"src/vscode:/vscode.git/clone" did not exist on "9d8943b7e7361e8527fc662d9769707087c4bad6"
- 15 Sep, 2022 1 commit
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Ponku authored
* crestereo draft implementation * minor model fixes. positional embedding changes. * aligned base configuration with paper * Adressing comments * Broke down Adaptive Correlation Layer. Adressed some other commets. * adressed some nits * changed search size, added output channels to model attrs * changed weights naming * changed from iterations to num_iters * removed _make_coords, adressed comments * fixed jit test * config nit * Changed device arg to str Co-authored-by:
Joao Gomes <jdsgomes@fb.com> Co-authored-by:
YosuaMichael <yosuamichaelm@gmail.com>
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- 19 Aug, 2022 1 commit
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Sophia Zhi authored
* S3D initial commit * add model builder code and docstrings * change classifier submodule, populate weights enum * fix change of block args from List[List[int]] to ints * add VideoClassification to transforms * edit weights url for testing, add s3d to models.video init * norm_layer changes * norm_layer and args fix * Overwrite default dropout * Remove docs from internal submodules. * Fix tests * Adding documentation. * Link doc from main models.rst * Fix min_temporal_size * Adding crop/resize parameters in references script * Release weights. * Refactor dropout. * Adding the weights table in the doc Co-authored-by:
Vasilis Vryniotis <datumbox@users.noreply.github.com> Co-authored-by:
Vasilis Vryniotis <vvryniotis@fb.com>
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- 10 Aug, 2022 2 commits
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Local State authored
* init submit * fix typo * support ufmt and mypy * fix 2 unittest errors * fix ufmt issue * Apply suggestions from code review Co-authored-by:
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Vasilis Vryniotis authored
* Extending to support MViTv2 * Fix docs, mypy and linter * Refactor the relative positional code. * Code refactoring. * Rename vars. * Update docs. * Replace assert with exception. * Updat docs. * Minor refactoring. * Remove the square input limitation. * Moving methods around. * Modify the shortcut in the attention layer. * Add ported weights. * Introduce a `residual_cls` config on the attention layer. * Make the patch_embed kernel/padding/stride configurable. * Apply changes from code-review. * Remove stale todo.
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- 24 Jun, 2022 1 commit
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Vasilis Vryniotis authored
* Adding MViT v2 architecture (#6105) * Adding mvitv2 architecture * Fixing memory issues on tests and minor refactorings. * Adding input validation * Adding docs and minor refactoring * Add `min_temporal_size` in the supported meta-data. * Switch Tuple[int, int, int] with List[int] to support easier the 2D case * Adding more docs and references * Change naming conventions of classes to follow the same pattern as MobileNetV3 * Fix test breakage. * Update todos * Performance optimizations. * Add support to MViT v1 (#6179) * Switch implementation to v1 variant. * Fix docs * Adding back a v2 pseudovariant * Changing the way the network are configured. * Temporarily removing v2 * Adding weights. * Expand _squeeze/_unsqueeze to support arbitrary dims. * Update references script. * Fix tests. * Fixing frames and preprocessing. * Fix std/mean values in transforms. * Add permanent Dropout and update the weights. * Update accuracies. * Fix documentation * Remove unnecessary expected file. * Skip big model test * Rewrite the configuration logic to reduce LOC. * Fix mypy
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- 23 Jun, 2022 1 commit
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YosuaMichael authored
* Add rough raft-stereo implementation on prototype/models * Add standard raft_stereo builder, and modify context_encoder to be more similar with original implementation * Follow original implementation on pre-convolve context * Fix to make sure we can load original implementation weight and got same output * reusing component from raft * Make the raft_stereo_fast able to load original weight implementation * Format with ufmt and update some comment * Use raft FlowHead * clean up comments * Remove unnecessary import and use ufmt format * Add __all__ and more docs for RaftStereo class * Only accept param and not module for raft stereo builder * Cleanup comment * Adding typing to raft_stereo * Update some of raft code and reuse on raft stereo * Use bool instead of int * Make standard raft_stereo model jit scriptable * Make the function _make_out_layer using boolean with_block and init the block_layer with identity * Separate corr_block into two modules for pyramid and building corr features * Use tuple if input is not variable size, also remove default value if using List * Format using ufmt and update ConvGRU to not inherit from raft in order to satisfy both jit script and mypy * Change RaftStereo docs input type * Ufmt format raft * revert back convgru to see mypy errors, add test for jit and fx, make the model fx compatible * ufmt format * Specify device for new tensor, dont init module then overwrite and put if-else instead * Ignore mypy problem on override, put back num_iters on forward * Revert some effort to make it fx compatible but unnecessary now * refactor code and remove num_iters from RaftStereo constructor * Change to raft_stereo_realtime, and specify device directly for tensor creation * Add description for raft_stereo_realtime * Update the test for raft_stereo * Fix raft stereo prototype test to properly test jit script * Ufmt format * Test against expected file, change name from raft_stereo to raft_stereo_builder to prevent import error * Revert __init__.py changes * Add default value for non-list param on model builder * Add checking on out_with_block length, add more docs on the encoder * Use base instead of basic since it is more commonly used * rename expect file to base as well * rename on test * Revert the revert of __init__.py, also revert the adding default value to _raft_stereo to follow the standard pattern * ufmt format __init__.py
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- 24 May, 2022 1 commit
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Vasilis Vryniotis authored
* Validate against expected files on videos * Plus tests for autocast
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- 19 May, 2022 2 commits
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Vasilis Vryniotis authored
* Add swin on hubconfig. * Add swin b/s in the `slow_models` list.
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Joao Gomes authored
* add swin_s and swin_b variants * fix swin_b params * fix n parameters and acc numbers * adding missing acc numbers * apply ufmt * Updating `_docs` to reflect training recipe * Fix exted for swin_b Co-authored-by:
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- 09 May, 2022 1 commit
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YosuaMichael authored
* Add resnext101_64x4d model definition * Add test for resnext101_64x4d * Add resnext101_64x4d weight * Update checkpoint to use EMA weigth * Add quantization model signature for resnext101_64x4d * Fix class name and update accuracy using 1 gpu and batch_size=1 * Apply ufmt * Update the quantized weight and accuracy that we still keep the training log * Add quantized expect file * Update docs and fix acc1 * Add recipe for quantized to PR * Update models.rst
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- 28 Apr, 2022 1 commit
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Vasilis Vryniotis authored
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- 27 Apr, 2022 2 commits
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Joao Gomes authored
* Add swin_t to slow list * apply ufmt * update expect for swin_t Co-authored-by: -
Hu Ye authored
* add swin transformer * Update swin_transformer.py * Update swin_transformer.py * fix lint * fix lint * refactor code * add swin_transformer * Update swin_transformer.py * fix bug * refactor code * fix lint * update init_weights * move shift_window into attention * refactor code * fix bug * Update swin_transformer.py * Update swin_transformer.py * fix lint * add patch_merge * fix bug * Update swin_transformer.py * Update swin_transformer.py * Update swin_transformer.py * refactor code * Update swin_transformer.py * refactor code * fix lint * refactor code * add swin_tiny * add swin_tiny.pkl * fix lint * Delete ModelTester.test_swin_tiny_expect.pkl * add swin_tiny * add * add Optional to bias * update init weights * update init_weights and add no weight decay * add no weight decay * add set_weight_decay * add set_weight_decay * fix lint * fix lint * add lr_cos_min * add other swin models * Update torchvision/models/swin_transformer.py Co-authored-by:
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- 05 Apr, 2022 2 commits
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Vasilis Vryniotis authored
* Use frozen BN only if pre-trained. * Add LSJ and ability to from scratch training. * Fixing formatter * Adding `--opt` and `--norm-weight-decay` support in Detection. * Fix error message * Make ScaleJitter proportional. * Adding more norm layers in split_normalization_params. * Add FixedSizeCrop * Temporary fix for fill values on PIL * Fix the bug on fill. * Add RandomShortestSize. * Skip resize when an augmentation method is used. * multiscale in [480, 800] * Add missing star * Add new RetinaNet variant. * Add tests. * Update expected file for old retina * Fixing tests * Add FrozenBN to retinav2 * Fix network initialization issues * Adding BN support in MaskRCNNHeads and FPN * Adding support of FasterRCNNHeads * Introduce norm_layers in backbone utils. * Bigger RPN head + 2x rcnn v2 models. * Adding gIoU support to retinanet * Fix assert * Add back nesterov momentum * Rename and extend `FastRCNNConvFCHead` to support arbitrary FCs * Fix linter
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YosuaMichael authored
* Add vit_b_16_swag * Better handling idiom for image_size, edit test_extended_model to handle case where number of param differ from default due to different image size input * Update the accuracy to the experiment result on torchvision model * Fix typo missing underscore * raise exception instead of torch._assert, add back publication year (accidentally deleted) * Add license information on meta and readme * Improve wording and fix typo for pretrained model license in readme * Add vit_l_16 weight * Update README.rst Co-authored-by:
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- 09 Mar, 2022 1 commit
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Vasilis Vryniotis authored
* Measuring execution times of models. * Speed up models by avoiding re-estimation of eager output * Fixing linter * Reduce input size for big models * Speed up jit check method. * Add simple jitscript fallback check for flaky models. * Restore pytest filtering * Fixing linter
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- 02 Mar, 2022 1 commit
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Vasilis Vryniotis authored
* Extend the EfficientNet class to support v1 and v2. * Refactor config/builder methods and add prototype builders * Refactoring weight info. * Update dropouts based on TF config ref * Update BN eps on TF base_config * Use Conv2dNormActivation. * Adding pre-trained weights for EfficientNetV2-s * Add Medium and Large weights * Update stats with single batch run. * Add accuracies in the docs.
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- 01 Feb, 2022 1 commit
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Vasilis Vryniotis authored
* Refactor model builder * Add 3 more convnext variants. * Adding weights for convnext_small. * Fix minor bug. * Fix number of parameters for small model. * Adding weights for the base variant. * Adding weights for the large variant. * Simplify LayerNorm2d implementation. * Optimize speed of CNBlock. * Repackage weights.
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- 29 Jan, 2022 1 commit
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Yiwen Song authored
* Adding conv_stem support * fix lint * bug fix * address comments * fix after merge * adding back checking lines * fix failing tests * fix iignore * add unittest & address comments * fix memory issue * address comments
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- 23 Jan, 2022 1 commit
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Vasilis Vryniotis authored
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- 21 Jan, 2022 1 commit
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Hu Ye authored
* add fcos * update fcos * add giou_loss * add BoxLinearCoder for FCOS * add full code for FCOS * add giou loss * add fcos * add __all__ * Fixing lint * Fixing lint in giou_loss.py * Add typing annotation to fcos * Add trained checkpoints * Use partial to replace lambda * Minor fixes to docstrings * Apply ufmt format * Fixing docstrings * Fixing jit scripting * Minor fixes to docstrings * Fixing jit scripting * Ignore mypy in fcos * Fixing trained checkpoints * Fixing unit-test of jit script * Fixing docstrings * Add test/expect/ModelTester.test_fcos_resnet50_fpn_expect.pkl * Fixing test_detection_model_trainable_backbone_layers * Update test_fcos_resnet50_fpn_expect.pkl * rename stride to box size * remove TODO and fix some typo * merge some code for better * impove the comments * remove decode and encode of BoxLinearCoder * remove some unnecessary hints * use the default value in detectron2. * update doc * Add unittest for BoxLinearCoder * Add types in FCOS * Add docstring for BoxLinearCoder * Minor fix for the docstring * update doc * Update fcos_resnet50_fpn_coco pretained weights url * Update torchvision/models/detection/fcos.py Co-authored-by:
Zhiqiang Wang <zhiqwang@foxmail.com> * Update torchvision/prototype/models/detection/fcos.py Co-authored-by:
Joao Gomes <joaopsgomes@gmail.com>
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- 20 Jan, 2022 1 commit
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Vasilis Vryniotis authored
* Adding CNBlock and skeleton architecture * Completed implementation. * Adding model in prototypes. * Add test and minor refactor for JIT. * Fix mypy. * Fixing naming conventions. * Fixing tests. * Fix stochastic depth percentages. * Adding stochastic depth to tiny variant. * Minor refactoring and adding comments. * Adding weights. * Update default weights. * Fix transforms issue * Move convnext to prototype. * linter fix * fix docs * Addressing code review comments.
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- 19 Jan, 2022 1 commit
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Yiwen Song authored
* adding vit_h_14 * prototype and docs * bug fix * adding curl check
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- 13 Jan, 2022 1 commit
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Kai Zhang authored
* add regnet_y_128gf * fix test * add expected test file * update regnet factory function, add to prototype as well * write torchscript to temp file instead bytesio in model test * docs * clear GPU memory * no_grad * nit Co-authored-by:
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- 06 Dec, 2021 1 commit
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Nicolas Hug authored
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- 27 Nov, 2021 1 commit
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Yiwen Song authored
* [vit] Adding ViT to torchvision/models * adding pre-logits layer + resolving comments * Fix the model attribute bug * Change version to arch * fix failing unittests * remove useless prints * reduce input size to fix unittests * Increase windows-cpu executor to 2xlarge * Use `batch_first=True` and remove classifier * Change resource_class back to xlarge * Remove vit_h_14 * Remove vit_h_14 from __all__ * Move vision_transformer.py into prototype * Fix formatting issue * remove arch in builder * Fix type err in model builder * address comments and trigger unittests * remove the prototype import in torchvision.models * Adding vit back to models to trigger CircleCI test * fix test_jit_forward_backward * Move all to prototype. * Adopt new helper methods and fix prototype tests. * Remove unused import. Co-authored-by:
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- 20 Oct, 2021 1 commit
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Vasilis Vryniotis authored
* Refactoring resnet_fpn backbone building. * Passing the change to *_rcnn and retinanet. * Applying for faster_rcnn + mobilenetv3 * Applying for ssdlite + mobilenetv3 * Applying for ssd + vgg16 * Update the expected file of retinanet_resnet50_fpn to fix order of initialization. * Adding full model weights for the VGG16 features.
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- 13 Oct, 2021 1 commit
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Joao Gomes authored
* adding tests to check output of quantized models * adding test quantized model weights * merge test_new_quantized_classification_model with test_quantized_classification_model * adding skipif removed by mistake * addressing comments from PR * removing unused argument * fixing lint errors * changing model to eval model and updating weights * Update test/test_models.py Co-authored-by:
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- 29 Sep, 2021 1 commit
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Kai Zhang authored
* initial code * add SqueezeExcitation * initial code * add SqueezeExcitation * add SqueezeExcitation * regnet blocks, stems and model definition * nit * add fc layer * use Callable instead of Enum for block, stem and activation * add regnet_x and regnet_y model build functions, add docs * remove unused depth * use BN/activation constructor and ConvBNActivation * add expected test pkl files * allow custom activation in SqueezeExcitation * use ReLU as the default activation * initial code * add SqueezeExcitation * initial code * add SqueezeExcitation * add SqueezeExcitation * regnet blocks, stems and model definition * nit * add fc layer * use Callable instead of Enum for block, stem and activation * add regnet_x and regnet_y model build functions, add docs * remove unused depth * use BN/activation constructor and ConvBNActivation * reuse SqueezeExcitation from efficientnet * refactor RegNetParams into BlockParams * use nn.init, replace np with torch * update README * construct model with stem, block, classifier instances * Revert "construct model with stem, block, classifier instances" This reverts commit 850f5f3ed01a2a9b36fcbf8405afd6e41d2e58ef. * remove unused blocks * support scaled model * fuse into ConvBNActivation * make reset_parameters private * fix type errors * fix for unit test * add pretrained weights for 6 variant models, update docs
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- 26 Aug, 2021 1 commit
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Vasilis Vryniotis authored
* Adding code skeleton * Adding MBConvConfig. * Extend SqueezeExcitation to support custom min_value and activation. * Implement MBConv. * Replace stochastic_depth with operator. * Adding the rest of the EfficientNet implementation * Update torchvision/models/efficientnet.py * Replacing 1st activation of SE with SiLU. * Adding efficientnet_b3. * Replace mobilenetv3 assets with custom. * Switch to standard sigmoid and reconfiguring BN. * Reconfiguration of efficientnet. * Add repr * Add weights. * Update weights. * Adding B5-B7 weights. * Update docs and hubconf. * Fix doc link. * Fix typo on comment.
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- 06 Aug, 2021 1 commit
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Vincent Moens authored
using nn.init.trunc_normal_ instead of scipy.stats.truncnorm Co-authored-by:Vincent Moens <vmoens@fb.com>
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- 27 May, 2021 1 commit
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Vasilis Vryniotis authored
* Speed up keypoint and retina. * Update keypoint expected file * Speed up fasterrcnn_resnet50_fpn. * Speed up maskrcnn_resnet50_fpn. * Updating params to resolve flakiness. * limit runs to those 4 tests * Relaxing precision to resolve flakiness * Undo test filtering
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- 11 May, 2021 1 commit
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Vasilis Vryniotis authored
* Partial implementation of SSDlite. * Add normal init and BN hyperparams. * Refactor to keep JIT happy * Completed SSDlite. * Fix lint * Update todos * Add expected file in repo. * Use C4 expansion instead of C4 output. * Change scales formula for Default Boxes. * Add cosine annealing on trainer. * Make T_max count epochs. * Fix test and handle corner-case. * Add support of support width_mult * Add ssdlite presets. * Change ReLU6, [-1,1] rescaling, backbone init & no pretraining. * Use _reduced_tail=True. * Add sync BN support. * Adding the best config along with its weights and documentation. * Make mean/std configurable. * Fix not implemented for half exception
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- 30 Apr, 2021 1 commit
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Vasilis Vryniotis authored
* Early skeleton of API. * Adding MultiFeatureMap and vgg16 backbone. * Making vgg16 backbone same as paper. * Making code generic to support all vggs. * Moving vgg's extra layers a separate class + L2 scaling. * Adding header vgg layers. * Fix maxpool patching. * Refactoring code to allow for support of different backbones & sizes: - Skeleton for Default Boxes generator class - Dynamic estimation of configuration when possible - Addition of types * Complete the implementation of DefaultBox generator. * Replace randn with empty. * Minor refactoring * Making clamping between 0 and 1 optional. * Change xywh to xyxy encoding. * Adding parameters and reusing objects in constructor. * Temporarily inherit from Retina to avoid dup code. * Implement forward methods + temp workarounds to inherit from retina. * Inherit more methods from retinanet. * Fix type error. * Add Regression loss. * Fixing JIT issues. * Change JIT workaround to minimize new code. * Fixing initialization bug. * Add classification loss. * Update todos. * Add weight loading support. * Support SSD512. * Change kernel_size to get output size 1x1 * Add xavier init and refactoring. * Adding unit-tests and fixing JIT issues. * Add a test for dbox generator. * Remove unnecessary import. * Workaround on GeneralizedRCNNTransform to support fixed size input. * Remove unnecessary random calls from the test. * Remove more rand calls from the test. * change mapping and handling of empty labels * Fix JIT warnings. * Speed up loss. * Convert 0-1 dboxes to original size. * Fix warning. * Fix tests. * Update comments. * Fixing minor bugs. * Introduce a custom DBoxMatcher. * Minor refactoring * Move extra layer definition inside feature extractor. * handle no bias on init. * Remove fixed image size limitation * Change initialization values for bias of classification head. * Refactoring and update test file. * Adding ResNet backbone. * Minor refactoring. * Remove inheritance of retina and general refactoring. * SSD should fix the input size. * Fixing messages and comments. * Silently ignoring exception if test-only. * Update comments. * Update regression loss. * Restore Xavier init everywhere, update the negative sampling method, change the clipping approach. * Fixing tests. * Refactor to move the losses from the Head to the SSD. * Removing resnet50 ssd version. * Adding support for best performing backbone and its config. * Refactor and clean up the API. * Fix lint * Update todos and comments. * Adding RandomHorizontalFlip and RandomIoUCrop transforms. * Adding necessary checks to our tranforms. * Adding RandomZoomOut. * Adding RandomPhotometricDistort. * Moving Detection transforms to references. * Update presets * fix lint * leave compose and object * Adding scaling for completeness. * Adding params in the repr * Remove unnecessary import. * minor refactoring * Remove unnecessary call. * Give better names to DBox* classes * Port num_anchors estimation in generator * Remove rescaling and fix presets * Add the ability to pass a custom head and refactoring. * fix lint * Fix unit-test * Update todos. * Change mean values. * Change the default parameter of SSD to train the full VGG16 and remove the catch of exception for eval only. * Adding documentation * Adding weights and updating readmes. * Update the model weights with a more performing model. * Adding doc for head. * Restore import.
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- 27 Jan, 2021 1 commit
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Vasilis Vryniotis authored
* Making _segm_resnet() generic and reusable. * Adding fcn and deeplabv3 directly on mobilenetv3 backbone. * Adding tests for segmentation models. * Rename is_strided with _is_cn. * Add dilation support on MobileNetV3 for Segmentation. * Add Lite R-ASPP with MobileNetV3 backbone. * Add pretrained model weights. * Removing model fcn_mobilenet_v3_large. * Adding docs and imports. * Fixing typo and readme.
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- 25 Jan, 2021 1 commit
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Vasilis Vryniotis authored
* Modify segmentation tests compare against expected values. * Exclude flaky autocast tests. Co-authored-by:Francisco Massa <fvsmassa@gmail.com>
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- 19 Jan, 2021 1 commit
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Vasilis Vryniotis authored
* Tag fasterrcnn mobilenetv3 model with 320, add new inference config that makes it 2x faster sacrificing a bit of mAP. * Add a high resolution fasterrcnn mobilenetv3 model. * Update tests and expected values.
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- 18 Jan, 2021 1 commit
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Vasilis Vryniotis authored
* Minor refactoring of a private method to make it reusuable. * Adding a FasterRCNN + MobileNetV3 with & w/o FPN models. * Reducing Resolution to 320-640 and anchor sizes to 16-256. * Increase anchor sizes. * Adding rpn score threshold param on the train script. * Adding trainable_backbone_layers param on the train script. * Adding rpn_score_thresh param directly in fasterrcnn_mobilenet_v3_large_fpn. * Remove fasterrcnn_mobilenet_v3_large prototype and update expected file. * Update documentation and adding weights. * Use buildin Identity. * Fix spelling.
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- 14 Jan, 2021 1 commit
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Vasilis Vryniotis authored
* Add MobileNetV3 Architecture in TorchVision (#3182) * Adding implementation of network architecture * Adding rmsprop support on the train.py * Adding auto-augment and random-erase in the training scripts. * Adding support for reduced tail on MobileNetV3. * Tagging blocks with comments. * Adding documentation, pre-trained model URL and a minor refactoring. * Handling better untrained supported models.
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- 09 Nov, 2020 1 commit
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Vasilis Vryniotis authored
* Change children() to modules() to ensure init happens in all blocks. * Update expected values of all detection models. * Revert "Update expected values of all detection models." This reverts commit 050b64ae * Update expecting values.
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