Optimize framework performance with CSV buffering, configurable valid…#4
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fseiffarth wants to merge 4 commits into
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Optimize framework performance with CSV buffering, configurable valid…#4fseiffarth wants to merge 4 commits into
fseiffarth wants to merge 4 commits into
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…ation frequency, and improved file operations - Replace OS-specific commands with shutil.copy2 for cross-platform file copying - Add CSV buffering mechanism to reduce I/O operations (flush every 50 writes) - Add configurable validation frequency to skip validation on some epochs - Optimize eval/train mode switching to avoid redundant calls - Make evaluation batch size configurable (default 512) - Remove redundant self.net.train(False) call in evaluation loop Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
**Performance optimizations:** - Replace torch.nn.Dropout() with torch.nn.functional.dropout() in all MPNN layers for better performance - Optimize ShareGNN weight distribution using chunks instead of preallocated tensors - Remove redundant code and unused variables (representation_list, n_heads_per_label, num field) - Simplify num_heads calculation in framework_layer **Security fixes:** - Replace unsafe eval() with ACTIVATION_MAP dictionary for activation functions - Replace eval() with ast.literal_eval() in ShareGNN preprocessing **Code quality improvements:** - Fix inconsistent return patterns in model layer creation - Remove unused pandas import in inv_based_pooling - Fix property_dict bug in ShareGNN utils - Remove redundant out_features initialization in share_gnn_linear - Improve variable naming consistency in layer_loader (head → heads) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
…and improve weight distribution logic TODO fix inv_based_message_passing.py
…ve weight distribution logic
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…ation frequency, and improved file operations