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.github/workflows/build.yaml

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/__init__.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/datasets.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/event_codec.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/event_codec_test.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/inference.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -68,7 +68,7 @@ def write_inferences_to_file(
   else:
     encoding_spec = note_sequences.NoteEncodingWithTiesSpec
 
-  codec = vocabularies.build_codec(vocab_config)
+  codec = vocabularies.build_codec(vocab_config)  # pyrefly: ignore[bad-argument-type]
 
   targets = []
   predictions = []

mt3/layers.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -147,7 +147,7 @@ def dot_product_attention(query: Array,
     # corresponds to in positional dimensions here, assuming query dim.
     dropout_shape = list(attn_weights.shape)
     dropout_shape[-2] = 1
-    keep = random.bernoulli(dropout_rng, keep_prob, dropout_shape)
+    keep = random.bernoulli(dropout_rng, keep_prob, dropout_shape)  # pyrefly: ignore[bad-argument-type]
     keep = jnp.broadcast_to(keep, attn_weights.shape)
     multiplier = (
         keep.astype(attn_weights.dtype) / jnp.asarray(keep_prob, dtype=dtype))
@@ -357,7 +357,7 @@ def __call__(self,
 
 def _normalize_axes(axes: Iterable[int], ndim: int) -> Tuple[int]:
   # A tuple by convention. len(axes_tuple) then also gives the rank efficiently.
-  return tuple([ax if ax >= 0 else ndim + ax for ax in axes])
+  return tuple([ax if ax >= 0 else ndim + ax for ax in axes])  # pyrefly: ignore[bad-return]
 
 
 def _canonicalize_tuple(x):
@@ -593,7 +593,7 @@ def __call__(self,
       i = position_embedder_index.value
       position_embedder_index.value = i + 1
       return jax.lax.dynamic_slice(self.embedding, jnp.array((i, 0)),
-                                   np.array((1, self.features)))
+                                   np.array((1, self.features)))  # pyrefly: ignore[bad-argument-type]
 
     return jnp.take(self.embedding, inputs, axis=0)
 
@@ -700,15 +700,15 @@ def combine_masks(*masks: Optional[Array], dtype: DType = jnp.float32):
   Returns:
     Combined mask, reduced by logical and, returns None if no masks given.
   """
-  masks = [m for m in masks if m is not None]
+  masks = [m for m in masks if m is not None]  # pyrefly: ignore[bad-assignment]
   if not masks:
     return None
-  assert all(map(lambda x: x.ndim == masks[0].ndim, masks)), (
+  assert all(map(lambda x: x.ndim == masks[0].ndim, masks)), (  # pyrefly: ignore[missing-attribute]
       f'masks must have same rank: {tuple(map(lambda x: x.ndim, masks))}')
   mask, *other_masks = masks
   for other_mask in other_masks:
-    mask = jnp.logical_and(mask, other_mask)
-  return mask.astype(dtype)
+    mask = jnp.logical_and(mask, other_mask)  # pyrefly: ignore[bad-argument-type]
+  return mask.astype(dtype)  # pyrefly: ignore[missing-attribute]
 
 
 def combine_biases(*masks: Optional[Array]):
@@ -720,14 +720,14 @@ def combine_biases(*masks: Optional[Array]):
   Returns:
     Combined mask, reduced by summation, returns None if no masks given.
   """
-  masks = [m for m in masks if m is not None]
+  masks = [m for m in masks if m is not None]  # pyrefly: ignore[bad-assignment]
   if not masks:
     return None
-  assert all(map(lambda x: x.ndim == masks[0].ndim, masks)), (
+  assert all(map(lambda x: x.ndim == masks[0].ndim, masks)), (  # pyrefly: ignore[missing-attribute]
       f'masks must have same rank: {tuple(map(lambda x: x.ndim, masks))}')
   mask, *other_masks = masks
   for other_mask in other_masks:
-    mask = mask + other_mask
+    mask = mask + other_mask  # pyrefly: ignore[unsupported-operation]
   return mask
 
 

mt3/layers_test.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/metrics.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/metrics_utils.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/metrics_utils_test.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/mixing.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -59,10 +59,10 @@ def mix_transcription_examples(
     Dataset containing mixed examples.
   """
   if max_examples_per_mix is None:
-    return ds
+    return ds  # pyrefly: ignore[bad-return]
 
   # TODO(iansimon): is there a way to use seqio's seed?
-  ds = tf.data.Dataset.sample_from_datasets([
+  ds = tf.data.Dataset.sample_from_datasets([  # pyrefly: ignore[bad-argument-type]
       ds.shuffle(
           buffer_size=shuffle_buffer_size // max_examples_per_mix
       ).padded_batch(batch_size=i) for i in range(1, max_examples_per_mix + 1)

mt3/models.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -131,7 +131,7 @@ def __init__(self, module, input_vocabulary, output_vocabulary, optimizer_def,
         input_vocabulary=input_vocabulary,
         output_vocabulary=output_vocabulary,
         optimizer_def=optimizer_def,
-        decode_fn=decode_fn,
+        decode_fn=decode_fn,  # pyrefly: ignore[bad-argument-type]
         label_smoothing=label_smoothing,
         z_loss=z_loss,
         loss_normalizing_factor=loss_normalizing_factor)

mt3/network.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -344,7 +344,7 @@ def decode(
       encoder_decoder_mask = layers.combine_masks(
           encoder_decoder_mask,
           layers.make_attention_mask(
-              decoder_segment_ids,
+              decoder_segment_ids,  # pyrefly: ignore[bad-argument-type]
               encoder_segment_ids,
               jnp.equal,
               dtype=cfg.dtype))

mt3/note_sequences.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/note_sequences_test.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/preprocessors.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -64,7 +64,7 @@ def _audio_to_frames(
   """Convert audio samples to non-overlapping frames and frame times."""
   frame_size = spectrogram_config.hop_width
   logging.info('Padding %d samples to multiple of %d', len(samples), frame_size)
-  samples = np.pad(samples,
+  samples = np.pad(samples,  # pyrefly: ignore[bad-assignment]
                    [0, frame_size - len(samples) % frame_size],
                    mode='constant')
 
@@ -167,9 +167,9 @@ def tokenize(sequence, audio, sample_rate, example_id=None):
              event_values=values,
              encode_event_fn=note_sequences.note_event_data_to_events,
              codec=codec,
-             frame_times=frame_times,
+             frame_times=frame_times,  # pyrefly: ignore[bad-argument-type]
              encoding_state_to_events_fn=(
-                 note_sequences.note_encoding_state_to_events
+                 note_sequences.note_encoding_state_to_events  # pyrefly: ignore[bad-argument-type]
                  if include_ties else None)))
 
     yield {
@@ -196,7 +196,7 @@ def process_record(input_record):
       args.append(input_record[id_feature_key])
 
     ds = tf.data.Dataset.from_generator(
-        tokenize,
+        tokenize,  # pyrefly: ignore[bad-argument-type]
         output_signature={
             'inputs':
                 tf.TensorSpec(
@@ -339,9 +339,9 @@ def tokenize(sequences, inst_names, audio, example_id=None):
              event_values=values,
              encode_event_fn=note_sequences.note_event_data_to_events,
              codec=codec,
-             frame_times=frame_times,
+             frame_times=frame_times,  # pyrefly: ignore[bad-argument-type]
              encoding_state_to_events_fn=(
-                 note_sequences.note_encoding_state_to_events
+                 note_sequences.note_encoding_state_to_events  # pyrefly: ignore[bad-argument-type]
                  if include_ties else None)))
 
     yield {
@@ -365,7 +365,7 @@ def process_record(input_record):
       args.append(input_record[id_feature_key])
 
     ds = tf.data.Dataset.from_generator(
-        tokenize,
+        tokenize,  # pyrefly: ignore[bad-argument-type]
         output_signature={
             'inputs':
                 tf.TensorSpec(
@@ -556,9 +556,9 @@ def tokenize(sequences, samples, sample_rate, inst_names, example_id):
              event_values=values,
              encode_event_fn=note_sequences.note_event_data_to_events,
              codec=codec,
-             frame_times=frame_times,
+             frame_times=frame_times,  # pyrefly: ignore[bad-argument-type]
              encoding_state_to_events_fn=(
-                 note_sequences.note_encoding_state_to_events
+                 note_sequences.note_encoding_state_to_events  # pyrefly: ignore[bad-argument-type]
                  if include_ties else None)))
 
     yield {
@@ -574,7 +574,7 @@ def tokenize(sequences, samples, sample_rate, inst_names, example_id):
 
   def process_record(input_record):
     ds = tf.data.Dataset.from_generator(
-        tokenize,
+        tokenize,  # pyrefly: ignore[bad-argument-type]
         output_signature={
             'inputs':
                 tf.TensorSpec(

mt3/run_length_encoding.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -124,8 +124,8 @@ def fill_event_start_indices_to_cur_step():
     while(len(event_start_indices) < len(frame_times) and
           frame_times[len(event_start_indices)] <
           cur_step / codec.steps_per_second):
-      event_start_indices.append(cur_event_idx)
-      state_event_indices.append(cur_state_event_idx)
+      event_start_indices.append(cur_event_idx)  # pyrefly: ignore[missing-attribute]
+      state_event_indices.append(cur_state_event_idx)  # pyrefly: ignore[missing-attribute]
 
   for event_step, event_value in zip(event_steps, event_values):
     while event_step > cur_step:
@@ -163,7 +163,7 @@ def fill_event_start_indices_to_cur_step():
   event_end_indices = np.array(event_end_indices)
   state_event_indices = np.array(state_event_indices)
 
-  return (events, event_start_indices, event_end_indices,
+  return (events, event_start_indices, event_end_indices,  # pyrefly: ignore[bad-return]
           state_events, state_event_indices)
 
 

mt3/run_length_encoding_test.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/scripts/dump_task.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/scripts/extract_monophonic_examples.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -240,7 +240,7 @@ def main(unused_argv):
         continue
       logging.info('processing %s...', filename)
       for ex in process_wav_file(
-          os.path.join(_INPUT_DIR.value, filename), crepe, counters):
+          os.path.join(_INPUT_DIR.value, filename), crepe, counters):  # pyrefly: ignore[no-matching-overload]
         writer.write(ex.SerializeToString())
       counters['wav_files_processed'] += 1
   for k, v in counters.items():

mt3/spectral_ops.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

mt3/spectrograms.py

@@ -1,4 +1,4 @@
-# Copyright 2025 The MT3 Authors.
+# Copyright 2026 The MT3 Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.