Move grid sampler to ATen #9961

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ssnl wants to merge 6 commits into pytorch:master from ssnl:gridsample

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ssnl commented Jul 27, 2018 •

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Spatial version benchmark

	CPUFloat THNN	CPUFloat ATen	CPUDouble THNN	CPUDouble ATen	CUDAHalf THNN	CUDAHalf ATen	CUDAFloat THNN	CUDAFloat ATen	CUDADouble THNN	CUDADouble ATen
[1024x1x28x28] zero pad	2.19281888s	0.21280479s	2.52922535s	0.23944831s	0.17494774s	0.06242800s	0.31270599s	0.03706479s	0.40542483s	0.07391024s
[1024x1x28x28] border pad	3.04329610s	0.24705672s	2.29205394s	0.22336411s	0.17980361s	0.06212497s	0.31415701s	0.03847790s	0.43020391s	0.07540464s
[32x3x244x244] zero pad	18.29301333s	2.18566656s	19.01662397s	3.51552224s	1.72487235s	0.28933954s	2.02466702s	0.18178749s	2.63671613s	0.41391206s
[32x3x244x244] border pad	18.72205329s	2.02600884s	20.13017297s	3.25979590s	1.96455693s	0.33070564s	2.18666625s	0.19546938s	2.91268897s	0.38465047s

basics:

grid tensors have dimensions [N, H, W, 2] (or [N, D, H, W, 3] for 3d).
input/output tensors have dimensions [N, C, H, W] (or [N, C, D, H ,W] for 3d)
grid sampler maps input([N, C, inp_H, inp_W]), grid([N, H, W, 2]) to output([N, C, H, W]) (3d case is similar).

variable naming:

tensor_sH means the stride of tensor at the dimension of H.
tensor_ptr_NCH is a data pointer that always points to the beginning of the tensor[n][c][h] slice in the loop.

ssnl requested review from apaszke, colesbury, ezyang, gchanan, soumith and zdevito as code owners

July 27, 2018 22:28

ssnl force-pushed the gridsample branch 3 times, most recently from 7e0530e to 4e6db58 Compare

July 28, 2018 02:01


          Move spatial grid sampler to ATen

3b249f8

ssnl force-pushed the gridsample branch from 4e6db58 to 3b249f8 Compare

July 28, 2018 02:21

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pjh5 commented Jul 28, 2018

@pytorchbot retest this please

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pjh5 commented Jul 28, 2018

@pytorchbot retest this please


          Move volumetric grid sampler to ATen

afa64bc

ssnl force-pushed the gridsample branch 2 times, most recently from d5afde0 to 767ac6f Compare

July 29, 2018 01:24

ssnl changed the title ~~[WIP] Move grid sampler to ATen~~ [need rocm help] Move grid sampler to ATen


          delete THNN and THCUNN and nn.yaml relevant files/entries

ca91bd9

ssnl force-pushed the gridsample branch from 767ac6f to ca91bd9 Compare

July 29, 2018 03:02


          Use enum class; add notes

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ssnl changed the title ~~[need rocm help] Move grid sampler to ATen~~ Move grid sampler to ATen


          std::floor => ::floor for rocm

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test/test_nn.py

    
                          C = random.randint(1, 8)

                          IH = random.randint(1, 8)

                          IW = random.randint(1, 8)

                          N = random.randint(2, 8)

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aten/src/ATen/native/GridSampler.cpp

    
                          //   (c, iy_nw, ix_nw) * nw + (c, iy_ne, ix_ne) * ne

                          // + (c, iy_sw, ix_sw) * sw + (c, iy_se, ix_se) * se

                          *out_ptr_NCHW = static_cast<scalar_t>(0);

                          if (padding_mode != GridSamplerPadding::Zeros || within_bounds_2d(iy_nw, ix_nw, inp_H, inp_W)) {

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aten/src/ATen/native/cuda/GridSampler.cu Outdated

    
              	  CUDA_KERNEL_LOOP(index, nthreads) {

              	  	const int w = index % out_W;

              	  	const int h = (index / out_W) % out_H;

              	  	const int n = index / (out_H * out_W);

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aten/src/ATen/native/GridSampler.cpp

    
                        giy = giy * (inp_H - 1) / 2;

                        // assuming grad_grid is contiguous

                        gGrid_ptr_NHW[0] = gix;

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aten/src/ATen/native/GridSampler.cpp

    
                                                 GridSamplerInterpolation interpolation_mode,

                                                 GridSamplerPadding padding_mode) {

                  auto grad_input = at::zeros_like(input);

                  auto grad_grid = at::empty_like(grid);

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aten/src/ATen/native/GridSampler.cpp

    
              namespace {

                static inline int64_t clip_coordinates(int64_t in, int64_t clip_limit) {

                  return std::min(clip_limit - 1, std::max(in, static_cast<int64_t>(0)));

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aten/src/ATen/native/GridSampler.cpp

    
                                               int64_t sH, int64_t sW, int64_t H, int64_t W,

                                               scalar_t delta) {

                  if (h >= 0 && h < H && w >= 0 && w < W) {

                    data[h * sH + w * sW] += delta;

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aten/src/ATen/native/GridSampler.cpp

    
                                               GridSamplerPadding padding_mode) {

                  int64_t N = input.size(0);

                  int64_t C = input.size(1);

                  int64_t inp_H = input.size(2);

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This was referenced Jul 31, 2018

[pyHIPIFY] Substitute std::(max|min|ceil|floor) with ::\1 #10045

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Grid sampler: nearest interpolation & reflection padding #10051

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aten/src/ATen/native/GridSampler.cpp

    
                      for (int64_t h = 0; h < out_H; ++h) {

                        for (int64_t w = 0; w < out_W; ++w) {

                          // get the corresponding input x, y, z co-ordinates from grid

                          scalar_t *grid_ptr_NDHW = grid_ptr_N + d * grid_sD + h * grid_sH + w * grid_sW;

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aten/src/ATen/native/cuda/GridSampler.cu Outdated

    
              namespace {

              	static __forceinline__ __device__

              	int clip_coordinates(int in, int clip_limit) {

              	  return ::min(clip_limit - 1, ::max(in, static_cast<int>(0)));

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aten/src/ATen/native/cuda/GridSampler.cu Outdated

    
                void safe_add_2d(scalar_t *data, int h, int w,

                                 int sH, int sW, int H, int W,

                                 scalar_t delta) {

                  if (h >= 0 && h < H && w >= 0 && w < W) {

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aten/src/ATen/native/cuda/GridSampler.cu

    
              	    TensorInfo<scalar_t, int> grad_grid,   // initialized to empty

              	    const GridSamplerPadding padding_mode) {

                  int C = input.sizes[1];

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aten/src/ATen/native/cuda/GridSampler.cu Outdated

    
              	    scalar_t se = (ix    - ix_nw) * (iy    - iy_nw);

              	    // calculate bilinear weighted pixel value and set output pixel

              			if (padding_mode == GridSamplerPadding::Border) {

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aten/src/ATen/native/cuda/GridSampler.cu

    
              	    gix = gix * (inp_W - 1.f) / 2;

              	    giy = giy * (inp_H - 1.f) / 2;

                    // assuming grad_grid is contiguous

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test/test_nn.py

    
                              test_cpu_against_cuda(N, C, H, W, padding_mode)

                              # test channels >1024, which doesn't work on cudnn 7102 and further

                              N, C, H, W = 1, 1025, 3, 3

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ezyang left a comment

Please fix the tabs v. spaces

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cpuhrsch commented Jul 31, 2018

It could be interesting to consider adding the timings to our benchmark library. I'm happy to review or advise etc.


          address comments

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ssnl commented Jul 31, 2018

@cpuhrsch Good idea. Will try to code up a spatial transformer for benchmark. :)

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Collaborator Author

ssnl commented Jul 31, 2018 •

edited

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@ezyang does this look better? :)

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43b1512

zdevito pushed a commit to zdevito/ATen that referenced this pull request


          Move grid sampler to ATen (#9961)

1fea89a

Summary:
Spatial version benchmark

|                           | CPUFloat THNN | CPUFloat ATen | CPUDouble THNN | CPUDouble ATen | CUDAHalf THNN | CUDAHalf ATen | CUDAFloat THNN | CUDAFloat ATen | CUDADouble THNN | CUDADouble ATen |
|---------------------------|---------------|---------------|----------------|----------------|---------------|---------------|----------------|----------------|-----------------|-----------------|
| [1024x1x28x28] zero pad   | 2.19281888s   | 0.21280479s   | 2.52922535s    | 0.23944831s    | 0.17494774s   | 0.06242800s   | 0.31270599s    | 0.03706479s    | 0.40542483s     | 0.07391024s     |
| [1024x1x28x28] border pad | 3.04329610s   | 0.24705672s   | 2.29205394s    | 0.22336411s    | 0.17980361s   | 0.06212497s   | 0.31415701s    | 0.03847790s    | 0.43020391s     | 0.07540464s     |
| [32x3x244x244] zero pad   | 18.29301333s  | 2.18566656s   | 19.01662397s   | 3.51552224s    | 1.72487235s   | 0.28933954s   | 2.02466702s    | 0.18178749s    | 2.63671613s     | 0.41391206s     |
| [32x3x244x244] border pad | 18.72205329s  | 2.02600884s   | 20.13017297s   | 3.25979590s    | 1.96455693s   | 0.33070564s   | 2.18666625s    | 0.19546938s    | 2.91268897s     | 0.38465047s     |

For #9702

basics:
+ grid tensors have dimensions `[N, H, W, 2]` (or `[N, D, H, W, 3]` for 3d).
+ input/output tensors have dimensions `[N, C, H, W]` (or `[N, C, D, H ,W]` for 3d)
+ grid sampler maps `input([N, C, inp_H, inp_W]), grid([N, H, W, 2])` to `output([N, C, H, W])` (3d case is similar).

variable naming:
+ `tensor_sH` means the stride of `tensor` at the dimension of `H`.
+ `tensor_ptr_NCH` is a data pointer that always points to the beginning of the `tensor[n][c][h]` slice in the loop.
Pull Request resolved: pytorch/pytorch#9961

Differential Revision: D9057175

Pulled By: SsnL

fbshipit-source-id: 9ed8f1dc376ed10229f047fdcf3c90dbd250bee6

ssnl deleted the gridsample branch

August 9, 2018 14:11

goodlux pushed a commit to goodlux/pytorch that referenced this pull request


          Move grid sampler to ATen (pytorch#9961)

fa1eb4f

Summary:
Spatial version benchmark

|                           | CPUFloat THNN | CPUFloat ATen | CPUDouble THNN | CPUDouble ATen | CUDAHalf THNN | CUDAHalf ATen | CUDAFloat THNN | CUDAFloat ATen | CUDADouble THNN | CUDADouble ATen |
|---------------------------|---------------|---------------|----------------|----------------|---------------|---------------|----------------|----------------|-----------------|-----------------|
| [1024x1x28x28] zero pad   | 2.19281888s   | 0.21280479s   | 2.52922535s    | 0.23944831s    | 0.17494774s   | 0.06242800s   | 0.31270599s    | 0.03706479s    | 0.40542483s     | 0.07391024s     |
| [1024x1x28x28] border pad | 3.04329610s   | 0.24705672s   | 2.29205394s    | 0.22336411s    | 0.17980361s   | 0.06212497s   | 0.31415701s    | 0.03847790s    | 0.43020391s     | 0.07540464s     |
| [32x3x244x244] zero pad   | 18.29301333s  | 2.18566656s   | 19.01662397s   | 3.51552224s    | 1.72487235s   | 0.28933954s   | 2.02466702s    | 0.18178749s    | 2.63671613s     | 0.41391206s     |
| [32x3x244x244] border pad | 18.72205329s  | 2.02600884s   | 20.13017297s   | 3.25979590s    | 1.96455693s   | 0.33070564s   | 2.18666625s    | 0.19546938s    | 2.91268897s     | 0.38465047s     |

For pytorch#9702

basics:
+ grid tensors have dimensions `[N, H, W, 2]` (or `[N, D, H, W, 3]` for 3d).
+ input/output tensors have dimensions `[N, C, H, W]` (or `[N, C, D, H ,W]` for 3d)
+ grid sampler maps `input([N, C, inp_H, inp_W]), grid([N, H, W, 2])` to `output([N, C, H, W])` (3d case is similar).

variable naming:
+ `tensor_sH` means the stride of `tensor` at the dimension of `H`.
+ `tensor_ptr_NCH` is a data pointer that always points to the beginning of the `tensor[n][c][h]` slice in the loop.
Pull Request resolved: pytorch#9961

Differential Revision: D9057175

Pulled By: SsnL

fbshipit-source-id: 9ed8f1dc376ed10229f047fdcf3c90dbd250bee6

ezyang added open source merged labels

nkaretnikov mentioned this pull request

grid_sampler_3d_backward aborts due to heap corruption #73187

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