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!39842 pclint_master_fix_1 

Merge pull request !39842 from yao_yf/pclint_master_fix_1
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i-robot 2022-08-08 03:22:57 +00:00 committed by Gitee
parent bbf85a975b 980190a053
commit 95ae98d24c
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GPG Key ID: 173E9B9CA92EEF8F
1 changed files with 25 additions and 24 deletions
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49
mindspore/ccsrc/plugin/device/cpu/kernel/crop_and_resize_grad_boxes_cpu_kernel.cc
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@ -45,7 +45,7 @@ void CropAndResizeGradBoxesCpuKernelMod::InitKernel(const CNodePtr &kernel_node)
MS_LOG(ERROR) << "Boxes tensor is " << input_boxes_shape_len << "-D, but CropAndResizeGradBoxes supports only "
<< kBoxesShapeLen << "-D for boxes tensor.";
}
if (boxes_shape_[1] != kCoordinateLen) {
if (LongToSize(boxes_shape_[1]) != kCoordinateLen) {
MS_LOG(ERROR) << "The coordinate size of boxes is " << boxes_shape_[1]
<< ", but CropAndResizeGradBoxes supports only " << kCoordinateLen << "for boxes.";
}
@ -77,8 +77,8 @@ void CropAndResizeGradBoxesCpuKernelMod::InitKernel(const CNodePtr &kernel_node)
void CropAndResizeGradBoxesCpuKernelMod::OutputZeroing(const std::vector<kernel::AddressPtr> &outputs) {
auto *outputDatas = reinterpret_cast<float *>(outputs[0]->addr);
const int nums_boxes = grads_shape_[0];
int num = nums_boxes * kCoordinateLen;
const int nums_boxes = LongToInt(grads_shape_[0]);
int num = nums_boxes * SizeToInt(kCoordinateLen);
float zero_num = static_cast<float>(0);
for (int i = 0; i < num; i++) {
*(outputDatas + i) = zero_num;
@ -95,15 +95,15 @@ bool CropAndResizeGradBoxesCpuKernelMod::LaunchKernel(const std::vector<kernel::
auto *boxes = reinterpret_cast<float *>(inputs[kBoxes]->addr);
auto *box_ind = reinterpret_cast<int *>(inputs[kBoxIndex]->addr);
auto *outputDatas = reinterpret_cast<float *>(outputs[0]->addr);
const int image_batch = image_shape_[kBatch];
const int image_height = image_shape_[kHeight];
const int image_width = image_shape_[kWidth];
const int depth = image_shape_[kDepth];
const int nums_boxes = grads_shape_[kNumBoxes];
const int crop_height = grads_shape_[kHeight];
const int crop_width = grads_shape_[kWidth];
const int crop_depth = grads_shape_[kDepth];
const int boxesCoordinateNum = boxes_shape_[1];
const int image_batch = LongToInt(image_shape_[kBatch]);
const int image_height = LongToInt(image_shape_[kHeight]);
const int image_width = LongToInt(image_shape_[kWidth]);
const int depth = LongToInt(image_shape_[kDepth]);
const int nums_boxes = LongToInt(grads_shape_[kNumBoxes]);
const int crop_height = LongToInt(grads_shape_[kHeight]);
const int crop_width = LongToInt(grads_shape_[kWidth]);
const int crop_depth = LongToInt(grads_shape_[kDepth]);
const int boxesCoordinateNum = LongToInt(boxes_shape_[1]);
const int num_image2 = image_height * image_width * depth;
const int num_image3 = image_width * depth;
const int num_crop2 = crop_height * crop_width * crop_depth;
@ -129,8 +129,8 @@ bool CropAndResizeGradBoxesCpuKernelMod::LaunchKernel(const std::vector<kernel::
if (y_in < 0 || y_in > image_height - 1) {
continue;
}
const int top_y_index = floorf(y_in);
const int bottom_y_index = ceilf(y_in);
const int top_y_index = FloatToInt(floorf(y_in));
const int bottom_y_index = FloatToInt(ceilf(y_in));
const float y_lerp = y_in - top_y_index;
for (int x = 0; x < crop_width; x++) {
const float x_in =
@ -138,8 +138,8 @@ bool CropAndResizeGradBoxesCpuKernelMod::LaunchKernel(const std::vector<kernel::
if (x_in < 0 || x_in > image_width - 1) {
continue;
}
const int left_x_ind = floorf(x_in);
const int right_x_ind = ceilf(x_in);
const int left_x_ind = FloatToInt(floorf(x_in));
const int right_x_ind = FloatToInt(ceilf(x_in));
const float x_lerp = x_in - left_x_ind;
for (int d = 0; d < depth; d++) {
const float top_left_value(
@ -161,19 +161,20 @@ bool CropAndResizeGradBoxesCpuKernelMod::LaunchKernel(const std::vector<kernel::
image_xgrad_value *= top_grad;
// dy1,dy2
if (crop_height > 1) {
*(outputDatas + b * kCoordinateLen + 0) += image_ygrad_value * (image_height - 1 - y * height_ratio);
*(outputDatas + b * kCoordinateLen + kCoordY2) += image_ygrad_value * (y * height_ratio);
*(outputDatas + IntToSize(b) * kCoordinateLen) += image_ygrad_value * (image_height - 1 - y * height_ratio);
*(outputDatas + IntToSize(b) * kCoordinateLen + kCoordY2) += image_ygrad_value * (y * height_ratio);
} else {
*(outputDatas + b * kCoordinateLen + kCoordY1) += image_ygrad_value * kNum * (image_height - 1);
*(outputDatas + b * kCoordinateLen + kCoordY2) += image_ygrad_value * kNum * (image_height - 1);
*(outputDatas + IntToSize(b) * kCoordinateLen + kCoordY1) += image_ygrad_value * kNum * (image_height - 1);
*(outputDatas + IntToSize(b) * kCoordinateLen + kCoordY2) += image_ygrad_value * kNum * (image_height - 1);
}
// dx1,dx2
if (crop_width > 1) {
*(outputDatas + b * kCoordinateLen + kCoordX1) += image_xgrad_value * (image_width - 1 - x * width_ratio);
*(outputDatas + b * kCoordinateLen + kCoordX2) += image_xgrad_value * (x * width_ratio);
*(outputDatas + IntToSize(b) * kCoordinateLen + kCoordX1) +=
image_xgrad_value * (image_width - 1 - x * width_ratio);
*(outputDatas + IntToSize(b) * kCoordinateLen + kCoordX2) += image_xgrad_value * (x * width_ratio);
} else {
*(outputDatas + b * kCoordinateLen + kCoordX1) += image_xgrad_value * kNum * (image_width - 1);
*(outputDatas + b * kCoordinateLen + kCoordX2) += image_xgrad_value * kNum * (image_width - 1);
*(outputDatas + IntToSize(b) * kCoordinateLen + kCoordX1) += image_xgrad_value * kNum * (image_width - 1);
*(outputDatas + IntToSize(b) * kCoordinateLen + kCoordX2) += image_xgrad_value * kNum * (image_width - 1);
}
}
}