1. 06 Nov, 2019 1 commit
    • pedrofreire's avatar
      Simplify and organize test_ops. (#1551) · af225a8a
      pedrofreire authored
      * Simlify and organize test_ops.
      
      We perform the following:
      
      - Simplify the functions slow_roi_pooling, slow_ps_roi_pooling, slow_ps_roi_align and bilinear_interpolate (including finding and removing a semi-bug in slow_ps_roi_pooling, which used bin_w instead of bin_h);
      - Wrote a slow_roi_align function, that was missing;
      - Create a base class testing all combinations of forward/backward, cpu/cuda, contiguous/non-contiguous;
      - Organize all testing inside the base class with _test_forward and _test_backward (which can be easily overriden if a parciular op needs something different); an Op class then only needs to implement fn, get_script_fn, and expected_fn.
      
      A few points:
      - We are using the same inputs for all tests, and not trying all possible inputs in the domain of a given operation. One improvement would be to test more diverse inputs, and to personalize the inputs for some ops (e.g. different inputs for pooling ops and align ops).
      - Running all tests is quite slow (~1 min only for CPU tests), so that can possibly be improved.
      
      * Reduce input size used in gradcheck.
      
      gradcheck can be quite costly, and it was causing OOM errors and making
      the tests slow. By reducing the size of the input, the test speed is
      down to 3 seconds for the CPU tests.
      
      Other points:
      - We remove an unused namedtuple;
      - We inherit from object for better Python 2 compatibility;
      - We remove a hardcoded pool_size from the TorchScript functions, and
      add it as a parameter instead.
      
      * Replace Tensor by torch.Tensor in type annotations.
      
      This should fix lint errors.
      af225a8a
  2. 05 Nov, 2019 1 commit
  3. 21 Oct, 2019 1 commit
  4. 16 Oct, 2019 1 commit
  5. 18 Sep, 2019 1 commit
    • Francisco Massa's avatar
      Remove cpp extensions in favor of torch ops (#1348) · f677ea31
      Francisco Massa authored
      * Remove C++ extensions in favor of custom ops
      
      * Remove unused custom_ops.cpp file
      
      * Rename _custom_ops.py
      
      * Reorganize functions
      
      * Minor improvements and fixes
      
      * Fix lint
      
      * Fully scriptable ops
      
      * Import types used by annotations
      f677ea31
  6. 10 Sep, 2019 1 commit
    • Thomas Viehmann's avatar
      Make custom ops differentiable (#1314) · a91fe722
      Thomas Viehmann authored
      * Make custom ops differentiable
      
      and replace autograd.Function. Use ops unconditionally.
      
      We may consider removing the extension functions in a follow-up.
      
      The code-path is tested by the exisitng tests for differentiability.
      
      * add scripting gradchecks tests and use intlist
      
      * fix implicit tuple conversion for gcc-5
      
      * fix merge
      a91fe722
  7. 14 Jun, 2019 1 commit
  8. 19 May, 2019 1 commit
  9. 07 May, 2019 1 commit
    • Francisco Massa's avatar
      Add C++ ops to torchvision (#826) · dc3ac290
      Francisco Massa authored
      * Initial layout for layers with cpp extensions
      
      * Move files around
      
      * Fix import after move
      
      * Add support for multiple types to ROIAlign
      
      * Different organization
      
      CUDA extensions work now
      
      * Cleanups
      
      * Reduce memory requirements for backwards
      
      * Replace runtime_error by AT_ERROR
      
      * Add nms test
      
      * Add support for compilation using CPP extensions
      
      * Change folder structure
      
      * Add ROIPool cuda
      
      * Cleanups
      
      * Add roi_pool.py
      
      * Fix lint
      
      * Add initial structures folder for bounding boxes
      
      * Assertion macros compatible with pytorch master (#540)
      
      * Support for ROI Pooling (#592)
      
      * 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 (#626)
      
      * Consistent naming for rois variable (#627)
      
      * remove .type().tensor() calls in favor of the new approach to tensor initialization
      
      * Consistent naming for rois variable in ROIPool
      
      * ROIPool: Support for all datatypes (#632)
      
      * 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
      
      * Fix rebase problem
      
      * Remove structures folder
      
      * Improve cleanup and bugfix in test_layers
      
      * Update C++ headers
      
      * Add CUDAGuard to cu files
      
      * Add more checks to layers
      
      * Add CUDA NMS and tests
      
      * Add multi-type support for NMS CUDA
      
      * Avoid using THCudaMalloc
      
      * Add clang-format and reformat c++ code
      
      * Remove THC includes
      
      * Rename layers to ops
      
      * Add documentation and rename functions
      
      * Improve the documentation a bit
      
      * Fix some lint errors
      
      * Fix remaining lint inssues
      
      * Area computation doesn't add +1 in NMS
      
      * Update CI to use PyTorch nightly
      
      * Make NMS return indices sorted according to the score
      
      * Address reviewer comments
      
      * Lint fixes
      
      * Improve doc for roi_align and roi_pool
      
      * move to xenial
      
      * Fix bug pointed by @lopuhin
      
      * Fix RoIPool reference implementation in Python 2
      
      Also fixes a bug in the clip_boxes_to_image -- this function needs a test!
      
      * Remove change in .travis
      dc3ac290