ROIPool: Support for all datatypes #632
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…naming scheme for CPU vs CUDA
varunagrawal
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* 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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* 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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Mar 31, 2019
* 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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* 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
fmassa
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May 7, 2019
* 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
fmassa
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* 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
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ROIPoollayer so it now supports all datatypes instead of just float.ROIPool.