Layers branch with NMS-GPU #727
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* Add LinearTransformation to docs - Arrange the transforms alphabetically * Add missing transforms to docs
* Add case in test_to_tensor for PIL Images mode '1' * Add support in ToTensor for PIL Images mode '1' * Fix pep8 issues
…ations … (pytorch#481) * fix for PyTorch v0.4 (remove .data and add _ for the initializations in nn.init) * fix m.**.**() style to nn.init.**(**) style * remove .idea * fix lines and indents * fix lines and indents * change to use `kaming_normal_` * add `.data` for safety * add nonlinearity='relu' for sure * fix indents
Remove test with variables
nit: replace 4 by expansion
* Added Progress Bar to the dataset downloading utility * Updated progressbar to update by blcoks * Added progressbar2 to the requirements * fixed style issues * Shifted from progressbar to tqdm
Improve `test_pad_with_non_constant_padding_modes` to avoid data multiplication in `transforms.ToPILImage()` on float data: ```python img = torch.zeros(3, 27, 27) # Float32 img[:, :, 0] = 1 # we add 1 and not 255 img = transforms.ToPILImage()(img) # This converts 1 to 255 due to [pic = pic.mul(255).byte()](https://github.com/pytorch/vision/blob/master/torchvision/transforms/functional.py#L107) ``` and thus test's correct values are [..., 200, 1, 0]
* cifar10.meta['label_names'] * cifar100.meta['fine_label_names'] * cifar100.meta['coarse_label_names']
pytorch#506) This reverts commit 972b80c.
* Add classes metadata to MNIST and FashionMNIST * Add `targets` property to MNIST and FashionMNIST * Add class metadata to CIFAR10/CIFAR100 * Add `targets` property to CIFAR10/CIFAR100 * Add targets attribute to DatasetFolder
* fix a bug described in issue pytorch#488 * improve doc described in issue pytorch#488 * add arguments in RandomCrop as proposed by vfdev-5 in PR pytorch#489
* Fix PIL link * Make normalize more efficient
* make vision depend on pillow-simd if already installed * actually make pillow-simd optional
* Addresses issue pytorch#145 as per @fmessa's suggestion. * Removed blank line for styling.
- Fix broken update calculation - Make progress bar use the neat `unit_scale` feature of tqdm
* reduce tqdm version to 4.19 for py2.7 to avoid spurious error * Update setup.py * Missed = * Update wrong version string
CUDA extensions work now
* ROI Pooling with tests. Fix for cuda context in ROI Align. * renamed bottom and top to follow torch conventions
* remove .type().tensor() calls in favor of the new approach to tensor initialization * Consistent naming for rois variable in ROIPool
* Use of torch7 naming scheme for ROIAlign forward and backward * use common cuda helpers in ROIAlign * use .options() in favor of .type() where applicable * Added tests for forward pass of ROIAlign, as well as more consistent naming scheme for CPU vs CUDA * working ROIAlign cuda backwards pass * working ROIAlign backwards pass for CPU * added relevant headers for ROIAlign backwards * tests for ROIAlign layer * replace .type() with .options() for tensor initialization in ROIAlign layers * support for Half types in ROIAlign * gradcheck tests for ROIAlign * updated ROIPool on CPU to work with all datatypes * updated and cleaned tests for ROI Pooling
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@fmassa the rebase is causing merge conflicts. This PR can merge to master without trouble. |
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Rebased
masterbranch ontolayersbranch and added support for GPU version of NMS.