Bm/version 1.4.0 #137
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Bm/version 1.4.0 #137
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Transformer-based models can now be reused and expanded quickly and easily
…/DeepTrack-2.0 into dt/eth-cs-examples
…/DeepTrack-2.0 into dt/eth-cs-examples
…/DeepTrack-2.0 into dt/eth-cs-examples
…eepTrack-2.0 into bm/version-1.4.0
giovannivolpe
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* chore: autopublish 2022-07-26T13:54:44Z * Remove create-badges job * Delete test.py * Add multi-head masked attention * Update multi-head gated attention to match parent layer * Update documentation * Test multi-head masked attention * allow gated attention layers to use bias * test bias in gated attention layers * set return_attention_weights to False to avoid multi-outputs Use MultiHeadSelfAttention and MultiHeadGatedSelfAttention if want to return the attention weights * reformat gnns/layers.py This commit adds new message-passing graph layers (MPN) and graph convolutional layers to dt, including vanilla MPN, GRUMPN, Masked-attention FGNN, and GraphTransformer. * Update layers.py * Update test_layers.py * Update models.py * Update test_models.py * Update test_models.py * Fix indexing problems related to tf.gather * Allow multi-inputs in ContinuousGenerator * Fix bad conversion to integer * version bump * Fix phase correction at focus and offset calculation * Fix phase correction in propagation * Fix mie phase out of foucs * Fix mie phase out of foucs * Update README.md * Bm/version 1.4.0 (#137) * Update layers.py * Update convolutional.py Transformer-based models can now be reused and expanded quickly and easily * Update documentation * Update Transformer-based models * Delete classifying_MNIST_vit_tutorial.ipynb * Create classifying_MNIST_vit_tutorial.ipynb * Update datasets.py * Allows kwargs as inputs in single_layer_call * Update embeddings.py * masked transformers * reformat transformer models * Create trajectory_analysis_tutorial.ipynb * Add Variational autoencoders * Add variational autoencoders * Update vae.py * Create MNIST_VAE_tutorial.ipynb * Update MNIST_VAE_tutorial.ipynb * Create folder for course examples * Update README.md * Update README.md * Update examples * Update README.md * Update README.md * Update MNIST VAE examples * Added MLP regression example * Update README.md * Create image_segmentation_Unet.ipynb * Update README.md * Documented and tested cell_counting_tutorial.ipynb * improve dnn example * Shift variant mie * Position mie scatterer correctly * implement set z * implement mnist v1 * implement z dependence * remove logging * Implement flattening methods * Implement pooling and resizing * Implement TensorflowDataset * Finalize MNIST * Implement Malaria classification * alpha0 release * fix batchsize in fit * implement dataset.take * Implement datasets * fix phase in mie * Fix mie positioning and focusing * Commit to new branch * add tensorflow datasets dependence * remove test Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Ccx55 <ccx555@gmail.com> Co-authored-by: BenjaminMidtvedt <41636530+BenjaminMidtvedt@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Ccx55 <ccx555@gmail.com>
giovannivolpe
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* chore: autopublish 2022-07-26T13:54:44Z * Remove create-badges job * Delete test.py * Add multi-head masked attention * Update multi-head gated attention to match parent layer * Update documentation * Test multi-head masked attention * allow gated attention layers to use bias * test bias in gated attention layers * set return_attention_weights to False to avoid multi-outputs Use MultiHeadSelfAttention and MultiHeadGatedSelfAttention if want to return the attention weights * reformat gnns/layers.py This commit adds new message-passing graph layers (MPN) and graph convolutional layers to dt, including vanilla MPN, GRUMPN, Masked-attention FGNN, and GraphTransformer. * Update layers.py * Update test_layers.py * Update models.py * Update test_models.py * Update test_models.py * Fix indexing problems related to tf.gather * Allow multi-inputs in ContinuousGenerator * Fix bad conversion to integer * version bump * Fix phase correction at focus and offset calculation * Fix phase correction in propagation * Fix mie phase out of foucs * Fix mie phase out of foucs * Update README.md * Bm/version 1.4.0 (#137) * Update layers.py * Update convolutional.py Transformer-based models can now be reused and expanded quickly and easily * Update documentation * Update Transformer-based models * Delete classifying_MNIST_vit_tutorial.ipynb * Create classifying_MNIST_vit_tutorial.ipynb * Update datasets.py * Allows kwargs as inputs in single_layer_call * Update embeddings.py * masked transformers * reformat transformer models * Create trajectory_analysis_tutorial.ipynb * Add Variational autoencoders * Add variational autoencoders * Update vae.py * Create MNIST_VAE_tutorial.ipynb * Update MNIST_VAE_tutorial.ipynb * Create folder for course examples * Update README.md * Update README.md * Update examples * Update README.md * Update README.md * Update MNIST VAE examples * Added MLP regression example * Update README.md * Create image_segmentation_Unet.ipynb * Update README.md * Documented and tested cell_counting_tutorial.ipynb * improve dnn example * Shift variant mie * Position mie scatterer correctly * implement set z * implement mnist v1 * implement z dependence * remove logging * Implement flattening methods * Implement pooling and resizing * Implement TensorflowDataset * Finalize MNIST * Implement Malaria classification * alpha0 release * fix batchsize in fit * implement dataset.take * Implement datasets * fix phase in mie * Fix mie positioning and focusing * Commit to new branch * add tensorflow datasets dependence * remove test Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Ccx55 <ccx555@gmail.com> * Add tensorflow datasets to the list of dependencies. * Read requirements.txt into setup.py * remove sphinx from build * remove create badges * Create CITATION.cff * Create .zenodo.json * Update transformer models * Update pint_definition.py * Update requirements.txt * create TimeDistributed CNN * small fixes to lodestar Co-authored-by: BenjaminMidtvedt <41636530+BenjaminMidtvedt@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Ccx55 <ccx555@gmail.com>
giovannivolpe
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Nov 21, 2022
* chore: autopublish 2022-07-26T13:54:44Z * Remove create-badges job * Delete test.py * Add multi-head masked attention * Update multi-head gated attention to match parent layer * Update documentation * Test multi-head masked attention * allow gated attention layers to use bias * test bias in gated attention layers * set return_attention_weights to False to avoid multi-outputs Use MultiHeadSelfAttention and MultiHeadGatedSelfAttention if want to return the attention weights * reformat gnns/layers.py This commit adds new message-passing graph layers (MPN) and graph convolutional layers to dt, including vanilla MPN, GRUMPN, Masked-attention FGNN, and GraphTransformer. * Update layers.py * Update test_layers.py * Update models.py * Update test_models.py * Update test_models.py * Fix indexing problems related to tf.gather * Allow multi-inputs in ContinuousGenerator * Fix bad conversion to integer * version bump * Fix phase correction at focus and offset calculation * Fix phase correction in propagation * Fix mie phase out of foucs * Fix mie phase out of foucs * Update README.md * Bm/version 1.4.0 (#137) * Update layers.py * Update convolutional.py Transformer-based models can now be reused and expanded quickly and easily * Update documentation * Update Transformer-based models * Delete classifying_MNIST_vit_tutorial.ipynb * Create classifying_MNIST_vit_tutorial.ipynb * Update datasets.py * Allows kwargs as inputs in single_layer_call * Update embeddings.py * masked transformers * reformat transformer models * Create trajectory_analysis_tutorial.ipynb * Add Variational autoencoders * Add variational autoencoders * Update vae.py * Create MNIST_VAE_tutorial.ipynb * Update MNIST_VAE_tutorial.ipynb * Create folder for course examples * Update README.md * Update README.md * Update examples * Update README.md * Update README.md * Update MNIST VAE examples * Added MLP regression example * Update README.md * Create image_segmentation_Unet.ipynb * Update README.md * Documented and tested cell_counting_tutorial.ipynb * improve dnn example * Shift variant mie * Position mie scatterer correctly * implement set z * implement mnist v1 * implement z dependence * remove logging * Implement flattening methods * Implement pooling and resizing * Implement TensorflowDataset * Finalize MNIST * Implement Malaria classification * alpha0 release * fix batchsize in fit * implement dataset.take * Implement datasets * fix phase in mie * Fix mie positioning and focusing * Commit to new branch * add tensorflow datasets dependence * remove test Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Ccx55 <ccx555@gmail.com> * Add tensorflow datasets to the list of dependencies. * Read requirements.txt into setup.py * remove sphinx from build * remove create badges * Create CITATION.cff * Create .zenodo.json * Update transformer models * Update pint_definition.py * Update requirements.txt * create TimeDistributed CNN * small fixes to lodestar * remove direct getter of properties * Update scatterers.py Coherence length fix for MieScatterer * Update scatterers.py Added coherence length to the conversion table * mie phase fix Co-authored-by: BenjaminMidtvedt <41636530+BenjaminMidtvedt@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Ccx55 <ccx555@gmail.com> Co-authored-by: Harshith Bachimanchi <62615092+HarshithBachimanchi@users.noreply.github.com>
giovannivolpe
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* chore: autopublish 2022-07-26T13:54:44Z * Remove create-badges job * Delete test.py * Add multi-head masked attention * Update multi-head gated attention to match parent layer * Update documentation * Test multi-head masked attention * allow gated attention layers to use bias * test bias in gated attention layers * set return_attention_weights to False to avoid multi-outputs Use MultiHeadSelfAttention and MultiHeadGatedSelfAttention if want to return the attention weights * reformat gnns/layers.py This commit adds new message-passing graph layers (MPN) and graph convolutional layers to dt, including vanilla MPN, GRUMPN, Masked-attention FGNN, and GraphTransformer. * Update layers.py * Update test_layers.py * Update models.py * Update test_models.py * Update test_models.py * Fix indexing problems related to tf.gather * Allow multi-inputs in ContinuousGenerator * Fix bad conversion to integer * version bump * Fix phase correction at focus and offset calculation * Fix phase correction in propagation * Fix mie phase out of foucs * Fix mie phase out of foucs * Update README.md * Bm/version 1.4.0 (#137) * Update layers.py * Update convolutional.py Transformer-based models can now be reused and expanded quickly and easily * Update documentation * Update Transformer-based models * Delete classifying_MNIST_vit_tutorial.ipynb * Create classifying_MNIST_vit_tutorial.ipynb * Update datasets.py * Allows kwargs as inputs in single_layer_call * Update embeddings.py * masked transformers * reformat transformer models * Create trajectory_analysis_tutorial.ipynb * Add Variational autoencoders * Add variational autoencoders * Update vae.py * Create MNIST_VAE_tutorial.ipynb * Update MNIST_VAE_tutorial.ipynb * Create folder for course examples * Update README.md * Update README.md * Update examples * Update README.md * Update README.md * Update MNIST VAE examples * Added MLP regression example * Update README.md * Create image_segmentation_Unet.ipynb * Update README.md * Documented and tested cell_counting_tutorial.ipynb * improve dnn example * Shift variant mie * Position mie scatterer correctly * implement set z * implement mnist v1 * implement z dependence * remove logging * Implement flattening methods * Implement pooling and resizing * Implement TensorflowDataset * Finalize MNIST * Implement Malaria classification * alpha0 release * fix batchsize in fit * implement dataset.take * Implement datasets * fix phase in mie * Fix mie positioning and focusing * Commit to new branch * add tensorflow datasets dependence * remove test Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Ccx55 <ccx555@gmail.com> * Add tensorflow datasets to the list of dependencies. * Read requirements.txt into setup.py * remove sphinx from build * remove create badges * Create CITATION.cff * Create .zenodo.json * Update transformer models * Update pint_definition.py * Update requirements.txt * create TimeDistributed CNN * small fixes to lodestar * Update layers.py * Update test_layers.py * remove direct getter of properties * Update scatterers.py Coherence length fix for MieScatterer * Update scatterers.py Added coherence length to the conversion table * mie phase fix * removed pydeepimagej from deps * Change loss input order of CGAN and PCGAN * Create dmdataset (dataset for graph-level regression tasks) * Update gnns/__init__.py * Add detection_linking_hela dataset * Update dmdataset.py * Create the regression_diffusion_landscape * Update scatterers.py CuPy fix for coherence length * Update test_scatterers.py Added a new method for testing MieSphere when coherence length parameter is provided. * Update augmentations.py * Update test_scatterers.py * Update test_scatterers.py * Create endothelial_vs dataset * Update layers.py * Update utils.py * Update docs link * Update README.md * version bump * version bump * Update README.md Co-authored-by: BenjaminMidtvedt <41636530+BenjaminMidtvedt@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Ccx55 <ccx555@gmail.com> Co-authored-by: Harshith Bachimanchi <62615092+HarshithBachimanchi@users.noreply.github.com> Co-authored-by: gideon <gideon.jagenstedt@gmail.com> Co-authored-by: Benjamin Midtvedt <benjamin.midtvedt@physics.gu.se>
giovannivolpe
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* chore: autopublish 2022-07-26T13:54:44Z * Remove create-badges job * Delete test.py * Add multi-head masked attention * Update multi-head gated attention to match parent layer * Update documentation * Test multi-head masked attention * allow gated attention layers to use bias * test bias in gated attention layers * set return_attention_weights to False to avoid multi-outputs Use MultiHeadSelfAttention and MultiHeadGatedSelfAttention if want to return the attention weights * reformat gnns/layers.py This commit adds new message-passing graph layers (MPN) and graph convolutional layers to dt, including vanilla MPN, GRUMPN, Masked-attention FGNN, and GraphTransformer. * Update layers.py * Update test_layers.py * Update models.py * Update test_models.py * Update test_models.py * Fix indexing problems related to tf.gather * Allow multi-inputs in ContinuousGenerator * Fix bad conversion to integer * version bump * Fix phase correction at focus and offset calculation * Fix phase correction in propagation * Fix mie phase out of foucs * Fix mie phase out of foucs * Update README.md * Bm/version 1.4.0 (#137) * Update layers.py * Update convolutional.py Transformer-based models can now be reused and expanded quickly and easily * Update documentation * Update Transformer-based models * Delete classifying_MNIST_vit_tutorial.ipynb * Create classifying_MNIST_vit_tutorial.ipynb * Update datasets.py * Allows kwargs as inputs in single_layer_call * Update embeddings.py * masked transformers * reformat transformer models * Create trajectory_analysis_tutorial.ipynb * Add Variational autoencoders * Add variational autoencoders * Update vae.py * Create MNIST_VAE_tutorial.ipynb * Update MNIST_VAE_tutorial.ipynb * Create folder for course examples * Update README.md * Update README.md * Update examples * Update README.md * Update README.md * Update MNIST VAE examples * Added MLP regression example * Update README.md * Create image_segmentation_Unet.ipynb * Update README.md * Documented and tested cell_counting_tutorial.ipynb * improve dnn example * Shift variant mie * Position mie scatterer correctly * implement set z * implement mnist v1 * implement z dependence * remove logging * Implement flattening methods * Implement pooling and resizing * Implement TensorflowDataset * Finalize MNIST * Implement Malaria classification * alpha0 release * fix batchsize in fit * implement dataset.take * Implement datasets * fix phase in mie * Fix mie positioning and focusing * Commit to new branch * add tensorflow datasets dependence * remove test Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Ccx55 <ccx555@gmail.com> * Add tensorflow datasets to the list of dependencies. * Read requirements.txt into setup.py * remove sphinx from build * remove create badges * Create CITATION.cff * Create .zenodo.json * Update transformer models * Update pint_definition.py * Update requirements.txt * create TimeDistributed CNN * small fixes to lodestar * Update layers.py * Update test_layers.py * remove direct getter of properties * Update scatterers.py Coherence length fix for MieScatterer * Update scatterers.py Added coherence length to the conversion table * mie phase fix * removed pydeepimagej from deps * Change loss input order of CGAN and PCGAN * Create dmdataset (dataset for graph-level regression tasks) * Update gnns/__init__.py * Add detection_linking_hela dataset * Update dmdataset.py * Create the regression_diffusion_landscape * Update scatterers.py CuPy fix for coherence length * Update test_scatterers.py Added a new method for testing MieSphere when coherence length parameter is provided. * Update augmentations.py * Update test_scatterers.py * Update test_scatterers.py * Create endothelial_vs dataset * Update layers.py * Update utils.py * Update docs link * Update README.md * version bump * version bump * Update README.md * Update README.md * Update graphs.py * Update test_generators.py * Update generators.py * fix test * Update vae.py --------- Co-authored-by: BenjaminMidtvedt <41636530+BenjaminMidtvedt@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Ccx55 <ccx555@gmail.com> Co-authored-by: Harshith Bachimanchi <62615092+HarshithBachimanchi@users.noreply.github.com> Co-authored-by: gideon <gideon.jagenstedt@gmail.com> Co-authored-by: Benjamin Midtvedt <benjamin.midtvedt@physics.gu.se>
giovannivolpe
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* chore: autopublish 2022-07-26T13:54:44Z * Remove create-badges job * Delete test.py * Add multi-head masked attention * Update multi-head gated attention to match parent layer * Update documentation * Test multi-head masked attention * allow gated attention layers to use bias * test bias in gated attention layers * set return_attention_weights to False to avoid multi-outputs Use MultiHeadSelfAttention and MultiHeadGatedSelfAttention if want to return the attention weights * reformat gnns/layers.py This commit adds new message-passing graph layers (MPN) and graph convolutional layers to dt, including vanilla MPN, GRUMPN, Masked-attention FGNN, and GraphTransformer. * Update layers.py * Update test_layers.py * Update models.py * Update test_models.py * Update test_models.py * Fix indexing problems related to tf.gather * Allow multi-inputs in ContinuousGenerator * Fix bad conversion to integer * version bump * Fix phase correction at focus and offset calculation * Fix phase correction in propagation * Fix mie phase out of foucs * Fix mie phase out of foucs * Update README.md * Bm/version 1.4.0 (#137) * Update layers.py * Update convolutional.py Transformer-based models can now be reused and expanded quickly and easily * Update documentation * Update Transformer-based models * Delete classifying_MNIST_vit_tutorial.ipynb * Create classifying_MNIST_vit_tutorial.ipynb * Update datasets.py * Allows kwargs as inputs in single_layer_call * Update embeddings.py * masked transformers * reformat transformer models * Create trajectory_analysis_tutorial.ipynb * Add Variational autoencoders * Add variational autoencoders * Update vae.py * Create MNIST_VAE_tutorial.ipynb * Update MNIST_VAE_tutorial.ipynb * Create folder for course examples * Update README.md * Update README.md * Update examples * Update README.md * Update README.md * Update MNIST VAE examples * Added MLP regression example * Update README.md * Create image_segmentation_Unet.ipynb * Update README.md * Documented and tested cell_counting_tutorial.ipynb * improve dnn example * Shift variant mie * Position mie scatterer correctly * implement set z * implement mnist v1 * implement z dependence * remove logging * Implement flattening methods * Implement pooling and resizing * Implement TensorflowDataset * Finalize MNIST * Implement Malaria classification * alpha0 release * fix batchsize in fit * implement dataset.take * Implement datasets * fix phase in mie * Fix mie positioning and focusing * Commit to new branch * add tensorflow datasets dependence * remove test Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Ccx55 <ccx555@gmail.com> * Add tensorflow datasets to the list of dependencies. * Read requirements.txt into setup.py * remove sphinx from build * remove create badges * Create CITATION.cff * Create .zenodo.json * Update transformer models * Update pint_definition.py * Update requirements.txt * create TimeDistributed CNN * small fixes to lodestar * Update layers.py * Update test_layers.py * remove direct getter of properties * Update scatterers.py Coherence length fix for MieScatterer * Update scatterers.py Added coherence length to the conversion table * mie phase fix * removed pydeepimagej from deps * Change loss input order of CGAN and PCGAN * Create dmdataset (dataset for graph-level regression tasks) * Update gnns/__init__.py * Add detection_linking_hela dataset * Update dmdataset.py * Create the regression_diffusion_landscape * Update scatterers.py CuPy fix for coherence length * Update test_scatterers.py Added a new method for testing MieSphere when coherence length parameter is provided. * Update augmentations.py * Update test_scatterers.py * Update test_scatterers.py * Create endothelial_vs dataset * Update layers.py * Update utils.py * Update docs link * Update README.md * version bump * version bump * Update README.md * Update README.md * Update graphs.py * Update test_generators.py * Update generators.py * fix test * Update vae.py * Bugfix in endothelial_vs dataset * Fix issue with repeated oneof-features (#169) * Update cell_migration_analysis.ipynb --------- Co-authored-by: BenjaminMidtvedt <41636530+BenjaminMidtvedt@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Ccx55 <ccx555@gmail.com> Co-authored-by: Harshith Bachimanchi <62615092+HarshithBachimanchi@users.noreply.github.com> Co-authored-by: gideon <gideon.jagenstedt@gmail.com> Co-authored-by: Benjamin Midtvedt <benjamin.midtvedt@physics.gu.se>
giovannivolpe
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Sep 13, 2023
* chore: autopublish 2022-07-26T13:54:44Z * Remove create-badges job * Delete test.py * Add multi-head masked attention * Update multi-head gated attention to match parent layer * Update documentation * Test multi-head masked attention * allow gated attention layers to use bias * test bias in gated attention layers * set return_attention_weights to False to avoid multi-outputs Use MultiHeadSelfAttention and MultiHeadGatedSelfAttention if want to return the attention weights * reformat gnns/layers.py This commit adds new message-passing graph layers (MPN) and graph convolutional layers to dt, including vanilla MPN, GRUMPN, Masked-attention FGNN, and GraphTransformer. * Update layers.py * Update test_layers.py * Update models.py * Update test_models.py * Update test_models.py * Fix indexing problems related to tf.gather * Allow multi-inputs in ContinuousGenerator * Fix bad conversion to integer * version bump * Fix phase correction at focus and offset calculation * Fix phase correction in propagation * Fix mie phase out of foucs * Fix mie phase out of foucs * Update README.md * Bm/version 1.4.0 (#137) * Update layers.py * Update convolutional.py Transformer-based models can now be reused and expanded quickly and easily * Update documentation * Update Transformer-based models * Delete classifying_MNIST_vit_tutorial.ipynb * Create classifying_MNIST_vit_tutorial.ipynb * Update datasets.py * Allows kwargs as inputs in single_layer_call * Update embeddings.py * masked transformers * reformat transformer models * Create trajectory_analysis_tutorial.ipynb * Add Variational autoencoders * Add variational autoencoders * Update vae.py * Create MNIST_VAE_tutorial.ipynb * Update MNIST_VAE_tutorial.ipynb * Create folder for course examples * Update README.md * Update README.md * Update examples * Update README.md * Update README.md * Update MNIST VAE examples * Added MLP regression example * Update README.md * Create image_segmentation_Unet.ipynb * Update README.md * Documented and tested cell_counting_tutorial.ipynb * improve dnn example * Shift variant mie * Position mie scatterer correctly * implement set z * implement mnist v1 * implement z dependence * remove logging * Implement flattening methods * Implement pooling and resizing * Implement TensorflowDataset * Finalize MNIST * Implement Malaria classification * alpha0 release * fix batchsize in fit * implement dataset.take * Implement datasets * fix phase in mie * Fix mie positioning and focusing * Commit to new branch * add tensorflow datasets dependence * remove test Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Ccx55 <ccx555@gmail.com> * Add tensorflow datasets to the list of dependencies. * Read requirements.txt into setup.py * remove sphinx from build * remove create badges * Create CITATION.cff * Create .zenodo.json * Update transformer models * Update pint_definition.py * Update requirements.txt * create TimeDistributed CNN * small fixes to lodestar * Update layers.py * Update test_layers.py * remove direct getter of properties * Update scatterers.py Coherence length fix for MieScatterer * Update scatterers.py Added coherence length to the conversion table * mie phase fix * removed pydeepimagej from deps * Change loss input order of CGAN and PCGAN * Create dmdataset (dataset for graph-level regression tasks) * Update gnns/__init__.py * Add detection_linking_hela dataset * Update dmdataset.py * Create the regression_diffusion_landscape * Update scatterers.py CuPy fix for coherence length * Update test_scatterers.py Added a new method for testing MieSphere when coherence length parameter is provided. * Update augmentations.py * Update test_scatterers.py * Update test_scatterers.py * Create endothelial_vs dataset * Update layers.py * Update utils.py * Update docs link * Update README.md * version bump * version bump * Update README.md * Update README.md * Update graphs.py * Update test_generators.py * Update generators.py * fix test * Update vae.py * Bugfix in endothelial_vs dataset * Fix issue with repeated oneof-features (#169) * Update cell_migration_analysis.ipynb * Update features.py (#189) * added WAE (both MMD and GAN) (#185) * added deterministic wae_gan, slightly modified vae (input size)) * changes to VAE, WAE_GAN, and GAN Implemented proposed changes to GAN, VAE, WAE_GAN: - optimizers of WAE_GAN as input parameters by overriding the compile method. - included documentation of input parameters for VAE and WAE_GAN. - WAE_GAN: different learning rates for the autoencoder and the discriminator, 1e-3 and 5e-4, respectively as in the original paper. - included a unit test for WAE_GAN, VAE, and GAN. - removed @as_KerasModel from GAN. - formatted the code for compatibility. * Update test_models.py * fixed typo * extra fixes * WAE generalized allows WAE-GAN and WAE-MMD * fixes * check unit test * compatibility issue removed match for compatibility, replaced with if * test unit corrected assert in test unit for GAN, VAE. and WAE * fixed dimension in test_models * added compile for GAN and WAE in test_model * defined call in gan * fixed input size in GAN --------- Co-authored-by: BenjaminMidtvedt <41636530+BenjaminMidtvedt@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Jesús Pineda <jesus.pineda@physics.gu.se> Co-authored-by: Benjamin Midtvedt <benmid@student.chalmers.se> Co-authored-by: Jesús Pineda <36273229+JesusPinedaC@users.noreply.github.com> Co-authored-by: Ccx55 <ccx555@gmail.com> Co-authored-by: Harshith Bachimanchi <62615092+HarshithBachimanchi@users.noreply.github.com> Co-authored-by: gideon <gideon.jagenstedt@gmail.com> Co-authored-by: Benjamin Midtvedt <benjamin.midtvedt@physics.gu.se> Co-authored-by: Carlo <carlo.manzo@gmail.com>
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