mirror of
https://github.com/facefusion/facefusion-labs.git
synced 2026-05-22 23:59:40 +02:00
Henry Ruhs
2e6394565a
* add sync batchnorm * replace random.choice with hash * fifty percent reduction * fix discriminator input * restore dataset.py * Remove duplicates * add discriminator_ratio to config * fix onnx export bug: replace round() with int() * Fix embedding naming * Introduce ModelWithConfigCheckpoint callback (#86) * Fix dist ini * Style: Refactor typing and improve code clarity in training.py (#88) * Add type casting for trainer params * Add type casting for trainer params * Add type casting for trainer params * Remove inplace activations for torch.compile compatibility (#89) * Fix README * improvise with norm layers & weighted average * add skip layer * use gelu instead of leaky_relu * cleanup * cleanup * Update dependencies * Different defaults and enable validation * Different defaults and enable validation * Revert to higher batch size * Just use copy over copy2 --------- Co-authored-by: harisreedhar <h4harisreedhar.s.s@gmail.com> Co-authored-by: NeuroDonu <112660822+NeuroDonu@users.noreply.github.com> Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>
97 lines
1.4 KiB
INI
97 lines
1.4 KiB
INI
[training.dataset]
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file_pattern =
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convert_template =
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multiplier =
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transform_size =
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usage_mode =
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batch_mode =
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batch_ratio =
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[training.loader]
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batch_size =
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num_workers =
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split_ratio =
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[training.model]
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generator_embedder_path =
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loss_embedder_path =
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gazer_path =
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face_masker_path =
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[training.model.generator]
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source_channels =
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output_size =
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num_blocks =
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[training.model.discriminator]
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input_channels =
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num_filters =
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num_layers =
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num_discriminators =
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kernel_size =
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[training.model.masker]
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input_channels =
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output_channels =
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num_filters =
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[training.losses]
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adversarial_weight =
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cycle_weight =
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feature_weight =
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reconstruction_weight =
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identity_weight =
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gaze_weight =
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mask_weight =
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[training.trainer]
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accumulate_size =
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discriminator_ratio =
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gradient_clip =
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max_epochs =
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strategy =
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precision =
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sync_batchnorm =
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preview_frequency =
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[training.modifier]
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mask_factor =
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noise_factor =
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[training.optimizer.generator]
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learning_rate =
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momentum =
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scheduler_factor =
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scheduler_patience =
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[training.optimizer.discriminator]
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learning_rate =
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momentum =
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scheduler_factor =
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scheduler_patience =
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[training.logger]
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logger_path =
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logger_name =
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[training.output]
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directory_path =
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file_pattern =
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resume_path =
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[exporting]
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directory_path =
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source_path =
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target_path =
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target_size =
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ir_version =
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opset_version =
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precision =
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[inferencing]
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generator_path =
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embedder_path =
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source_path =
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target_path =
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output_path =
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