qg9FIKYui1WS2WxBNVtRVDM2uz1jaAhIXIAsL4lCEFB4kaU6kEkBINF7xqGdrqVEZRm6LNBlhbAlaMvnkYn+5vhc4ZDi9YevRwQpDXm5YHefo3SB1jkxgHOGcSBhjqY4ZCZ8c0QyjB4fPVWxIC9m6NzRdAOF1fSjp8w1iLS6S6WYzWbEqJMxKirGIeWdAceiyUGaqmxSorX7JkEwcJg84+RkgTI2gRbdiFQGop+CDcYkgFGBGJILLjiXZKllYBgcpbGgE5a5yDReRMbgCWKS+xqLiym8YnB+ghRYhNJEn6psQiqEthRFBaRYaSY4R4pGDggGYlSEMBUYlcLmBZgsIZKVRZgCadIqf7wsP+Pua7b3PPvsI4yVfPTpJ9gc/vD3v8FZMSe4VEgsFzMUCf8UpeJb3/4OX//a1zB5wavrW7785S9xc3vPdrul67pE2PWJ+xbciBtHurZlt9szm6dcdGNSoMZuu0XIwOXlksViSV0nDbwkohhRKoDr2d/vWW+3hKDYrHs+e/qC7W5HUWouL0+Phc9Dl0NrTVlWU06cRWoNJnVe4hSmmWXF9J5KyrJiu94eYZxaa7RxaOfSLmIqviV5rMbmltElybdUBmXspH+fqMef42T/zYEn3hhCCKStENkSkW3IXEM/9ASftlTBJzmslBY/UVZB0Y2efhxxuz21qciKkqgz+jFgs4ReOoTbH9oqzicFmy0zXJdaajGMSdU2CWmO2ODgkCLSDz1Zpji5uMRketLERzrXkWlNcNA2O9zYYbVAS0HfdmgZcH3P0I8URUGMA8M40HYDyxOTbJeZTMmfsxIlRdKVx0CUCpvnBFJx0UUQSiO1xWQlJqvTn/vUdyeCjBpjJn16CBADUkFwEqNt0lmrnCA1mBKRlei8StFUPyXdOIhCYowM+zvG/R0yOm7u7/jTb92nLHVvQQ6cn55wd3eDzmvqaoY1hi9/fca27RCm4PLh2+yagVe3n02MtZ6iLJFa0fQjMUSEEgQhEWNgRpLbHiSmDx895PKxYLZcJrDDBP64vblm6BqUt4yjwyPYrne8uN3x6mbLftNRZJbT1Yr5rKYsq6OkuaqqIxz0UCBLRVtBlAnzdKjL2CxDWcvY9lhrj+GKeZ6zWMwp60UCQk73jpQyMfVVCt8o6jl5WSOV+dyIMj89fuMTXUCSyukCXa5wzU0yJAg1/WqQciQGT1LTpafi6CIKR5mV6HLO6EPqmRc1UbnUSxfiqOY6+ITVhGJWyjJEl/YGKq2GB9/ygffuhx7wFEVOtaiRSmIzi9WK/W5DlpcMbZPabi6lmOZ5hpaeYrnAKLjrerq2BwR1XdG2PVkpCSKgM8usrtHWphC/kBxzwTuqepFyy0NACJUMHVmFzSqUyYgyw4Up2kcKICCjJjpJJNF4nE+pIGVZU1ZzokiFPaksIiuRWY3OS4SUUxHuJ0txKRIq8OrjH5P1O+zYsapq9m7kj//1v+Pl83u+9v5Drvo5z58+4/n1lqqaIYG8KPjgBz/g8VtvMatrnn3yKRfn5whpkxsvKu7Xe9o+EW+skszKgrqwFJnk9DSjrhMeeRxGivnsmK9mrcXt01naS839esft/Y59O7LZtVxv9gwuMi9mFFVFJCJFJM8z7ORIPOCcYgy0bYtQadfjxwFr0nHO+4hmOgpqRVXVLBb9kQGQ7peRWoijJv4IJAkRKTVlNWO+PGVxcorO8s/5ZP56/MYn+tHRJi22XDLaCoeaNjXJTz6Onr4f8SMJCawVQkOmM7TNCDpnRCGUZfQBqQ3BeXgDZHEQpigtGVxgGDog5ZgJBMPYT1ry1+ihwY/kVjNbLZHWEoRAKE0/duRlhes7pLF0Q4+xFk1ijA2uReGpy5TR5Z0/6H7TDiO4lJemxFGA4WNAq3wij1jcFARQVQXSGJxLLqwoFKOb9NLKorUAcQAkgFQmab6lQMrkbtMmQ9kMdEYUGqkNwuRvrOZTYVT8ZMsnxhTxe/3kQ06NRL/1FjunuN63fCoU3/7oIzbNS/7BH3yNi9UJdzcDd7db9l3qUqxOLxA64wc//JDSarQtQEm6pseHgc2+Y9+0WKMR2tAMnqIQOO8m05I48gBubu7xQcFKsd91NPs9TTuy63peXm/56Mkzds2INiVBGZRVoDR9P9K1nuCrxAGc2l4H7UIzjOk4pNMOKq+rJOLyASbTVAgBDSn0IyZD0na7JS8KlFLc3d9PmO50HLCZZQgRY3Nslid+gM0TyVe81ml8nuMLMNEjUSR6iChmiGKOkxkeQE3bVZOTz+0kj02UF2QC6fsISInWKdhASU2MAqEETduS5zqp6kIgjgM+iKnvHdBKgJ9sr12bBOZC0o8jUmrQOdUyIYhdCCglECJilEBJiJOddXWSkYnI0GzwfsBLIDqcNNhSYceBYd8yDA6b1ygpcUOHIG3bA5GoJOVsDloThCBEKPMSlErpsZhU2Z+oNcZoiJFhcNPrMhir0FqClwy9Q8aJgpJliRSDRJkCkZVEXSN1nSAd8MaD9Y0rEyMhRmZXj5k9fER/fU+zaZBy4OLilJqIlSPXd3sqPbAsFO2+w8qIVIaz83Ne3dzSjo7zkwV5MVXUBazv78gzw8ki8dM6D7WOnBZQL8+xeUHb9XT7jr4NrC5OsTaj3SWo4zCM3G92PL/bs9019ANYWzKbLxA60V7GvqVPj1x8TF2Irk2VfOdTy3Yk4mJAaUM+jmRZOi5JlRHGJHVGjwQNUQmiiGhrsFOEk9akorBOLHibWaSS5FannWA55cSnNxSp/ivduqeRoH8og8wrmFo9kYDUGcpGPEOKN5IaAgwu0DuHzQqksQRtESiEUHh/OGMqYkytH4LDKEXwAS8CmTow20cUYLRMWW1aIXxAKM356RVFWROCw2aKyMH8AE3ToVXyM0c/0vVTppPU2LJOMUx4Rt+AVoxuwEeBg9T7NxnW5IAiz+z0YFPpgTL1zwG88xPaORVxjE7efSXFRGZVr9V8YiDiiDFglEHKxBaPOiNIQ1QZ0laorEbmS7R5w8TyMypxB4TV2ZfeZ3Adj/drbl5e89GT57za7NmPI7v1mifPbjidzym0wmQZ8/mMLCto91vWtzcYJVmerDCZxQeP847NdoutZnz1y2/z1uO3eL4dGe5foPbPGaLgZL4ksuPm+p6u7ak8dLsUb933PcF7bu+23N6mfPPFLMlXldL0biS6gegHAklx2Y+RZ89eoGSKuDbWkGc5XgTG4I4cwzYryMsZtipwQ4fyYIwk6ohHUM8r2r6n60fmRU3TtkQpQaUoapPZRKw5kF6nJFWTZ4ip3/5f6Yr+egghsMYyWotTGjetYEIopNR0fc++SxBIqS1KG4YgyFRCGgup0coSBocQKcMNEnSi71pQAWlE6vKJ118z6eeTeUOJVEgpqzn1fA4RrM2JMeAmCOE4jCkKOLikvSYQhZjSPAMK+RqD3Pd0XZvQv06CsTiftPjKGtTEbtMqCS3kIRr5IP5RyQOgjEXbPP0wOcbaJHCZimbJCZfy36KC0QdyaxE2w4sMoQuELkDlSFNiJg3/G+/+z7weIJgtT8DkmNxhsy2z+YzTiyuu7675/uaOV+st3ShBKkbnMcMWLbfMioy3HlxweXnB1aO3+PCjj/nRj37M7d0dIcJ8EPzr/+Xfcrr6Ht/4o3/E4vwR0UKwhqZvyaqC+nRJWAtuNg27buDFixfH7sjt3R1ap7jp2axkGAaaZsvg05/neX6Mrbpf31MWxdF6LDuJNl0yoBjDer9F644YoRoGTrMcGSN9t0doh5F5ur90Nkl7kx++rGtQKak2iCTLLusaqQ2L5YrZfImyNkmuf2Mn9C/YRIdUUU9xRRohDt7ogHMDUhmKWYmbClcqL1MSiS3wQqfWhdBJ5TSMpDnwuhKauGpTuKOQSC3xoyNKhdSavu0oi4p5UZMXVfK9K03fJw95JFVsCQYpwU/iCTd0COcm9ph8A+OUeuvGGMamw40RRdLzJ020wgWPRiKICKmObZuDfholkSbHFqkIp2yWcuAnu+4hWiqRXywCjyeQ5RZpNOgMpebIrCLaGpnP0OUc8Ubf/OetMOmMrKiWp2T1ku1+h80KijynnlWUWcD3j/FB0A6C0YEXGu8ChUkUoa9+/et45/g3//7P+OSzp+w7x816S1XPWeQz3rq44ub5Z/yT/+n/w9e+/g3ef7igu9/Q9z2L5YJt23PXtLx4+ZR+8AxDqqUM44BRGvxAVRdokyTEXd8cqTJapfLiOAy48eB4FGRFjY+R3XrH6qSgbXtevrqhLC1CRKpZjYyeEByua+jESNQBVIaUGUVZoHWWzv/DCEdZK9i8pF4sqecLtM0wRYkyOYjfzJb9ML5wE/0QEB8jxCAQU59YSUMInhE5+YoVg0vm9rS6Z4CY2nAgVDxW2yGiypLcGlxMOVwyJNWXnrLJkYJqlpEXNXmVCmIyCoauA5JG2QcxRUk1xDBCDBiVHiCH/qxSgoifAhgiIiRqjdAKomD0LrHqJ3FUiBEXI2EciCFtKw9kEmMsUiqikASS/VHp1yv5YWt40OdLJOFISzUIo0BlCFUhTQ1ZjchmIF/feH9TJzdOLSapc9772jf5NHrWRN7K0spY2BIRQQnJ/bbl6fMbRgQmK+i6jl038B+/9yO+/e1v8+r6hre/9BXWbYupT2mQfPDxM5b6nKLIGTYNrzYtbuiYyUjTNfzwo+fs+5bNdosmkmnDfDZLuXZjCtEIwaUknLGb0m0jVtqE9yLJkUNITDcfUqwXYnLiCY0bBT/4/o9Zb254/NYli2WN0QqjBHf7Ld1+SxYybGWRQqAmkVJWl0BDN3ryqqauZ4lOA9iiYr48SdxAqUDIdL0R/Kam+298osc3PoghMHT9ZO4HIXUqeAk1wQAcyqS4IZOXZNJMZ/sEgITkWxdS4NzIbFZjTWK1Rz+ipUTFlD4SnAMf0NpMgErJfDafVkyDEIphHNLrE+C8I0Z/nGB5nqKOXd/TNfsUEElyjQkpybOSYewYui4lssSUh+6DwBbpvOancD4R0jncjck8YjOb2kCTnTeZbgqUyVMUkjRYnc7mxDC9edMRR6WkEmlNyltTGVGlnrm0JcLkBNSElPoZ1+MNqAJM/XipmJ+cUy1WZBJkjNzf3hDGHYXVXJ3MWRQZV8uaYAuy2ZJvffs7oCyfvbzm1f0eHyWD82zbFhUNu86jQs/3f7zn73z5LTJr2bUDi2rFDz/4Hvfre4SRtONAXhZcnFSczMpj1pwQgvvNhm4YpiNTPO5yhj4RXo1RmKygyG0iu+iMsp4hlGZwjm4YaPYNT5+/JMYBHyJ1VZFnlr7ds9uuGdsGHweyJscUHcGWCJtPsJGAD36CfhQsVycgBHbqoadJfoBL/Oa27fAFmOiQzPkCEC4gvSeEkSAEOitx3kHsCS5tY7UukhlDpFaRkBK8Q8Ux9VXHAT+OCD+Q5TVmgjYGr1JvnSxNqtAhYioMRSHJZgtUXqTKuxQ4P+KjI8qIiAFtBG4I+HFAGkNE0LU9waWneBQitb1CSBN6CChhELpMr78fURZUpggq5ba1+z0iRso8Q0lJ40dCBBsVKkgMBmkybJZhTIVSdUpfkYJRgAwhxTxFhyAQVMoLF1JPK3mGMDljUaHyGUIVMB0UfvZ1eD3J3wy9FFNk1PLqHX7w6pZcBkRecHtzQwgCLSDPLauLK+xizunlJfNlzZ/8yf9Kc39DJiUdBqUF0OPHlouTh5xdXdKvn7IZBFl07K9fcq80znfMKs3yZIG16ZhzOrcs6gJjMrp2oO9HBqPpfcKP3dzcpiRUIdDCEEaHylLO/fXtlizL0crRdx15nhOBtm253zeIQhHIidogQmTYrOmUYb3bJKuph2bbktsdUVswaXFQ1iQu/tAlq3JekJV1cgdObbxE4fp85a4/a3whJvqBMOpHR9e2KaqJ1+aXSFolyyonynQ+FiLS9w02LxiHDiapJzHhl0RM0UTWmqPTKCWaKJxP4QwhJOOMMRprTPp3yLSLiCmPDBHRUuPHDiUgsyb13N2ImnzxwmoynWKS+/2W7XZLphXGJmWUKkpintNPYowABO/Swy3C2I3JWju69MAYh3QcMannbW1OUVRIY4mCY1KrmAAIIsrJbReQhFSYNBUimyOzEpvlSJWRcsn+5mtx2K6/qfKKU4t9dXbB21/6Mh/+4LuUWZ6MI7sdXdsgpGbXNJRZhhtG3n3nbcbBsd/u6Loex8DoIkW1RGUzvvF3/g5PX77ifttxrz2y31NkFaq7Z1FI5rMVZ2crjFXM5zV1lTMMPXme0mVHl1bwrm/Z7na0k6y2qqpULDVJwHKIqL69vSWzJePkDrTWIibFZD+OU5AHCCHZrLd0XvDs6SvOzs7QumC76YjxBqUNppihOfTMs2O8dphAcYdsut/05H5zfCEm+sEWqkzqjTcywQgPYfWHtJQYAkp7RBwILqF5xz5BF8MEdEzb6pztbndEQB2EF1LK1N5xCfnUdT1WS8rCIkhZaSnjTSSYohJH8qqW4IMjeod3fXqgEFEEBIG+HxAxHpM4wigIPjHcBBGdW5qxRzqPskmhJ4ym23XsmiZVy2NEGYNUlgB4QOvkUIMEyowiIkQizablIhW9mCa91pZoS8iXyPIEafLpgSWnE6L4a+/9T//+zUme3r/0Z0IpTi6u2O/3tNsNeZ5zdXXFq+ee7b4F59itt8yqGcVZxjuPH/KP/uH/jizT/Nm3f8Rms+XywWMevPUeUgusERR5hg+eWZ7x7qMLzs9OGNucIrdIlVxkloTkFtrSj54gJE0/0HQD/TCw3++PSrUsy9h3O9q2xXtFPUuhC02TcN5VVSGEYLFY8PTpU169uuFmvaPte9YProhB0PYDm2Zku2lZLSUxaNqux/kNWVlgijnC5JisYrlYEEVKhzkk3Zo4KQy/QDP9CzHRDyv64cAewyThmKSFh78TQoAwIERkHAa8D7StJ8+r11FGB/rppFISB95XCJOeeWQcOxyBtt0xOzvFWp3aY+OIFOnspUTyo4sQEdGDj4kxKiJ+6DFaIUVIiSHeESYVWZ7nZJnBDz2CmCD9GuLkQ+72DaUxKGNQAqLzjJ0j+oiUgWEYCVIhigIroLY5eV6lCSwEXjiE8Kg4McdEEsKksIKSqAqEnaPyGZiSiD7uHH7eeFPXfnivDz+OnwOiUOT1gkdf+io//O5f8uGHH/L21Snz2RwXYNMNdLuOIsuxWpPnlsvzJf/gj36Ppm351l/9kPWLF8zKmk+fP2W33VJnhpPLh/x3f/QHiL4hjD09BVmmkQqyzBBiYHCe9b7j5vqWxXzFvu0ZfQqPtNZOXoLJYFOVBJfovkVR4lzPw4cPWMxP0hZea549e8Z+v0/quKbDR7i5uUsBGKUC7fn4Sc93vvOXfOX9r/DOO+9yv75ms95QzPaYsqbKKqqqIqCO+fPy53n6f8PjCzHRAYiJWHp3d58KXkoRhCO8kYzpnEvcdKlxEQYXGb0n+ogyOSk0MfG01+s1eoIsHG7WFEg4MrgeTaSqC6zVUxtMJY14EpCmCnk3IGWEGAjR44aeYegY+o4qT5ruECCI1KtPfu6UjmKKPIEo/JiCGKyhqCv8ek8YB6QS4AVKKPp2IPpIZiIyf13Br+czymqGFBo3etCRiAPhpiKcJkqB1BqTV0S7IsgCaSswBZMlCH7GSv6zxpttttc4rdTePHwchaKYzXn7y+/zL/7HNWJouDhZMJvNGGjphpb9bs+NfMnZ+Yq6tBSPL/hvf/99XNPywY+f8eR7f4mtNBclfOXdh/z+N3+Xth/QPjKv5+g8A0JyA44+qf2EYnAeqQ0fPvkEN0YQknHaySmlUFLSDwO5LaYkXsnDhw9ZLGqyLKcskl7ee8/Nzc2EXJZobRNiWhqG3lHUmrPzGV95/x2ur695/vwJRal5+OgRTdcdF42UB6CSi/Cg1PQeHQKoz99z/jeNL8ZEj2FSYUWsiQxhJMaRkT4hdJsRPyYV2xgGpNZ4BC6IZH3sAk3rmc/nKdtsCnh4/ytQlVWiv5AELSIkFJQwkqgF+77BWkMmJZFACCkiaRwSXw3nGYeGoWsJY0j+cw0x+LSaTmEUUmi8D/TdLrUGRQDhCGODkiHBGYLHWJXifaVBZSLFBx3wyb3HKEdlDYv5nLqcQfB07QaTjSiVikhCSKJI8UtaVchsjiiXiOIEqcopN+1wRvy5ILjXH/4nlVpvbEOn4lI9X1ItLnnyw2+zLDOwFl2WLJQhuoG23bHZCE7OTokCvvTWFaXN+cq7z/nRk0+QWnIyW/DV99/nwcUpu+09YQyY0qK9xI0j601DWZb0Q88w9Iio8C6SmQwRk1/A5hlGa+qyRITISTVjdXaOyVJPHalxQbKaLVmuTri9u8U7z1tffo9d3zM/e8jZ7YZmtyXTkvVmQ1mcIIeetx8/4uvvf5lx6Pj2X34L/fZbzBcrtLHkeZG4ewFMUSOVnmohb6ixvkDjNz7RBdOWUUSUDBgpGKNicIL1dmR9u+PVizvur7fkRQ06Obp2bcfo4fr2jmev1gxhKrzFiHce70a+9VcfYIzG6Im97j2FVswKy8XlirxQvP3OA5bLGUYbvB+RCdyElo6xH3FjTwgdeIeVlqgNo0zmlYNqVADj4Bn7ER8SMy5EjxtTZPLgfOqpC0UUIyFKQpBIGfEEMIpu0xEJZEpPRTyLRDOMA0IHpLIo4ZDSIqRiJIDOyKpT5PwSb2cImf9UeB8c+4M/b77/pyZ52rO/8ffTr9pY/ugf/Z/4n6+fpgfvROypS+ibTcIzac2+6xAxcn+34/LynIePH/HNv/NVNrs9VT6nKiqECFSlpetG1vs1hUrpNV2X+G4RuN3sQRmafTcJklJq7dlqhdGaMssxWpNnOZcPH+IitG3BDz/4gIePHuHjNfth4NmzZyil+NrXvsbpxQUfffSUk5s1zW7NrEimos+evWJwe1aLGW8/fsjpcsG8mvH82XPe/8bvJRmyTFv13bbBzj2LZZrsB9PMF238Sif6Txd2fvomevMM+ObfjULg+pb9es39umG7Hvnkxy/57Nk1TTdSzlY8+t3fpZ7NWd/dcne/5ub2CU8+e0rXj2xbGINnWLdHemzwjt0QcG5/jM6VUiKRlGbgeud4cFYgQ0Q+vkSeRWL06UEz9ih5qIynxBUXAyI62qZFl4boUtqpUoqh7wlBMLqRojA436N0gk5EPCEqnBuwWmOyCh/l5H1Ogpmu62maFpmlFULI1IPtRocoS0xZoI3FCIP2ir7paf3A1g8sH5xSLixBZghkQmi/+f7/KhaXn/V/SME73/wdvvHZ30fv77h/+ZJ2e8Pp5RnZbE6UkBUFs8WcTz/5jB/+8CmP3xb87u9/k9YNFAzsN+tEl/WOrmsQIlJXKSrLOU83jDRdir5qu47Rt8d6yyF2u9SCq/NL8qpkfrpi9J73vvQeP/rgR3z4wx/Q7nc8/eRjzi8u2O+37Pd76rpmaJNX4WS1pN03eJ/hBNzt9tzfrxnHPfebLT5CVpRk1ZxnL1/xdZHSVsWkb1dC0w8Dzk2EoRj/M3ZIn//4lU30wzn6eLb7qcn85jf/5ucPfnEpBX50/OVffp+//Is/Y2wdV1dvcfH4hJOrS6Sx7IaBT2923K/33LWR251ju+8YvKcbU6aWMSqVq6NiICKlRQudkFNCELxgHCT+viX6ERUihcmIYsRoSZmZVHwjxR0F74i+Be/xPuD6jqgcAosfk7nCGMPgQmLNB5cq5UogbIJPxjEeVXBKKzQyZbwTsdbgvcM5j7cGlKao5xP5JSOvZiijIUj224ab56948uHHPP3kM8ZBki8uefd3/x7f/If/iOXjt1MFnv+c7fgveb2BYrHkm3/0D3jxg28jhWT3ox/h+pb5yYp+IupqrVmtTpjNT/jOdz/g/OEDHr31Ntd3r/h4/SGfffYx1mbM54tUKc8F622KfGr6HoDQDzRtR4gcc+nzPKeuaowwXJ5foHLL4vSEqCQvXjxjt7lnu7mnKAvGseOTjz+kXiyZzeas5gv2my3GGOoy55u/+zsMQ2q7NW3LZ599ytg3NLsN0pZ0DrJqTrP9iFdPn3Ny/gCkYAiOvF6iVKoNHaK8vojjV75177oOKeUbWNufHG9WeGOcsqulpO9a/t2f/An/7t/9Offbjsxa5jGixwFxd5sKWlIwjB2b3T1Pn3/CGEakSVvySJiC6930dJVYYxDCo33irkspIHqccAwB9gM8u92SFRm2cCznJQMOLcBHjwgkCaXvETFMaaUp01xOBSqlJUPfJg98dBhhcc4zDFMGR9RoWxLcgBt6pFRkJgEPvB8BRVmUvAprfICqnlNOkb5RSFw70Nxt+fjjT/ned77Pxx9/SrNr8Y3nfHVG88Mn/OD73+GTJ3/F/+X/9n+nOH2I+Bx01YIkfX349nvkEj70Pcv9HTfXNwij0dbSdR1BJAjF2+895tX9S/7jt/+Kxdk/4urBu5ioub+5odm3GJNzd7tBipZucLRdx/1mz8nJCt8Px12K96kWUxQF5xcXrDc7hNU8fPiQCLy6fsUH3/sum8098zqd763WDMFzd33D+ckZL54+I89zHj56hIiecWyRylDN55w9esyDd95FBp/gIlpCdNTzFcJFbl68JLhUJJY2ZwyJ+Jrn+a/9Pf9lxi8/0WN8A0KUtMTjMNI2TaJ4GJ2KRzHFDXddN+GMBcH7BPMbJX/8z/4Zf/Hnf8626akX56xO5gyhYbNz3N++wA09eZajckPbrBF4iANWKwYZGMOI69pJtBCJSuNHjZQKox19lzTnWgWCBhk0d0HgQ4a52bCaB+Z1gZIJ/RxdmOTgSZASXKQfhpTOmkuI/ngciN4lSE4mca5HCoUbJpChnrzyPuDjgAsCHQ5BiJ6uHSjK8pjflpdF0rgLzf16zyc//i4/+M73uLlfs97t6Uef+Pd5wW0YkVkg+nv+/C/+OVd/8k3+4f/5/4o02evaR/oWfj3aLA/tfuDZy2ui1jx89y022w1PP/uMt959h64dWG+3zGczVqcV773/Lk+fX/P/+if/P/7gD/8uVycp5bQfevb7nqZp2G63ROGOZp227Y7ilqSVyNFaMZ/PUFpTnay4ePSAYRhot1u2L18R3chusyESqaoaay23/R3WGF6+eIHNMoqiZL1ec16cM6srTFZOaTF5shHLyGw+p91v6Zst6/UtJ8slmTbc3Nzw8OySECEzFq3N8fV+UcevYKJzPBQeHTzWYpSm7zuGrqUoM4SEiEHbjGEY0SIgJdy/esr3f/Rj/uk//+fcvHyJRmLKnnazxohIO6aHRpEXDEOH3+xxrafQBV5LmqYnepJ2PaZ0lOMxIkDE4abjgRAJ0jBoQdONWCXpvURmjo8/6dCm4d23l5R5jutHvGsJOILUOGnoRseoDHGE6AMoGEOfHGsutczSezDCmHY2gSxZUclw0/bOKYUQSW4Thcdmlry0aAbq3OK6wA8/fsI//Vd/ys31LYW1GGMpsgVaJcmux+JcIAaR6Lmj4wd/8q/5b/7b/wP51XtoVDqvC4/4axDnX35EYPCOpt2jVTIeFfmMy4tzPu2ecPfqJWfnVyiRsb7dsDeRxWLG4OCzv/we//Jf/GtOThJ2y8jECdjvdyzmc5qmTfeI0WglEcIzn5XHo+Hp6QrwPHhwic5nrG9uuX35gr7ZoghoAuerE7a7HQrF+n7LyckZRVUQhKBeLKnqOT5EkAqrMoZuZB+35C4iBVijePHiOW5w3L94Sh4HPCPvvvsOfTlDZiVlvUySqUl5+UUev/REj2/8fIjXPdg087Jg7AX7/Q5tFDaTSBQ60+AdY9/xp//+3/M//pP/Ny+ev6DKc8LouLu55XQ2A5cCDsoy5V4hBOv1mv1uz27f4qNI0cOuP6rimqZhHMfUd/fD8XUeIpFH55FOIGKgEyFtL73HdHOyMufsfMVsphHGoaJAxtTKis6BG7AyZWRrLdlu19hM0zY9Ns8IUy55CAFrklpKGnP8fGYz+pDahFFNwhylsVZxcnLOEANrn/HHf/xn/Js/+yv2PVR5BiKgMoNDkZU5zgXCyJTzLTBaktmS7e01Lz/5kLcu306T+9es3DBGs1otYbhAupZue8vlg8f4ANvtnn3ToZTFSM1ud0dRzdBKsFzM+P4PfoTRV+y3a05XJxilKPMFIQjyoqKs0vemlGJ9f8/l5RV2yq0viiKd1Z3jdD4DP6K0SnHSBBCCzPZEP2CtZlYsMJklm5U8ePSYcragKGcoY9lu19zt1jRdjy0qVlohiLx8ccN23zP2Y4pzVhnrF9d49QlXX59jFEghsHmJMvonalNfxPFLTvS0nPsx2Sp1Zl+3YkRK6jDGoHRN02zZ7K+ZzebHJMknTz7mn/6zf8aPPvgAN4zkF5dYpckyQ/SBbKJ0zufz47ZOCHGMBe67HsREQJ220QeA4OgcIZGeGMcRSJJaFyMSmeKSRCq4vbpd4/YeLwW2sNSzL1EXBhk9MQqa/Z4wOvrdltOTU0SU3N7ekWUGNzoQMQEI33gNh5QVmZf0fc/2fp22894TnUfoRBoNAZqmpxsiH9+1/PFf/Su+/9FLgrDUVY3MMoKUeKEpipphwmEplTzsmc1SdrobGdodTz/+Ee/84f8eZDZdoZ9nYfnlxgE8FaVktlwRxp6tUjTrG04vH7FYjXz84Uds1zdcnJ9xtjpj1zQMTcOiLqhLg9WW2y7gRrDK4n0KqBj8yKyqyPM8acgnJJa1lr7vj5VzKeHppx9jreXs8oKzs1NiCNxfv+T5p58yDB1nJ0uGrmW7b9jep4Xj+tUNZ5dXaGspZzVffvweTdez3jV0Y0eRZcznc+ZLy/Onz7h78ZSda+nub8BI9nfXZDKQ5xkqK5D6tZLwizp+BcW4gNRp0vk2TagsL9K5fNJiS1J2Vec3dNs7AoKsKPned7/DJ598hpWa09Ml0XnKoubi7AwlIu1+9xOwxvv7O2IMKbaYZP9zU073IfhuNpvhnGPftEifztUHVZ0QAi8kYwzgPVpCkNCPHW0f8AryKuPi/JT33pqTmxKZA4Pg7uY5SmWEILi7uaYo8qlvLynLjHiQ3E4a8df55B0xRsqqYuc2afspU9ppYrIlbn0/Bj59ueW7T27YxZK6mCVjhLSJla4ymiEyDAElFZlIeCklUz0gzywqOnZ3r4h+QMjUbP51xvJKQUrBLWv88oTRB0bvUSZjv9lwdn5Jt2/pmj2ZmXOyWFJXM+42G7SOFOWCvm/xfqBtPVoqlI44YNf0CdiAYrk6ZVbltPsdeZ7TdR11XSfL6jBMSS8J8rBYrbh6/Bar80ueffoxGs/99Qtmixl7Bx//+AMev/MeH3z/u8yXK6q6pNtvuXz4iJN5nfBbWUYYR15e39N1HW3Xsd3csipTUfX+5ae061csr95FWPubZkr8Z41ffqKLiJCRrLApeF5J+r4hzxckuXi60bzzDF1LXWTc36/5zre/zT/+x/+Y29s7VvWMuqqo8oIyzynzHD8OlGXJ9fU1wzCwXC6xNmO/32KNoRvSubsoMnA9Ukn2+32CQkyY4sMVeG25VHgR6d2IJCKMxCoDKtD6gRebDfZjxdXJCatZzen5DIBsUVH2AulGds2W2Xye6CXRk+dZ8iXHQBQcsdKQTCDjdLw4HGf6vgef/PDOdwQfafaeoXdJxmtKwqAJUSGCw4eAQyBMPnHgJyRxZtPxo+uwJn2fVkmazR1h7MAmCebrUumvdhyDAiNEISkXJyATtHJ/f0vfj2RFyfn5Oe1uw/p+Q1kXLJYLZvMrskyibEFV5Xz68cd0TQsxsm/WDJEUzVQ63DgSEGglqKoKKWUyDYWAFOB9jxQW5waePH1Gdrehni1YnFzxu1cPkb7jsw9/SLPfwnrHYjZjNa+pypKbu3v2Y08hFa9cJK9q5osl6/WGpu+43zTkec5n2y2ndU0MDjcMdNt7nn78Yy7e+wN0DsmX8Wt5m39l4xea6G86nMaJz6anDOi+3RORZHmCKCS7XiKdBKHY7RtGF/nWf/xL/sOffwvvA4VOxaZZPaOoa+73e4Ib8ePI4CK7dsOrm/skZVUSYTRts8FkGU3T0o/9cevsvU/ndO+JJLvggeEtpcQL0D5VyrWS9GPKKgsxaeLaIfLs1T0395fkVU1VlYQ4ktUzut0dps6RvidET1FlKJXA/1bpRI6JSTXmIwipplXK4PyAzXKapmMcPSHA0HnatufFqw3X2wFkzsk8Z7zvEHFgFAohDFZoGNwU6ABBGzwpU84JRWlyGLsp7SVHCHO4UL9+NaYQ6fgkBMVsic0rTFYzjIH13R2zxZyT1Yzb+y1t39C4gZPliqIvKbKaWVXj+wR8HPqB6+sbwgib+y25SYmy7b4DD8MQuHpwgWo6bFmwafc0Xcs4Nmx2PTe3OzbbBqUlRZnzu7/zNd5+dMXF21+hKnLW62vmJys++ehjTlcrTnKNj4HrZ59y9+oFVT3jyRg5Ob+gXJywLEtC8Lz/tffZ3V8zbNa4fUdZ5+zu79hvb5lViwQs/QLKXt8cv/CKfqg0SqXZbzdUZZESRGOcbJsd2tjk7ybZJ+erU+5ePuV7H/yQf/Nv/33yn/cDbd6yXC6JQrBtGu7v7/FDiumJMaZK9RR7M05b8QBJvCJSnaBt28m0kpRTRusE3p+KcMlXnWyelbQIAW3X4V36N0JZCBLnPNum4eXdHUVhGJqWk2VFnlvOTh8Rxpb7p5+QWUvE0XQtxkoQkhgTDcdHGHwgt0VyjUk1wSsNxmRsdxv6piUMI/0YwZRsu4Ztv2VVVfjRMXiIUpFlGYuqIsuyxJPLcxCR0Td0YyBKk87hUaCkYTY/RYjXl/W1qeXXMcTrX4JACIk0inp1gRKCsd1z/+JTjJHUUTLcOYZxZN80GG0ILlBkFXU9p67h9vY25do1I9HDzasbFosF1lru2i3KKLKqYn5ySjuOCKPIyxo6h9oHun3P9bMbbAZdafhW3/LxhwtCCHz1q1/h5KTirXe/xKKq+ezjj7AE6pMl27yh6wZuX70gz0qunznMuiErMrLCYLO0E2wHR9g3nLoZu82a25vnzK7e4gugJP9Pjl/4FXqfuGjWaKq6pt1vKcv86OAZ+u6YR6WUOrZG/vR//VP+h//h/8HTpy9YrU64u7s/brkParqDjrxvu6Mf/SB79LxOYIH0wOn6nmHidRVFQVmWCKmY4uaPrxVEQikLMNZSFSVu5tjtkh/ZKIGUyfa53rU8efIp7z664nRVHy2zQ+g5Oztlv9vQ9QmtDHKyxCp8SF/P6KS7Z3LUHbhy6fsLrLcpSXQYoXUKJwru1tcUueK0XtC0PTEK6sxOR5SCYRhSUKBJYY7jkOoSbduwzAQ2M5Rl+RuJ5T3uXSMYa1DLJe++/zV+HEaG/ZYsE4y9Ay+52b+kqkqadoc81dR1fayjGGMZakeWGXa7HUWRvv9x6AkxcH19zehm1HXFzfUaIcG7yGazJ3jHajXDh56qKpnNZumoBHz44Ue8us7JlOQr777DN37/D7l9+ZK7+2u0lhgjqao86TBEYPQDsfP0fSSGkdIaZlfnbG8CQ99i44LnT57w8L3fRVX5T8i7v4jjF966H27cruvI8yRAaLYbiiJLKCcRCWOf2kBZ4p89/+wT/u2//bfc3t6mVdZIFos5+/2Ou7s71uv1JCR5nX92WM0P47A9f/P31lqKsviJfxtiJIZA/8aDQmtNUruDEZLMWGSWU2YZw9gjoyJTGhciN/dbzKIgL3L6vufktKTrOrSUjKOj73u8dxzSP0KMMNkonZ+gikIQYkh46gORVqYo46Yd8aNn23pe7SLP7ju2HTT9Fq0tlycrfN+DGwjBHjsNWifstQsgREq0qeqCOktpK1L+eqrs/6lxbC/JxONX1lIslpw9eofnnz7B6o6zqwds7+5ww8jYjhBhNwFCpJQpCUUIqjJtvcdxdbyeM58imJRSBB+JQRCjIrjAy5evUhvPKvIiw4ec09NVou+OB+GSgWiwRcWr+x1jhOL0jNa14IeUi05DWdYIZZDVkug9wo80uw2b+1SYMzKy3W6ReUl88Zyh2ZNXq9/AO/5fNn6prbueggR2ux1VmZMXOV2zAynQKslHjdaMU0TP+v6ep08/S6vzRI3J8yK1Kd4oYnVdh4+B3o2JGJNZlJJobcitxTt/XNUPrTTn3ZFIc9jmo+yRqHp4MLlhSCQblfBPWZahtGS7u2XoA3qa6EOAsqpT/M5uIMaG01VF13dE5xI+KEiyTKUghZgoLj4EQoSqLAkIuqZDSTmdy8OEyZK0rWO3b2m95sV9z9Pbhk3fU2cG7m4hDDw8P0VIwzAMKXTAJCyWGx0+ksInQ+pACBkp85LVajVZJT+/cZjk6eolpHIQApkXLC8foPKcze0LotXkdUm72dDvd7i+Z7PZcHl5yd3d3bE/Po4DeW6o6wJgCmRMegbvQQpF8ClEo+0azk4vCDEwn88maXE4bvkP95SUmoAkKyuWJ0v6oUFLw8WDS66ffcIsr1KarbYsTi+47xyFrfBdS3N3TehSCEiUnhhcEnNtNri25dcuWPgVjF9ooh9Xlq5Da0VRFHRNQ1FkFPWMdrej71qKsiROueGDG1mv1xzeEO8DMTpAYK0hz/Nje6qqqiSO2W6oqxptDMPQJ5SxS8BGSP3xYRhw3jM6N33scKPDZhnR8/phMKYzf2Y0RBhHh7WBWV3TNPv0b3QqCAY/MI6e7b7hxctXvP34khjTmT7PNLrIcX4gkwluIGVESoMQGkWCJABpgmqJloquH3DjmPrPUjCMI5t9z94nzf2m8+wnqa2QHu5vsDrw1qN3yaJGKoFzA+MYMDan2zUIJckzQ54bhBzIcst8tSIerKqvf/pcx8QHAqnIqhm2KJgta+rFgmZ9z/b2hruXryhjoNntKKqKu/s1/TAyDCNCJHVlO+GfYgg0bcdsvpjgjkmvEZE4B0VRUlZFYv8nDO8kIxYpXlkqpFAIadBWUy/mrOwZTdtgBSxWS3brLTZL02GzXTM/vaDfN9zf3WKNpq4KnMiR9EQ5oqXAZNmvSaXwqx+/1GEuz1Nv02hJludstlvq2Yx8tmS3u0+TP6sZnSDmM84fv0NdL4jhepJvjgiRhB9KyUTnnM7oYfDQRap5gRsd4zadw0dcwjBPMtdxHHEhpoD60Sc/ekotBD8eX6sxSY88BJcKV9FSa0nXd3T9iLALALq+42RekinBZttyMq+4vd1RXi0pqiUmh9AGxnab+q3ep3QZFxl9Qh9JIRnGEaUlSivi6LFG4vDgBha1pq4tHz3bctt77rsBLwKajNELdqmmx6v9hvnLj3l4fkoUhl4aZDGnH0RyxymZHHUugBSYQpPNZkSRggiIHvU5FoqSiOZw46eHnVQalMEIQX5VMq6uuKlfocoT9vcv0VlOUVYUsz1d04HwaCkhKJTMCUEy9uCipWkgRMOr63TEq+qarC6Tx6LI6do25Z5VNcZmxBiZzWbJIx4jeZZgm1FK0BaFYQiG4kTQDz3Cj0QpqJcLlJI0rkNZiVcZdXmO6xtyYSlPS0aRsc8yRFHwRV/N4ZeY6IftWlkWdG1DCIGyrGh2e6r5jNlixf5+Q9v3SG0Zuw4l1RsMuKQMc25EyECWp+ictm3TytwnkMMwjpNooSfGQO9TUcY5d2yZuWEgioibVu8sS5P6sJoDx7ADZCREz+DGCRSZUlaNj4x9S13n3N1cYxWIVclumzMzAqPPplz2iDaWspoxdi3WJi6dDymY0Zh0XDiwy4ZxTLw5kQqBfkxuuPPzmqvbBm4HDLDUlt3oaXuHQXNRzricWc5nhnkWsbOMbS/Y9QNDAKUkUUqsSV0FrSXlfElWzZloEbzhTP+Fb5Bf9L74iRFTC05bhTI5D4qSxckZ25slzeYePzguXGS/2dF1DYMbcWNyKxqTQiC983QxkBU5pTFordDWUtvseIybzedJmViWFGWJMenIZ21GCJ4QfDryRJHIurbA2BUZJwhg/eIJKZx2QJmSk5MTZrMZXdfRNHuyWYmJI77f4zCszi4pymraOH2xJ/svOdFTKkhRlrhxTKC+LKPdJwRQvVzR7Hbsdluk1nz20UcM/fAT5/HlcgViPJ6h5YTgbbueGGDftekLTpBHKSXBJ1bXoVCXFGbhWDc4VFqBI9frUMxCRmxmsMbgnadtG2KEXdMm2mvoyXXkrUcPmZWaIk8Qx2a3YbZIlfRCa6wpwEe0jAgRscbCFNwYY0zHma5LevcIMkQIMXHmxoFSB95/e86XHhgEGW3vuG0bbu4bmtZRmYxFrjmfGb7y3kPsbMZ9G3i1Dry8abnddtiiIPiBptlTIMnnp9j5afrGp2CHL8bpUYDUHB480iiquSGzhn1V0+12CCRVlrPZrhnF1FKdiqjee8LgqGZzirKcug2SGCJWJtSymPQSIQTmdTruOTcyjIHN/T3OO4rZjOXJGUpbTF6AUAhryayiLOcIodhdf5bSedSIUpqiKJL3va4TBHTsifUSPwrOH7+LNtkX5D3+m8cvta9LE0cmj7ZSFGUKupMiucqyssCWJZWAu5ev+PhHP6RpW7TWFHlO2yY0srFJNrrdbo/mEyEFw+hoh/5YfEtI3Xg8cwNkWQbK43w8VuPfXMXfLMRprREK8kmLHoEQEr2V4Al+wI+CLC9Tesro6Zseb0FEz9A2VFmZkkIyEGHqLPhUYDt8naIoEiVldAlDHCMiQhw9KgoYPLkS1CclwxggSvpeUxnFeblgvetodw3G7anKS/b9jkFH3vrS13ko5vzLP/kWfr1L3n8RyU0SK50/egdZzNPqEhMOOsCvwbv2C4wjEGM6wyvQhSQn9f/7fUMYOoJzSbkoJcW0WscISg8sFgu01oQsnwgz4Lo+GZvaNvkqlKJvG9Z3Hbe3t+z2O4q84OzigqqeU5Q1eVlh8xKTF0Spcd5jqzkXUTIMnubuFfQDUvnX7eIheeIDBplVrC7OuHrnK0jzxbWmvjl+4WJcGvG4SWRqg2RZhvOBZj+w3TdUs5KyLhl3GUPbopSkrCqMztC6RYikbz70qfthSFuxEBKSeeiRIokx/BtyzoOJwHmPFBKtxdTy8sfJfXjSw2SdNQaT6cQK1wYlJPvdnrIoOD87BT+jyjSrKmfsOwYi86xAS0HX7GmySBADoSiToSOQinBKgRT0UzhA0zRToVIjgTLP2d1tIAT86FBeY2SCYcwWBaiCVy/u4WaH8ILz1Yw4lxg5Mj8pGYWgrGqK+YLdkNGOY+o3O482qbaxXC1Znj8kHsUyb/oKf7Mj/sxtbSRKjbIlXvdkecGwW9M1Dfd368lpOFLkedqC5wXDrqEPkTzPJs6gOB7flFIME+N9t7mn77tJcAVj1/HW228zX55QVDXK2CmvLwUxBq3xEeqLd3iM4MO/+jNcu0FO+Gg3dVlGHykXp6yu3uL00Zco5idJrPQF37bDr0TSk6qrQiYXWdoqS4rC03QD3XaP0J7dy4+xIgGRezfgwojNFJm2U9zuSNvuabqetk/YoEO+FSr1vqNIueLOOaKIU8ywRClD9P4YNnjoux9DAievcEpykSQoczoi5EWygb549ZxcG5xRqLFjNTPMrcX4ARnGFAEVHX4QYCxBBCCgshwlLYP3aOkRStL3GzKbI2XqKIzOg0ixzE3Xvm6JCVAyqfGij6ANMo5UJlIuK7JcUp2tOHv8LrOTS5pBs77ZT6miDmlzVjNLLVvqes7i8vHxOiCSLPOL7LcQJLSWzAtUWSIyw67b8+STJ8QYybKcuq6m+opmNp8z9CmtZRwHlNZTwms27RBbuq5jvb6nrivmqyXaWrKi4PTBJflsQV4kMZVU061/TOQBpGV++TbvKcPTH/0Vr16+ZDaf4fqeICRlveTy8bsszy7Jqlli+/2WjF/ylU4iiTekkEpJIhEjBiqZs7vbcr97xSc/+itwLYdElrIukS4gXaQbYegdbTcwTJngIqbdgpCCru+PMtZ+TAYVpEJPlVU/OdwOEz2EkEg3ky89hHAUZXRdj1SKqFLrrSpy3DiwXC2xQuP3O4xSWA3zUnOxqLm8OqWoLXmhCMHRN3uyXIFOry8IjcmL9PHYkeUlBIdWGqQk4LBFzt2rGwY3IkKgWW/RnWAZltSzUx4+fMhuCOi+Z17VlLOc6mTG/MFDZqeXDE4zDpoPP/iU3XqP96Swh8Fji5GzB4+w9QkgkqtsurTyC7DY/LyXIEiSZGUtsijAaqpFzcefPsHaLKkBfdolaSEY+za5GefzYzF22O+4ffEcpRTL5ZLCWhoB6/t7Ti7OOb285PTyksX5Bdrm9KNnNiuPD/+Ez2YSNAHaUp8/5L2qonr+HCUVQkqKIkfmNUU1TwEh8rdjJT+MX4F77WdVWVPWt9KaxckpezqktmgVWVaWptM4F8iMoSgs7c3mKApRRALQdx1yKrDEmLTsB8tqlmXH89jrBBb3U4ks7nguN8YcGXZ5XmAnnlmVJ0FFURZ4N3Lz6gU5UD884eKs5uSkYLWqCTLQjynNwyhBoQ1hHFBSIwVIlQhy3qeb71CcUSptPwVp5S6rkrXShABttydTgNZEK7B5wfLsIdvbO8grytNzlldn1GcP6J1itx/53vc+5rvf+RFERWahXMyZ546TkyWX730VU8+PsdPp0vw23IjJt5/ZdE2rsqIuqtRm7QfWt/cIYLmc00/1nWP443R/GGN4/vw53nvKsmS2mFMJEFJS1QtOzx6wWJ4jbUnfD2kn9wbjTfyUy08qg6lWXLxVAmI6GkhCFMcUoN+28evbewidtkcCZqtTvv67f4dmt6POnqJCxAWRrJQyYKyhqkraYSAMHX07HkU5zjmapgE4GjsO/fPDZAeOFz3lZvvjv0+tp/RrMuKkyCdjNCEE1vf3qScdHbnRXK2WLOoSLeBuvcbkGiMjVa4pcoXreoJssbkik8mtV5QWm2f4qBj6hiJPCkHnPT6EFNes5FEQdH1zzTiO6KpgkIoyLxl1RuNaZLGiPLmkOL1EzBa0cUbXB/7quz/mO3/1Ac5FcqvIC4n0KfhxfnrK6TtfBfPFBhT+vJFqLIoiLyiKgtPVivV6M7EFk8R5HEZiDEcISXpo58frfnp6evz/lNE8ePiAk4sHnF0+op6fokwBItUzDovCm5P2pynFUSpMXv5ERf23Z6P+18ev57WLJJ0Icdo6KoPNC6rSsig1Vkk8mizLiXGgKEqG0eNjJK9Kts2nR4DDfr9PJhGToP7DMBzTMLMso65rttvtUfp6aNsd2m+HLTswyV1NgiUG8K5HG8NyXjMvLXVWsMxzYmipyjnr3cDL24YqNwydYycCmYqYhcKPDjKJlhElUj02RhIVJzOI4OmnON0YAsP02nb7HUoFTi9OuHjrAfnyBFWsePLZHXe7kZPFKWZ2gagv6FROcJq7+zu+/d0PuL25QSuF95G2GanrksVsydtfeo/y7AovJFp8sVI8/3OHzXKMNYzDgJapWFrYjLKqkFIkTLZJt+tBv35ove33e6qqoq4TCLI+m5MVGWVds1idkhWz1EqbUGeH9u7ftDL/vNrGb+NqDr+EqeXnDTH1Tw5/I0nABVEqlIhcna345EVDv+6RUlAWJbvtlr/4i7+gHXpOL84oZzOa3Z6+T5N3GEbW6w3jkOKOD9txKSWLxeIob40hRR8pJZP8sSjSOV8IpJAT1sowjOn/9f1AmaVC3n67RjvHumu4WJVsNlvawdN7z/p2y4PTJbPcsNltEW5gdVLQ64iQhixboITEWEVwETf26dwnYDwYaqI4xj1VteHiwQnVcg5ZTTtqPn16z4uXdwRvWZ1DLXKCyNist/z5f/gWL18lummZG4pMYYzi9GTOxdUZD979EiIrJgD1b8c4UAZf/xwx2hyTUauypKxKpJCUZYm2qX17iCh2bpyESY6qKimKPJFhlcKNLuXMZwU2L5HavPFV/9PYp/QnP+vd/CKXNv/m8Quv6D9vsqdzdCT4/jXGaGzYbbaM3ci8yHn78QXe3CXPOpoYXYIs9h2vXt1wZQv63hNDwPlI2/SMoydGic0SkPBwxtput1itaMI4RSkpcmOn8ICMzGbYzBJDnM5hAUmkDyCFIQ6OoghcnC4o8oRJHmLk+XogjI5FrYkBnI+8vL3DKjBIcuuoCpuq5lGSvm1HHAfi0CHCgIpj0vNriYyRPFOczkp0aSlXJ8RsAdmKl0/uuL/eU0RNLhUxeLrthm4T+PTjz3j1ySdkUlHOCkQI4KDIJEr0FFen5G+9jdL6i9Ev/88e4rUmP/oj/y7LS2xu6YaO0ad+useTaYOQMXkLVKoBDSPkhSUERZ5ntN0+3RdB4geQukLILNWMiEfi0E+Hi/yMlzZ1Z/72jF/KvfbT4/WbF1NlG4FAIGVOPV9SVDnt7o6r8wWth2fPbtmse4q8oKpKds3EZY9gM8vYD+DAmBSKIARkmT2CAheLBfv9nuh94suHAEpN0klNkSdDQzYJL4ZhoB+6ySCT4JVSSvIsYz6bsdsl+KTRhtFFcpvT9yNaJ+WcFJG+6/CNQwjLfFmSo4ikvHNILTTvRkQMCRflRrRKGeBRQlHX5PMKYXLQOetty9PPXpDbgqurMy4fPcJWNdvtjg8+/DE//P4PaXc7pAAnAlWRU1hBnQuWyzlvv/8N7PwCjzoCG397xlGFgZAaXc45Ob88dk8OEmbvk0rOBI+Ugr4fJxZfouhqnURWh8JtUZUsVyvmiyXamrS1ij95v/7NW3DxxZe6/ReOX3ii/81hcpFIIJJabdFLopAEAkIMaCKnVU44u+DJZy8pSkVVVpRlh4vJsy1IIhfn3NG+KIRgNiuo6oqzs7Pj5/COrt3Tdd3xFRwUVUeNO0yJLnFy0x1Y7ykppu1H8rKmbVrutzsym+ECOB/oR4fWAi0jMSRsVh80XS/J+wimB7kHCb5rcH2L9AOKkAREMRKVROUZdlaiipqoKwYHP/7oE3784w85nV8SjOX6fsP1h5/w2YsXPH/xirHvyZQkyw25hUx7lBip6xmPv/Qey6svg5oTUNNU/+0Z4o2PIhJhcmanlxRlSbi+xhgz4bMjUqbt9uEaxxix1mKtPdqTrbWEGNHGEKVAWYPQr9toP/k1/+sav6Qy7mcHK6ZPqUR+jiKx02xGVtQED/u7G8JoWc5Pad05w9jxjW9+A/mDH9ENI15IjFJolVbu/T4FJWaZpZ6VnJysku9aSrLMsrm7Q0l13M4rlSq41ubHFtwhSWNsB0Y3Akk5V85LQohcX9+RmPQpD60fHd4HZIxkVtCNnouzJTE4ciVACdpeUfQRlTvG/QYpBGO3J/QNYWzREnRepQJj31KVObrM8TrH5Av8AE0zYk0OEX7w0Ue8ePmK27t7+t6jlGFWZClOWgu0DGRZYFZnXL77Fl/7w7/P7PxLRFGgAPlbdDtPTonpdzJp4aNmtjpPrrSp4p7ur0jTtHRdm87rUwRSCIHtdkuWZUdFYlVVSC1ZnZ6Slfnkjv/tLaL9qsYvXXX/mW/gpCM/iDCjUJisRKqC4DQ6wtCu2ew7ViePGYac88sLsqLi5c0tu6ZLggiZVuK2TcaWoiiwmeLBgyvquubm5oa7247tdos2mkxlx3ZLhKSjn1pwBya4Pxolkv7cOcd+PyJVQkdrY2j7pKM3UpIbhRCWxbzGucByuaBrGpQtsNkM7yJd22DLHO8jQ99iUkkfpRKU0of0NbOyYK0EQWpQBTZXzBcnfBZe8sknn3Lbdwyjw/tIWdZYm7EocvAtmVGsFjllKalmBVfvf42Td75KMIlUq0jadhHlb8M8B9I6DklIHZFEAUU1YzabHy3LkJyOXdceW6KbzYbFYnHspbdtS1VVlGVJnufMFguqWY22NpXU/vbtxP+Lx6+tNShIZorJr0RQOcIWDDHQBui94P5+TTtqTlcXGCH5nfe/zKPHD7nZrOlaR54lwYJzqTc+m80gOrLMJjtj09BsN2RKU5Qzejem3rWPjG4kU5IyLyhnNZvthk2zo+1HvI+EoWc2K5mVGZmCZt8To2a773BTH14qRZ4ZtqOj8YHT5ZxN77mc1/ioudt2bHY9p+c1QowYGZFjz9Alfhkx4k2DNRWzuiZEQdQ5ulowpJolcUwxTMwKyDX7fUNdJoYaEeo6UJqSOsuZF5Ys97z7/ns8+NrfR+ZnvOkA/+27mcVPfSSQ2lCfnCPUD5B+wCgJIqImDcXQ9RAiXZMEVDbLiDoQg0dKg9KSoHN0uUII/UbN4rerevGrHr+Wif7XbzyB0AWqKBkEfHp9x81dy24fMNuI6OHi4QMUkUcPLrh4eA7CkmXJ65vyw1PGlwiO+9sbbu9vUWHgwWo+QfdLNs2Ol9eviEJQliWVTaDE/X7H9d0tbd/jXST6gJVpFXSuww+BZoiTFn2kGweEUpgsYzM0EAPrtue+GSiMJn/XYGzOzfWaeZXRPm85mQdmNuCaBs2YzoZKIbQgxkCmLc4JhMrRNkdry/5+y6ouGE9rlpVl1g0Ye0FdVXz29ClSCgqrqK1GR4/WgcvHj/n6H/4Dlo9+B1SepMJC8jpf7bdpuh/EKq9hTFIp8tkqyZvbJAhCClyAcRiOBdRmvz+KoQ5HtkBEWUMxP8UUc14/BN/8+b/O8Wtd0eF1EURKSRSGJ59e8+zlmmcv7uhHQVXOGYcRrwRfPf06ZZEmbDWzOJdQQtZorE5n9dsXL3j1/DmMPbNMUy5KpMpZ7zpOlwtms4rRJ2acDJqb21te3d4wjANt2ybOekyedCEku6YjBE87Cgbv6d04mWfS9l9JgyTSuYDfNjCv+fDVKwaliV5x8zL9n/mTaxaq4/JEc3aSkRuN1AlppLVFK4ufTDaKSNdu6fZ39M0tq4VmQ0s5W1KUFcF7wvkyYZNEQZ1JRLanvpjxzh/8Eav3/ghl8zfaRW++47+d4/jqpaKazdE2I4wW58eJopOMSgda7IE7WNd10lVkOcIY0DmLxckUmpFEMb/d78yvZnyOqr7I7V3Djz+54eVdg5cZ7djTb3eMfiQaxe12zftf+xrvfOldZkWBVEmv7MYRI3OMhJl+xPlqQRgH3NgxDh3bbUck2USlimRCs9nuuF8nDX0KXEw6dBU8ioiRMq2EyuADdM7hQkAaS1YWKGMIQRBcQChBnlsyrXAEtkPkycs7ZFSIkLDUZ2ZkdllQ1XO0iWRVhiqyVGiTBoHEO4dzcHdziw+SdrMm19C1e0oLIyO59uy6PYWJqCg4rebUlSE/PeHsy1/h0e/8PWR9dZzkf/uGoFosQWmu79YoEVEmO8ZZvxlPHEMg+hS1pYxF2pL65JzTi4vfWk36r2t8LhM92UVhs+vpBs1s9YAsL7nf7Li9u+V+t8YWGe2UrvqD732P97/+Va4eXGGzDKOTXHZWzclPK/q2ZXN/S9ds2W3W6M6TZwGtJaFxdG4idk6RRQBKKvpxRPiRTCuYMtxSa81BgCIrKeqK9XZL348EaVAqTfh+0yBi4J3HDxEy8upmzW59j5aCqsi5uipYnRfMT0vmlUJaQZAqASO1xdiccbMmBtiuG/a7HuF6jPBYIWnHFh8dw95jJWSFJF8tKWuDNpazR+/wzlf/AeXqMV5qNF/8GKBfdFSzBdoWDN6nNFmZqj2H4lvfp/TczFqs0QgpcFHw4OoRb3/ld7BF+YVHO33e43Nb0WOM9L2jmp1gi4KPPvmUZy9eIGSivu7bjnld0zUtYz/gnOfm5p7T01OKvKCsSrI8xxYOazTSFhgEWZCks9g9bd8hCPRNS9u2eM8xk3x0YwJYAEVmkVoxjB4iaJuzWsw5Pz9HGsW3v/OdBJmUntFDkWeYrGB9d8Ptesfj03Nur58gfEM9L3h8NefRo5zT85ysBHRgcAFTZBibgdTJEWVzhn7Di6evGLqAxmOkx6qIkpbCCAgDIUbOLy4w1pItM+rVBe985e9SXX6daOqUTvO3YLv+M4eAoqp5+90vcfPsCUOzx6hUNk/BnUkH4X1AFQk8Wc1XnD16m3e+/g3K+eq42/lP6dn/axqf20SXUjKb1WTW8NWvfZV937Pre27u7hhbx7yuGKd+arNvMVnLi5cvaNqG1WpF2ZbJbqo11pjpYjukEEgl8MHRDz1tP7Dbd/SDpx0D0hh0DEjnkuNNCrKiwHkQWqJMmox/8Ht/l7NVzfNnn9Ls7tkMnhAT2IKTK8Rsxrtffp92u+aubdA68PbpjIergq++dcZX3l6ynEW0jThGZJaRFRXCFDgpGJREFwVESfCJDBOC5HbfMJ/PKIwhY8TmCjvLyRYLsmpJdfqAh1/5BtXDL0NWEcRvl9D1Fxpa8tb7X+Xb3/oPbDcbJF2Kjo6glUpFWUCXK5Zf+QZf+Z3f4ew8PRjT6v/XHWn/tY/PZaIf3vDVaklZFHz5vfd4fnPLfdPSjY4nn3zEft9hHhhmeUaz27Fv9jiS4qnrOk5PTxnHkWLyHx/shkopokt99/V6jXMBIWTyt0uTNOghpBgmJcknX3oInrKo2OwbtMn42te+Tq5ht7lDKZ2UWFGhpCEGRRgFWmjC4HByy1ffe8Dfe/+C8xpW84J5pRAiSWyzIkMoA0IhtSLPS6QpiMERkYTgQEi2u20KttissScnlLMKVMQUNfn8hPNHX+b8S79Pcf4WQmgiZhLGvFGm/ls4hICrR4/45h/8AX85dmxuXiJdRHlJh2O2WnD16CFf+fo3efvrf8BsPkfIn9IF/m+T/CfG57p1XywWzGYzbJZRFgVFnlNWFavTK05XC9brW6IfyaqctuuIUhwljtfX1ygp2XrPYj5nu90e+XDz0qbtHUwxSWLyrLep4BY9Rkn8GMlsor/GGHE+rfJ1PePy8gH4nqqs0TpDjSM+RE7PHpCVc4SIfPbhxyjfcHqZ8433vsbvfvWSSrfE2Cbr7egRgDEZ2hRkWQlKgTQEkaGMpZrVSBkZuhajBDFAWeZUZYbQinxeMju/4vTx+zz48u9jTt4FmU8qQ1JoI3FqC/8tvZkF2CL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" \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "\n" ], "text/plain": [ - "
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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -2769,20 +2761,20 @@ }, { "cell_type": "code", - "execution_count": 199, + "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Tensor(shape=[1, 4, 6], dtype=Float32, value=\n", - "[[[ 0.00000000e+00, 8.99999976e-01, 1.00000009e-01, 7.99999833e-02, 5.19999981e-01, 9.20000017e-01],\n", - " [ 1.00000000e+00, 8.99999976e-01, 5.50000072e-01, 2.00000018e-01, 8.99999976e-01, 8.79999995e-01],\n", - " [-1.00000000e+00, 8.00000012e-01, 7.99999833e-02, 1.99999988e-01, 5.60000002e-01, 9.49999988e-01],\n", - " [-1.00000000e+00, 6.99999988e-01, 1.49999991e-01, 3.00000012e-01, 6.20000005e-01, 9.10000026e-01]]])" + "[[[ 8.99999976e-01, 1.00000000e+00, 5.50000072e-01, 2.00000018e-01, 8.99999976e-01, 8.79999995e-01],\n", + " [-1.00000000e+00, 1.00000000e+00, 1.00000009e-01, 7.99999833e-02, 5.19999981e-01, 9.20000017e-01],\n", + " [-1.00000000e+00, 1.00000000e+00, 7.99999833e-02, 1.99999988e-01, 5.60000002e-01, 9.49999988e-01],\n", + " [-1.00000000e+00, 1.00000000e+00, 1.49999991e-01, 3.00000012e-01, 6.20000005e-01, 9.10000026e-01]]])" ] }, - "execution_count": 199, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -2797,7 +2789,7 @@ }, { "cell_type": "code", - "execution_count": 201, + "execution_count": 40, "metadata": {}, "outputs": [ { @@ -2806,16 +2798,16 @@ "\n", "\n", - "\n", + "\n", " \n", " \n", " \n", " \n", - " 2023-02-17T22:36:59.843246\n", + " 2025-12-21T09:06:41.065085\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.5.3, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -2826,60 +2818,50 @@ " \n", " \n", " \n", - " \n", + "\" style=\"fill: #ffffff\"/>\n", " \n", " \n", " \n", - " \n", " \n", - " \n", + " \n", " \n", + 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\" id=\"image8086e1f869\" transform=\"scale(1 -1) translate(0 -138.96)\" x=\"33.2875\" y=\"-10.515689\" width=\"180\" height=\"138.96\"/>\n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + "\" clip-path=\"url(#p516e55e87d)\" style=\"fill: none; stroke: #0000ff; stroke-width: 2; stroke-linejoin: miter\"/>\n", " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3054,12 +3036,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3100,12 +3082,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3164,12 +3146,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", + " \n", + " \n", + " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", " \n", " \n", - " \n", - " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", - " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "\n" ], "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -3505,9 +3358,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -3519,7 +3372,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.11" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_13_computer-vision/8.rcnn.ipynb b/chapter_13_computer-vision/8.rcnn.ipynb index a6886f3..c56b307 100644 --- a/chapter_13_computer-vision/8.rcnn.ipynb +++ b/chapter_13_computer-vision/8.rcnn.ipynb @@ -2,10 +2,18 @@ "cells": [ { "cell_type": "code", - "execution_count": 17, + "execution_count": 1, "id": "6e520417", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(179467,ffffbca4b640,python):2025-12-21-09:12:12.251.995 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n", + "[WARNING] DEVICE(179467,fffe8926f120,python):2025-12-21-09:12:18.575.029 [mindspore/ccsrc/plugin/ascend/res_manager/mem_manager/ascend_memory_adapter.cc:127] Initialize] Free memory size is less than half of total memory size.Device 0 Device MOC total size:65464696832 Device MOC free size:3994501120 may be other processes occupying this card, check as: ps -ef|grep python\n" + ] + }, { "data": { "text/plain": [ @@ -16,7 +24,7 @@ " [ 1.20000000e+01, 1.30000000e+01, 1.40000000e+01, 1.50000000e+01]]]])" ] }, - "execution_count": 17, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } @@ -24,17 +32,18 @@ "source": [ "import numpy as np\n", "import mindspore\n", - "import mindspore.ops as ops\n", - "from mindspore.ops.operations.nn_ops import PSROIPooling\n", + "from mindspore import mint\n", + "import sys\n", + "sys.path.insert(0, \"..\")\n", "from d2l import mindspore as d2l\n", "\n", - "X = ops.arange(16, dtype=mindspore.float32).reshape(1, 1, 4, 4)\n", + "X = mint.arange(16, dtype=mindspore.float32).reshape(1, 1, 4, 4)\n", "X" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 2, "id": "8beab150", "metadata": {}, "outputs": [], @@ -44,40 +53,10 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 3, "id": "1618e091-3293-442a-8241-a9bddbf45619", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0 1 0 1\n", - "[[[0. 1.]\n", - " [4. 5.]]]\n", - "0 1 1 2\n", - "[[[1. 2.]\n", - " [5. 6.]]]\n", - "1 2 0 1\n", - "[[[4. 5.]\n", - " [8. 9.]]]\n", - "1 2 1 2\n", - "[[[ 5. 6.]\n", - " [ 9. 10.]]]\n", - "0 1 0 1\n", - "[[[4. 5.]\n", - " [8. 9.]]]\n", - "0 1 2 3\n", - "[[[ 6. 7.]\n", - " [10. 11.]]]\n", - "1 2 0 1\n", - "[[[ 8. 9.]\n", - " [12. 13.]]]\n", - "1 2 2 3\n", - "[[[10. 11.]\n", - " [14. 15.]]]\n" - ] - }, { "data": { "text/plain": [ @@ -89,9 +68,39 @@ " [13., 15.]]]])" ] }, - "execution_count": 20, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "[ERROR] TBE Subprocess[task_distribute] raise error[], main process disappeared!\n", + "Exception in thread Thread-5:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python3.10.14/lib/python3.10/threading.py\", line 1016, in _bootstrap_inner\n", + " self.run()\n", + " File \"/usr/local/Ascend/ascend-toolkit/latest/python/site-packages/tbe/common/repository_manager/utils/multiprocess_util.py\", line 91, in run\n", + " key, func, args, kwargs = self.task_q.get(timeout=TIMEOUT)\n", + " File \"\", line 2, in get\n", + " File \"/usr/local/python3.10.14/lib/python3.10/multiprocessing/managers.py\", line 818, in _callmethod\n", + " kind, result = conn.recv()\n", + " File \"/usr/local/python3.10.14/lib/python3.10/multiprocessing/connection.py\", line 250, in recv\n", + " buf = self._recv_bytes()\n", + " File \"/usr/local/python3.10.14/lib/python3.10/multiprocessing/connection.py\", line 414, in _recv_bytes\n", + " buf = self._recv(4)\n", + " File \"/usr/local/python3.10.14/lib/python3.10/multiprocessing/connection.py\", line 383, in _recv\n", + " raise EOFError\n", + "EOFError\n" + ] } ], "source": [ @@ -110,9 +119,9 @@ ], "metadata": { "kernelspec": { - "display_name": "MindSpore", + "display_name": "Python 3.10", "language": "python", - "name": "mindspore" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -124,7 +133,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.10" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_14_natural_language_processing_pretraining/3_word2vec_pretrianing.ipynb b/chapter_14_natural_language_processing_pretraining/3_word2vec_pretrianing.ipynb index 645fcf1..2b849b9 100644 --- a/chapter_14_natural_language_processing_pretraining/3_word2vec_pretrianing.ipynb +++ b/chapter_14_natural_language_processing_pretraining/3_word2vec_pretrianing.ipynb @@ -24,15 +24,23 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "3258694b-1c58-4d3e-85a4-0f3ae4719259", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(197548,ffff84ef5640,python):2025-12-21-10:05:19.780.457 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + } + ], "source": [ "import math\n", "import mindspore\n", "import mindspore.nn as nn\n", - "import mindspore.ops as ops\n", + "from mindspore import mint\n", "from d2l import mindspore as d2l\n", "\n", "batch_size, max_window_size, num_noise_words = 512, 5, 5\n", @@ -92,12 +100,12 @@ "data": { "text/plain": [ "Tensor(shape=[2, 3, 4], dtype=Float32, value=\n", - "[[[-4.44511386e-07, 6.75162021e-03, -1.10750450e-02, -4.48313728e-03],\n", - " [-3.80617043e-04, -3.46304267e-04, -1.00970650e-02, 8.21283739e-03],\n", - " [-1.19789327e-02, -1.37363840e-02, -5.93600213e-04, -1.00296247e-03]],\n", - " [[ 4.71872091e-03, -4.49423585e-03, -3.06172739e-03, -2.19914801e-02],\n", - " [ 2.38259858e-03, 1.24084332e-03, -8.02362617e-03, -2.24583466e-02],\n", - " [ 5.16804680e-03, 1.11878654e-02, 1.04257055e-02, -1.67296249e-02]]])" + "[[[-7.96333328e-03, 2.65865191e-03, 1.43835917e-02, -1.00341868e-02],\n", + " [-1.77106056e-02, -7.02906074e-03, 8.66726879e-03, 2.01863307e-03],\n", + " [ 1.31345205e-02, -6.47115579e-04, -1.40717840e-02, 3.02668265e-03]],\n", + " [[ 1.45658001e-03, 9.94547829e-03, 4.08218220e-05, 1.05659962e-02],\n", + " [-1.17883114e-02, 1.14409463e-03, -1.30126020e-02, 8.69803037e-03],\n", + " [-1.24062533e-02, 1.45287684e-03, -4.32842690e-03, -1.05699692e-02]]])" ] }, "execution_count": 4, @@ -130,7 +138,7 @@ "def skip_gram(center, contexts_and_negatives, embed_v, embed_u):\n", " v = embed_v(center)\n", " u = embed_u(contexts_and_negatives)\n", - " pred = ops.bmm(v, u.permute(0, 2, 1))\n", + " pred = mint.bmm(v, u.permute(0, 2, 1))\n", " return pred" ] }, @@ -144,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "7918db00-e945-42d5-9071-f127a761f2d1", "metadata": {}, "outputs": [ @@ -154,14 +162,14 @@ "(2, 1, 4)" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "skip_gram(ops.ones((2, 1), mindspore.int64),\n", - " ops.ones((2, 4), mindspore.int64), embed, embed).shape" + "skip_gram(mint.ones((2, 1), dtype=mindspore.int64),\n", + " mint.ones((2, 4), dtype=mindspore.int64), embed, embed).shape" ] }, { @@ -180,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "070cb5df-4187-40e8-a57d-8ae122a2e7ce", "metadata": {}, "outputs": [], @@ -191,7 +199,7 @@ " super().__init__()\n", "\n", " def construct(self, inputs, target, mask=None):\n", - " out = ops.binary_cross_entropy_with_logits(\n", + " out = mint.nn.functional.binary_cross_entropy_with_logits(\n", " inputs, target, weight=mask, pos_weight=mask, reduction=\"none\") # pos_weight的取值\n", " return out.mean(axis=1)\n", "\n", @@ -208,17 +216,24 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "dd2ffd16-f63a-460c-9dd1-e5cfae4d50d9", "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "." + ] + }, { "data": { "text/plain": [ "Tensor(shape=[2], dtype=Float32, value= [ 9.35210109e-01, 1.84620929e+00])" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -240,7 +255,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "f2f30873-5715-4e6e-948f-7d201cec5f38", "metadata": {}, "outputs": [ @@ -273,7 +288,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "22a60bc1-376f-4da1-875e-2f7a02ca48d9", "metadata": {}, "outputs": [], @@ -297,7 +312,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, "id": "93898b1d-0439-4f24-9d73-77d2d1fc0280", "metadata": {}, "outputs": [], @@ -309,7 +324,7 @@ " if type(m) == nn.Embedding:\n", " m.embedding_table.set_data(initializer('xavier_uniform', m.embedding_table.shape, m.embedding_table.dtype))\n", " net.apply(init_weights)\n", - " optimizer = nn.Adam(params=net.trainable_params(), lr=lr)\n", + " optimizer = nn.Adam(params=net.trainable_params(), learning_rate=lr)\n", " animator = d2l.Animator(xlabel='epoch', ylabel='loss',\n", " xlim=[1, num_epochs])\n", " # 规范化的损失之和,规范化的损失数\n", @@ -345,24 +360,15 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 15, "id": "d892b8df-eced-4fd0-84a9-469eb266eacd", "metadata": {}, "outputs": [ { - "ename": "RuntimeError", - "evalue": "The pointer[mgr] is null.\n\n----------------------------------------------------\n- C++ Call Stack: (For framework developers)\n----------------------------------------------------\nmindspore/ccsrc/backend/graph_compiler/segment_runner.cc:146 TransformSegmentToAnfGraph\n", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[12], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m lr, num_epochs \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.002\u001b[39m, \u001b[38;5;241m5\u001b[39m\n\u001b[0;32m----> 2\u001b[0m \u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnet\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_epochs\u001b[49m\u001b[43m)\u001b[49m\n", - "Cell \u001b[0;32mIn[11], line 24\u001b[0m, in \u001b[0;36mtrain\u001b[0;34m(net, dataset, lr, num_epochs)\u001b[0m\n\u001b[1;32m 22\u001b[0m net\u001b[38;5;241m.\u001b[39mset_train()\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, batch \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(dataset\u001b[38;5;241m.\u001b[39mcreate_tuple_iterator()):\n\u001b[0;32m---> 24\u001b[0m (l, l_sum), grads \u001b[38;5;241m=\u001b[39m \u001b[43mgrad_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 25\u001b[0m optimizer(grads)\n\u001b[1;32m 26\u001b[0m metric\u001b[38;5;241m.\u001b[39madd(l_sum, l\u001b[38;5;241m.\u001b[39mnumel())\n", - "File \u001b[0;32m/data/miniconda3/envs/ms_d2l/lib/python3.8/site-packages/mindspore/ops/composite/base.py:605\u001b[0m, in \u001b[0;36m_Grad.__call__..after_grad\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 604\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mafter_grad\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 605\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mgrad_\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn_\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/data/miniconda3/envs/ms_d2l/lib/python3.8/site-packages/mindspore/common/api.py:101\u001b[0m, in \u001b[0;36m_wrap_func..wrapper\u001b[0;34m(*arg, **kwargs)\u001b[0m\n\u001b[1;32m 99\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(fn)\n\u001b[1;32m 100\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39marg, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 101\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 102\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _convert_python_data(results)\n", - "File \u001b[0;32m/data/miniconda3/envs/ms_d2l/lib/python3.8/site-packages/mindspore/ops/composite/base.py:583\u001b[0m, in \u001b[0;36m_Grad.__call__..after_grad\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 580\u001b[0m \u001b[38;5;129m@_wrap_func\u001b[39m\n\u001b[1;32m 581\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mafter_grad\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 582\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pynative_forward_run(fn, grad_, args, kwargs)\n\u001b[0;32m--> 583\u001b[0m \u001b[43m_pynative_executor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgrad\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgrad_\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgrad_position\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 584\u001b[0m out \u001b[38;5;241m=\u001b[39m _pynative_executor()\n\u001b[1;32m 585\u001b[0m out \u001b[38;5;241m=\u001b[39m _grads_divided_by_device_num_if_recomputation(out)\n", - "File \u001b[0;32m/data/miniconda3/envs/ms_d2l/lib/python3.8/site-packages/mindspore/common/api.py:1115\u001b[0m, in \u001b[0;36m_PyNativeExecutor.grad\u001b[0;34m(self, obj, grad, weights, grad_position, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1099\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mgrad\u001b[39m(\u001b[38;5;28mself\u001b[39m, obj, grad, weights, grad_position, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 1100\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1101\u001b[0m \u001b[38;5;124;03m Get grad graph.\u001b[39;00m\n\u001b[1;32m 1102\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1113\u001b[0m \u001b[38;5;124;03m None.\u001b[39;00m\n\u001b[1;32m 1114\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1115\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_executor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgrad_net\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgrad\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mobj\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgrad_position\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalues\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[0;31mRuntimeError\u001b[0m: The pointer[mgr] is null.\n\n----------------------------------------------------\n- C++ Call Stack: (For framework developers)\n----------------------------------------------------\nmindspore/ccsrc/backend/graph_compiler/segment_runner.cc:146 TransformSegmentToAnfGraph\n" + "name": "stdout", + "output_type": "stream", + "text": [ + "loss 0.410, 13080.0 tokens/sec\n" ] }, { @@ -371,16 +377,16 @@ "\n", "\n", - "\n", + "\n", " \n", " \n", " \n", " \n", - " 2023-03-05T10:27:45.978204\n", + " 2025-12-21T10:19:26.578758\n", " image/svg+xml\n", " \n", " \n", - " Matplotlib v3.6.2, https://matplotlib.org/\n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", " \n", " \n", " \n", @@ -391,82 +397,76 @@ " \n", " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", " \n", " \n", " \n", " \n", + " \n", + " \n", + " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", - " \n", " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", - 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" \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", + " \n", + " \n", + " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", " \n", " \n", + " \n", + " \n", + " \n", + " \n", + " \n", "\n" ], "text/plain": [ @@ -817,18 +1069,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "d0ba53e9-a9b3-4d9e-99ea-0b3121a237a3", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cosine sim=0.767: intel\n", + "cosine sim=0.758: microprocessor\n", + "cosine sim=0.676: chips\n" + ] + } + ], "source": [ "def get_similar_tokens(query_token, k, embed):\n", " W = embed.embedding_table.data\n", " x = W[vocab[query_token]]\n", " # 计算余弦相似性。增加1e-9以获得数值稳定性\n", - " cos = ops.mv(W, x) / ops.sqrt(ops.sum(W * W, dim=1) *\n", - " ops.sum(x * x) + 1e-9)\n", - " topk = ops.topk(cos, k=k+1)[1].astype('int32')\n", + " cos = mint.mv(W, x) / mint.sqrt(mint.sum(W * W, dim=1) *\n", + " mint.sum(x * x) + 1e-9)\n", + " topk = mint.topk(cos, k=k+1)[1].astype('int32')\n", " for i in topk[1:]: # 删除输入词\n", " print(f'cosine sim={float(cos[i]):.3f}: {vocab.to_tokens(i)}')\n", "\n", @@ -870,9 +1132,9 @@ ], "metadata": { "kernelspec": { - "display_name": "ms_d2l", + "display_name": "Python 3.10", "language": "python", - "name": "ms_d2l" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -884,7 +1146,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_14_natural_language_processing_pretraining/6_similarity_analogy.ipynb b/chapter_14_natural_language_processing_pretraining/6_similarity_analogy.ipynb index af40cb1..7fb1e07 100644 --- a/chapter_14_natural_language_processing_pretraining/6_similarity_analogy.ipynb +++ b/chapter_14_natural_language_processing_pretraining/6_similarity_analogy.ipynb @@ -24,15 +24,23 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "ad25d092-ecb2-42a0-9e48-6716620c6ff6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(217135,ffff9c16c640,python):2025-12-21-11:02:33.171.909 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + } + ], "source": [ "import os\n", "import mindspore\n", "import mindspore.nn as nn\n", - "import mindspore.ops as ops\n", + "from mindspore import mint\n", "from d2l import mindspore as d2l" ] }, @@ -228,10 +236,10 @@ "source": [ "def knn(W, x, k):\n", " # 增加1e-9以获得数值稳定性\n", - " cos = ops.mv(W, x.reshape(-1,)) / (\n", - " ops.sqrt(ops.sum(W * W, dim=1) + 1e-9) *\n", - " ops.sqrt((x * x).sum()))\n", - " _, topk = ops.topk(cos, k=k)\n", + " cos = mint.mv(W, x.reshape(-1,)) / (\n", + " mint.sqrt(mint.sum(W * W, dim=1) + 1e-9) *\n", + " mint.sqrt((x * x).sum()))\n", + " _, topk = mint.topk(cos, k=k)\n", " return topk, [cos[int(i)] for i in topk]" ] }, @@ -270,6 +278,13 @@ "id": "6345ef84-935f-4a88-a795-3bc72a6aa789", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] DEVICE(217135,ffff9c16c640,python):2025-12-21-11:03:21.077.772 [mindspore/ccsrc/plugin/ascend/res_manager/mem_manager/ascend_memory_adapter.cc:127] Initialize] Free memory size is less than half of total memory size.Device 0 Device MOC total size:65464696832 Device MOC free size:4000530432 may be other processes occupying this card, check as: ps -ef|grep python\n" + ] + }, { "name": "stdout", "output_type": "stream", @@ -508,9 +523,9 @@ ], "metadata": { "kernelspec": { - "display_name": "ms_d2l", + "display_name": "Python 3.10", "language": "python", - "name": "ms_d2l" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -522,7 +537,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_14_natural_language_processing_pretraining/7_bert.ipynb b/chapter_14_natural_language_processing_pretraining/7_bert.ipynb index 2cbfad0..862e6b4 100644 --- a/chapter_14_natural_language_processing_pretraining/7_bert.ipynb +++ b/chapter_14_natural_language_processing_pretraining/7_bert.ipynb @@ -49,14 +49,22 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "5e7d3239-a83e-4000-9260-67c30c9b9947", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(232167,ffff7fe36640,python):2025-12-21-11:45:09.563.373 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + } + ], "source": [ "import mindspore\n", "import mindspore.nn as nn\n", - "import mindspore.ops as ops\n", + "from mindspore import mint\n", "from d2l import mindspore as d2l" ] }, @@ -131,7 +139,7 @@ " key_size, query_size, value_size, num_hiddens, norm_shape,\n", " ffn_num_input, ffn_num_hiddens, num_heads, dropout, True))\n", " # 在BERT中,位置嵌入是可学习的,因此我们创建一个足够长的位置嵌入参数\n", - " self.pos_embedding = mindspore.Parameter(ops.randn(1, max_len,num_hiddens),\n", + " self.pos_embedding = mindspore.Parameter(mint.randn(1, max_len,num_hiddens),\n", " name=\"pos_embedding\")\n", "\n", " def construct(self, tokens, segments, valid_lens):\n", @@ -156,7 +164,20 @@ "execution_count": 5, "id": "14274d54-0c0b-43f5-84a0-88c73c99b802", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] ME(232167:281472827352640,MainProcess):2025-12-21-11:45:21.765.000 [mindspore/nn/layer/basic.py:174] For Dropout, this parameter `keep_prob` will be deprecated, please use `p` instead.\n", + "[WARNING] ME(232167:281472827352640,MainProcess):2025-12-21-11:45:21.801.000 [mindspore/nn/layer/basic.py:174] For Dropout, this parameter `keep_prob` will be deprecated, please use `p` instead.\n", + "[WARNING] ME(232167:281472827352640,MainProcess):2025-12-21-11:45:21.825.000 [mindspore/nn/layer/basic.py:174] For Dropout, this parameter `keep_prob` will be deprecated, please use `p` instead.\n", + "[WARNING] ME(232167:281472827352640,MainProcess):2025-12-21-11:45:21.828.000 [mindspore/nn/layer/basic.py:174] For Dropout, this parameter `keep_prob` will be deprecated, please use `p` instead.\n", + "[WARNING] ME(232167:281472827352640,MainProcess):2025-12-21-11:45:21.863.000 [mindspore/nn/layer/basic.py:174] For Dropout, this parameter `keep_prob` will be deprecated, please use `p` instead.\n", + "[WARNING] ME(232167:281472827352640,MainProcess):2025-12-21-11:45:21.887.000 [mindspore/nn/layer/basic.py:174] For Dropout, this parameter `keep_prob` will be deprecated, please use `p` instead.\n" + ] + } + ], "source": [ "vocab_size, num_hiddens, ffn_num_hiddens, num_heads = 10000, 768, 1024, 4\n", "norm_shape, ffn_num_input, num_layers, dropout = [768], 768, 2, 0.2\n", @@ -190,7 +211,7 @@ } ], "source": [ - "tokens = ops.randint(0, vocab_size, (2, 8))\n", + "tokens = mint.randint(0, vocab_size, (2, 8))\n", "segments = mindspore.Tensor([[0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 1, 1, 1, 1, 1]])\n", "encoded_X = encoder(tokens, segments, None)\n", "encoded_X.shape" @@ -243,10 +264,10 @@ " num_pred_positions = pred_positions.shape[1]\n", " pred_positions = pred_positions.reshape(-1)\n", " batch_size = X.shape[0]\n", - " batch_idx = ops.arange(0, batch_size)\n", + " batch_idx = mint.arange(0, batch_size)\n", " # 假设batch_size=2,num_pred_positions=3\n", " # 那么batch_idx是np.array([0,0,0,1,1,1])\n", - " batch_idx = ops.repeat_interleave(batch_idx, num_pred_positions, 0)\n", + " batch_idx = mint.repeat_interleave(batch_idx, num_pred_positions, dim=0)\n", " masked_X = X[batch_idx, pred_positions]\n", " masked_X = masked_X.reshape((batch_size, num_pred_positions, -1))\n", " mlm_Y_hat = self.mlp(masked_X)\n", @@ -375,8 +396,8 @@ } ], "source": [ - "encoded_X = ops.flatten(encoded_X)\n", "# NSP的输入形状:(batchsize,num_hiddens)\n", + "encoded_X = encoded_X[:, 0, :]\n", "nsp = NextSentencePred(encoded_X.shape[-1])\n", "nsp_Y_hat = nsp(encoded_X)\n", "nsp_Y_hat.shape" @@ -392,7 +413,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "84ba52e2-5eda-4226-bb92-aeaf62f41977", "metadata": {}, "outputs": [ @@ -402,7 +423,7 @@ "(2,)" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -427,7 +448,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "850487e0-3eb4-4199-9871-5f995195e42b", "metadata": {}, "outputs": [], @@ -494,9 +515,9 @@ ], "metadata": { "kernelspec": { - "display_name": "ms_d2l", + "display_name": "Python 3.10", "language": "python", - "name": "ms_d2l" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -508,7 +529,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_15_natural_language_processing_applications/1_sentiment_analysis_and_dataset.ipynb b/chapter_15_natural_language_processing_applications/1_sentiment_analysis_and_dataset.ipynb index 94c8afa..ad48b2d 100644 --- a/chapter_15_natural_language_processing_applications/1_sentiment_analysis_and_dataset.ipynb +++ b/chapter_15_natural_language_processing_applications/1_sentiment_analysis_and_dataset.ipynb @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "9bb8e4c2", "metadata": {}, "outputs": [], @@ -30,13 +30,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "9ffc55a6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(285146,ffffb2c21640,python):2025-12-21-14:34:05.410.609 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + } + ], "source": [ "from d2l import mindspore as d2l\n", - "from mindspore import nn, ops\n", "import numpy as np\n", "import os" ] @@ -53,10 +60,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "aa23a672", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "正在从http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz下载../data/aclImdb_v1.tar.gz...\n" + ] + } + ], "source": [ "d2l.DATA_HUB['aclImdb'] = (\n", " 'http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz',\n", @@ -75,10 +90,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "76cf7444", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "训练集数目: 25000\n", + "标签: 1 review: I never thought an old cartoon would bring tears to my eyes!\n", + "标签: 1 review: Great acting, great movie. If you are thinking of building s\n", + "标签: 1 review: Only once in a while do we get an R-rated comedy that gets e\n" + ] + } + ], "source": [ "def read_imdb(data_dir, is_train):\n", " \"\"\"读取IMDb评论数据集文本序列和标签\"\"\"\n", @@ -111,7 +137,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "34809770", "metadata": {}, "outputs": [], @@ -130,10 +156,864 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "9e2b8a0c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " 2025-12-21T14:37:15.321632\n", + " image/svg+xml\n", + " \n", + " \n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n" + ], + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "d2l.set_figsize()\n", "d2l.plt.xlabel('# tokens per review')\n", @@ -151,10 +1031,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "7a9d5d2e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(25000, 500)\n" + ] + } + ], "source": [ "num_steps = 500 # 序列长度\n", "train_features = np.array([d2l.truncate_pad(\n", @@ -174,10 +1062,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "5d5c0c52", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "X: (64, 500) , y: (64,)\n", + "小批量数目: 391\n" + ] + } + ], "source": [ "train_iter = d2l.load_array((train_features, train_data[1]), 64)\n", "\n", @@ -199,7 +1096,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "b9c87961", "metadata": {}, "outputs": [], @@ -216,8 +1113,8 @@ " vocab[line], num_steps, vocab['']) for line in train_tokens]\n", " test_features = [d2l.truncate_pad(\n", " vocab[line], num_steps, vocab['']) for line in test_tokens]\n", - " train_iter = load_array((train_features, train_data[1]), batch_size)\n", - " test_iter = load_array((test_features, test_data[1]),\n", + " train_iter = d2l.load_array((train_features, train_data[1]), batch_size)\n", + " test_iter = d2l.load_array((test_features, test_data[1]),\n", " batch_size,\n", " is_train=False)\n", " return train_iter, test_iter, vocab" @@ -242,9 +1139,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -256,7 +1153,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.12" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_15_natural_language_processing_applications/2_sentiment_analysis_rnn.ipynb b/chapter_15_natural_language_processing_applications/2_sentiment_analysis_rnn.ipynb index 7046e70..1cfca85 100644 --- a/chapter_15_natural_language_processing_applications/2_sentiment_analysis_rnn.ipynb +++ b/chapter_15_natural_language_processing_applications/2_sentiment_analysis_rnn.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "d688acc1", "metadata": {}, "outputs": [], @@ -27,14 +27,15 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "201e0fb1", "metadata": {}, "outputs": [], "source": [ "from d2l import mindspore as d2l\n", - "from mindspore import nn, ops, Tensor\n", + "from mindspore import nn, Tensor\n", "from mindspore import dtype as mstype\n", + "from mindspore import mint\n", "from mindspore.common import initializer as weight_init\n", "\n", "batch_size = 64\n", @@ -53,7 +54,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "63b784fa", "metadata": {}, "outputs": [], @@ -68,7 +69,7 @@ " bidirectional=True)\n", " self.decoder = nn.Dense(4 * num_hiddens, 2)\n", "\n", - " def constrtuct(self, inputs):\n", + " def construct(self, inputs):\n", " # inputs的形状是(批量大小,时间步数)\n", " # 因为长短期记忆网络要求其输入的第一个维度是时间维,\n", " # 所以在获得词元表示之前,输入会被转置。\n", @@ -79,7 +80,7 @@ " outputs, _ = self.encoder(embeddings)\n", " # 连结初始和最终时间步的隐状态,作为全连接层的输入,\n", " # 其形状为(批量大小,4*隐藏单元数)\n", - " encoding = ops.cat((outputs[0], outputs[-1]), axis=1)\n", + " encoding = mint.cat((outputs[0], outputs[-1]), dim=1)\n", " outs = self.decoder(encoding)\n", " return outs" ] @@ -112,7 +113,10 @@ " weight = getattr(cell, name)\n", " weight.set_data(weight_init.initializer(init_normal, weight.shape,\n", " weight.dtype)) \n", - " \n", + "\n", + "# 实例化双向RNN模型\n", + "embed_size, num_hiddens, num_layers = 100, 100, 2\n", + "net = BiRNN(len(vocab), embed_size, num_hiddens, num_layers) \n", "init_weights(net)" ] }, @@ -128,7 +132,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "bb1acca9", "metadata": {}, "outputs": [], @@ -146,10 +150,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "685a2fd7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(49346, 100)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "embeds = glove_embedding[vocab.idx_to_token]\n", "embeds.shape" @@ -165,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "ec007ddd", "metadata": {}, "outputs": [], @@ -186,10 +201,965 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "6f38c983", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loss 0.314, train acc 0.868, test acc 0.851\n", + "71.6 examples/sec\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " 2025-12-21T15:25:04.356738\n", + " image/svg+xml\n", + " \n", + " \n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n" + ], + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "lr, num_epochs = 0.01, 5\n", "trainer = nn.Adam(learning_rate=lr, params=net.trainable_params())\n", @@ -207,7 +1177,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "d23a35b0", "metadata": {}, "outputs": [], @@ -215,7 +1185,7 @@ "def predict_sentiment(net, vocab, sequence):\n", " \"\"\"预测文本序列的情感\"\"\"\n", " sequence = Tensor(vocab[sequence.split()], mstype.int32)\n", - " label = ops.argmax(net(sequence.reshape((1, -1))), axis=1)\n", + " label = mint.argmax(net(sequence.reshape((1, -1))), dim=1)\n", " return 'positive' if label == 1 else 'negative'" ] }, @@ -229,20 +1199,49 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "c6312d18", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "." + ] + }, + { + "data": { + "text/plain": [ + "'positive'" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "predict_sentiment(net, vocab, 'this movie is so great')" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "966141f9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'negative'" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "predict_sentiment(net, vocab, 'this movie is so bad')" ] @@ -279,9 +1278,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -293,7 +1292,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.12" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_15_natural_language_processing_applications/3_sentiment_analysis_cnn.ipynb b/chapter_15_natural_language_processing_applications/3_sentiment_analysis_cnn.ipynb index 5a838ce..9f6a30c 100644 --- a/chapter_15_natural_language_processing_applications/3_sentiment_analysis_cnn.ipynb +++ b/chapter_15_natural_language_processing_applications/3_sentiment_analysis_cnn.ipynb @@ -29,15 +29,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "48191c52", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(446700,ffff98163640,python):2025-12-21-21:55:39.179.844 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + } + ], "source": [ "from d2l import mindspore as d2l\n", "from mindspore.common import initializer as weight_init\n", - "from mindspore import nn, ops\n", - "\n", + "from mindspore import nn\n", + "from mindspore import mint\n", + "import mindspore" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "7584f315-50a0-47fe-938c-84f154b03905", + "metadata": {}, + "outputs": [], + "source": [ "batch_size = 64\n", "train_iter, test_iter, vocab = d2l.load_data_imdb(batch_size)" ] @@ -61,14 +79,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "7c2376bc", "metadata": {}, "outputs": [], "source": [ "def corr1d(X, K):\n", " w = K.shape[0]\n", - " Y = d2l.zeros((X.shape[0] - w + 1))\n", + " Y = mint.zeros((X.shape[0] - w + 1))\n", " for i in range(Y.shape[0]):\n", " Y[i] = (X[i: i + w] * K).sum()\n", " return Y" @@ -84,10 +102,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "688c5e7e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Tensor(shape=[6], dtype=Float32, value= [ 2.00000000e+00, 5.00000000e+00, 8.00000000e+00, 1.10000000e+01, 1.40000000e+01, 1.70000000e+01])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "X, K = d2l.tensor([0, 1, 2, 3, 4, 5, 6]), d2l.tensor([1, 2])\n", "corr1d(X, K)" @@ -108,10 +137,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "e42c7d37", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Tensor(shape=[6], dtype=Float32, value= [ 2.00000000e+00, 8.00000000e+00, 1.40000000e+01, 2.00000000e+01, 2.60000000e+01, 3.20000000e+01])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def corr1d_multi_in(X, K):\n", " # 首先,遍历'X'和'K'的第0维(通道维)。然后,把它们加在一起\n", @@ -162,7 +202,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "2ed6c15d", "metadata": {}, "outputs": [], @@ -177,7 +217,8 @@ " self.dropout = nn.Dropout(p=0.5)\n", " self.decoder = nn.Dense(sum(num_channels), 2)\n", " # 最大时间汇聚层没有参数,因此可以共享此实例\n", - " self.pool = nn.AdaptiveAvgPool1d(1)\n", + " # TextCNN通过最大池化提取最显著特征\n", + " self.pool = nn.AdaptiveMaxPool1d(1)\n", " self.relu = nn.ReLU()\n", " # 创建多个一维卷积层\n", " self.convs = nn.CellList()\n", @@ -187,15 +228,15 @@ " def construct(self, inputs):\n", " # 沿着向量维度将两个嵌入层连结起来,\n", " # 每个嵌入层的输出形状都是(批量大小,词元数量,词元向量维度)连结起来\n", - " embeddings = ops.cat((\n", - " self.embedding(inputs), self.constant_embedding(inputs)), axis=2)\n", + " embeddings = mint.cat((\n", + " self.embedding(inputs), self.constant_embedding(inputs)), dim=2)\n", " # 根据一维卷积层的输入格式,重新排列张量,以便通道作为第2维\n", " embeddings = embeddings.transpose(0, 2, 1)\n", " # 每个一维卷积层在最大时间汇聚层合并后,获得的张量形状是(批量大小,通道数,1)\n", " # 删除最后一个维度并沿通道维度连结\n", - " encoding = ops.cat([\n", - " ops.squeeze(self.relu(self.pool(conv(embeddings))), axis=-1)\n", - " for conv in self.convs], axis=1)\n", + " encoding = mint.cat([\n", + " mint.squeeze(self.relu(self.pool(conv(embeddings))), dim=-1)\n", + " for conv in self.convs], dim=1)\n", " outputs = self.decoder(self.dropout(encoding))\n", " return outputs" ] @@ -210,7 +251,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "163fbfce", "metadata": {}, "outputs": [], @@ -241,7 +282,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "8f81ba9b", "metadata": {}, "outputs": [], @@ -265,13 +306,968 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "3358c347", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loss 0.072, train acc 0.976, test acc 0.865\n", + "1919.5 examples/sec\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " 2025-12-21T21:58:55.459066\n", + " image/svg+xml\n", + " \n", + " \n", + " Matplotlib v3.8.4, https://matplotlib.org/\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n" + ], + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "lr, num_epochs = 0.001, 5\n", - "trainer = nn.Adam(params=net.trainable_params(), lr=lr)\n", + "trainer = nn.Adam(params=net.trainable_params(), learning_rate=lr)\n", "loss = nn.CrossEntropyLoss(reduction=\"none\")\n", "d2l.train_ch13(net, train_iter, test_iter, loss, trainer, num_epochs)" ] @@ -286,20 +1282,49 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "39004eb1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "." + ] + }, + { + "data": { + "text/plain": [ + "'positive'" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "d2l.predict_sentiment(net, vocab, 'this movie is so great')" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "940726d0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'negative'" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "d2l.predict_sentiment(net, vocab, 'this movie is so bad')" ] @@ -326,9 +1351,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -340,7 +1365,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.12" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_15_natural_language_processing_applications/4_natural_language_inference_and_dataset.ipynb b/chapter_15_natural_language_processing_applications/4_natural_language_inference_and_dataset.ipynb index 2cdad72..e360c24 100644 --- a/chapter_15_natural_language_processing_applications/4_natural_language_inference_and_dataset.ipynb +++ b/chapter_15_natural_language_processing_applications/4_natural_language_inference_and_dataset.ipynb @@ -66,7 +66,7 @@ "outputs": [], "source": [ "from d2l import mindspore as d2l\n", - "from mindspore import nn, ops\n", + "from mindspore import nn\n", "import os\n", "import re\n", "\n", @@ -299,9 +299,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -313,7 +313,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.12" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_15_natural_language_processing_applications/5_natural_language_inference_attention.ipynb b/chapter_15_natural_language_processing_applications/5_natural_language_inference_attention.ipynb index ab47fd7..ccfdc40 100644 --- a/chapter_15_natural_language_processing_applications/5_natural_language_inference_attention.ipynb +++ b/chapter_15_natural_language_processing_applications/5_natural_language_inference_attention.ipynb @@ -36,14 +36,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "00b36e33", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[WARNING] CORE(338881,ffff9482d640,python):2025-12-21-17:10:36.637.850 [mindspore/core/utils/ms_context.cc:533] GetJitLevel] Set jit level to O2 for rank table startup method.\n" + ] + } + ], "source": [ "from d2l import mindspore as d2l\n", - "from mindspore import nn, ops, Tensor\n", - "from mindspore import dtype as mstype" + "from mindspore import nn, Tensor\n", + "from mindspore import dtype as mstype\n", + "from mindspore import mint" ] }, { @@ -65,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "12571d03", "metadata": {}, "outputs": [], @@ -109,7 +118,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "2d2e811f", "metadata": {}, "outputs": [], @@ -128,10 +137,10 @@ " e = f_A.bmm(f_B.transpose(0, 2, 1))\n", " # beta的形状:(批量大小,序列A的词元数,embed_size),\n", " # 意味着序列B被软对齐到序列A的每个词元(beta的第1个维度)\n", - " beta = ops.softmax(e, axis=-1).bmm(B)\n", + " beta = mint.softmax(e, dim=-1).bmm(B)\n", " # beta的形状:(批量大小,序列B的词元数,embed_size),\n", " # 意味着序列A被软对齐到序列B的每个词元(alpha的第1个维度)\n", - " alpha = ops.softmax(e.transpose(0, 2, 1), axis=-1).bmm(A)\n", + " alpha = mint.softmax(e.transpose(0, 2, 1), dim=-1).bmm(A)\n", " return beta, alpha" ] }, @@ -155,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "0fabac37", "metadata": {}, "outputs": [], @@ -166,8 +175,8 @@ " self.g = mlp(num_inputs, num_hiddens, flatten=False)\n", "\n", " def construct(self, A, B, beta, alpha):\n", - " V_A = self.g(ops.cat((A, beta), axis=2))\n", - " V_B = self.g(ops.cat((B, alpha), axis=2))\n", + " V_A = self.g(mint.cat((A, beta), dim=2))\n", + " V_B = self.g(mint.cat((B, alpha), dim=2))\n", " return V_A, V_B" ] }, @@ -195,7 +204,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "5b92c515", "metadata": {}, "outputs": [], @@ -211,7 +220,7 @@ " V_A = V_A.sum(axis=1)\n", " V_B = V_B.sum(axis=1)\n", " # 将两个求和结果的连结送到多层感知机中\n", - " Y_hat = self.linear(self.h(ops.cat((V_A, V_B), axis=1)))\n", + " Y_hat = self.linear(self.h(mint.cat((V_A, V_B), dim=1)))\n", " return Y_hat" ] }, @@ -227,7 +236,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "e8f725dc", "metadata": {}, "outputs": [], @@ -268,10 +277,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "3e1fbafb", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "正在从https://nlp.stanford.edu/projects/snli/snli_1.0.zip下载../data/snli_1.0.zip...\n", + "read 549367 examples\n", + "read 9824 examples\n" + ] + } + ], "source": [ "batch_size, num_steps = 256, 50\n", "train_iter, test_iter, vocab = d2l.load_data_snli(batch_size, num_steps)" @@ -289,10 +308,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "89a270df", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Parameter (name=embedding.embedding_table, shape=(18678, 100), dtype=Float32, requires_grad=True)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "embed_size, num_hiddens = 100, 200\n", "net = DecomposableAttention(vocab, embed_size, num_hiddens)\n", @@ -311,10 +341,998 @@ }, { "cell_type": "code", - 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "lr, num_epochs = 0.001, 4\n", "trainer = nn.Adam(learning_rate=lr, params=net.trainable_params())\n", @@ -334,7 +1352,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "b2f40a3e", "metadata": {}, "outputs": [], @@ -344,8 +1362,8 @@ " net.set_train(False)\n", " premise = Tensor(vocab[premise], dtype=mstype.int32)\n", " hypothesis = Tensor(vocab[hypothesis], dtype=mstype.int32)\n", - " X = ops.stack((premise.reshape(-1, 1), hypothesis.reshape(-1, 1)), axis=1)\n", - " label = ops.argmax(net(X), axis=-1)\n", + " X = mint.stack((premise.reshape(-1, 1), hypothesis.reshape(-1, 1)), dim=1)\n", + " label = mint.argmax(net(X), dim=-1)\n", " results = []\n", " for l in label:\n", " if l == 0:\n", @@ -367,10 +1385,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "e4f3d6c6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "." + ] + }, + { + "data": { + "text/plain": [ + "['entailment', 'entailment', 'contradiction', 'entailment']" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "predict_snli(net, vocab, ['he', 'is', 'good', '.'], ['he', 'is', 'bad', '.'])" ] @@ -397,9 +1433,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.10", "language": "python", - "name": "python3" + "name": "py310" }, "language_info": { "codemirror_mode": { @@ -411,7 +1447,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.12" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/chapter_15_natural_language_processing_applications/7_natural_language_inference_bert.ipynb b/chapter_15_natural_language_processing_applications/7_natural_language_inference_bert.ipynb index 7c87305..7fb7d75 100644 --- a/chapter_15_natural_language_processing_applications/7_natural_language_inference_bert.ipynb +++ b/chapter_15_natural_language_processing_applications/7_natural_language_inference_bert.ipynb @@ -37,7 +37,7 @@ "from d2l import mindspore as d2l\n", "import json\n", "import multiprocessing\n", - "from mindspore import nn, ops\n", + "from mindspore import nn\n", "import os" ] }, diff --git a/img/autumn-oak.jpg b/img/autumn-oak.jpg new file mode 100644 index 0000000..747fa1e Binary files /dev/null and b/img/autumn-oak.jpg differ diff --git a/img/catdog.jpg b/img/catdog.jpg new file mode 100644 index 0000000..4471a71 Binary files /dev/null and b/img/catdog.jpg differ diff --git a/img/rainier.jpg b/img/rainier.jpg new file mode 100644 index 0000000..57f19a2 Binary files /dev/null and b/img/rainier.jpg differ