Fix paddle.vision.ops.deform_conv2d API big Tensor

[xingmingyyj]

PR Category

Operator Mechanism

PR Types

Bug fixes

Description

1. 修复int溢出导致的访存越界问题
2. 修复 CUDA error(9)问题
3. batch较大时存在精度diff

paddle.vision.ops.deform_conv2d(Tensor([5070448, 3, 5, 5],"float32"), Tensor([5070448, 18, 5, 5],"float32"), Tensor([6, 3, 3, 3],"float32"), None, list[1,1,], list[1,1,], list[1,1,], 1, 1, Tensor([5070448, 9, 5, 5],"float32"), ) Not equal to tolerance rtol=0.01, atol=0.01 Tensor-likes are not close! Mismatched elements: 3 / 2281701600 (0.0%) Greatest absolute difference: 0.04030437394976616 at index (1852051, 0, 0, 2) (up to 0.01 allowed) Greatest relative difference: 1.0 at index (910808, 0, 0, 3) (up to 0.01 allowed) ACTUAL: (shape=torch.Size([5070448, 18, 5, 5]), dtype=torch.float32) tensor([[[[ 0.0000e+00, 0.0000e+00, -3.4506e-02, -8.3038e-04, 0.0000e+00], [-8.7802e-04, 3.7523e-03, 1.5622e-02, -8.7787e-04, 5.6141e-03], 

offset的反向传播公式为：
$$\frac{\partial L}{\partial \Delta p_n} = \sum_{p_0} \frac{\partial L}{\partial y(p_0)} \cdot w(p_n) \cdot \frac{\partial x (p_0 + p_n + \Delta p_n)}{\partial \Delta p_n}$$
其中：

• $p_0$:表示采样点。
• $p_n$:表示相对位置。
• $\Delta p_n$:表示偏移量。
• $\frac{\partial x (p_0 + p_n + \Delta p_n)}{\partial \Delta p_n}$:表示双线性插值函数的梯度。
  paddle和torch在计算双线性插值反向时有diff。当点$p_0 + p_n + \Delta p_n$越界时，例如，$p_0 + p_n + \Delta p_n=(-1,0)$, paddle前向直接返回0，反向直接返回0。torch前向直接返回0，但是会给周围没有越界的点回传梯度。对齐torch实现后，精度可以对齐。这里保持了paddle的实现。paddle代码实现位置：https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/phi/kernels/impl/deformable_conv_grad_kernel_impl.h#L62
  ；torch代码实现位置：https://github.com/pytorch/vision/blob/main/torchvision/csrc/ops/cuda/deform_conv2d_kernel.cu#L494。

4. 排除上述问题后，image_shape较大时仍然存在精度diff

test begin: paddle.vision.ops.deform_conv2d(x=Tensor([4, 22817014, 5, 5],"float32"), offset=Tensor([4, 18, 3, 3],"float32"), weight=Tensor([5, 22817014, 3, 3],"float32"), bias=None, stride=list[1,1,], padding=list[0,0,], dilation=list[1,1,], deformable_groups=1, groups=1, mask=Tensor([4, 9, 3, 3],"float32"), ) [accuracy error] backward paddle.vision.ops.deform_conv2d(x=Tensor([4, 22817014, 5, 5],"float32"), offset=Tensor([4, 18, 3, 3],"float32"), weight=Tensor([5, 22817014, 3, 3],"float32"), bias=None, stride=list[1,1,], padding=list[0,0,], dilation=list[1,1,], deformable_groups=1, groups=1, mask=Tensor([4, 9, 3, 3],"float32"), ) Not equal to tolerance rtol=0.01, atol=0.01 Tensor-likes are not close! Mismatched elements: 1833583996 / 2281701400 (80.4%) Greatest absolute difference: 1.451427698135376 at index (3, 22517627, 2, 1) (up to 0.01 allowed) Greatest relative difference: inf at index (1, 13256072, 1, 4) (up to 0.01 allowed) ACTUAL: (shape=torch.Size([4, 22817014, 5, 5]), dtype=torch.float32) tensor([[[[-1.1867e-02, -9.4617e-02, -6.7302e-02, 4.5707e-02, 1.0042e-01], [-1.4820e-03, 5.5286e-03, 2.1573e-02, -7.3028e-03, 7.3889e-02], 

怀疑是Matmul导致，Matmul修复后进行验证。
Pcard-73263

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Codecov Report

❌ Patch coverage is 26.15385% with 48 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (develop@b8b4c24). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
...dle/phi/kernels/cpu/deformable_conv_grad_kernel.cc	0.00%	45 Missing ⚠️
...hi/kernels/impl/deformable_conv_grad_kernel_impl.h	0.00%	3 Missing ⚠️

❌ Your patch status has failed because the patch coverage (26.15%) is below the target coverage (90.00%). You can increase the patch coverage or adjust the target coverage.

Additional details and impacted files

@@ Coverage Diff @@ ## develop #74058 +/- ## ========================================== Coverage ? 26.15% ========================================== Files ? 3 Lines ? 65 Branches ? 0 ========================================== Hits ? 17 Misses ? 48 Partials ? 0 

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[wanghuancoder]

LGTM

[wanghuancoder]

LGTM