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!3600 Modifying SGD operator bug and adding operator check. 

Merge pull request !3600 from linqingke/new_ops
This commit is contained in:
mindspore-ci-bot 2020-08-03 09:18:09 +08:00 committed by Gitee
parent 6e21618fe1 d54fe5a60a
commit f4ac6a2ccb
5 changed files with 20 additions and 14 deletions
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12
mindspore/ccsrc/backend/kernel_compiler/gpu/arrays/scatter_nd_gpu_kernel.h
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@ -69,7 +69,10 @@ class ScatterNdGpuFwdKernel : public GpuKernel {
memcpy_flag_ = true;
}
ScatterNd(indices, update, output, block_size_, input_size_, output_size_, indices_dim_0_, indices_dim_1_,
const size_t input_size = input_size_ / sizeof(T);
const size_t output_size = output_size_ / sizeof(T);
ScatterNd(indices, update, output, block_size_, input_size, output_size, indices_dim_0_, indices_dim_1_,
indices_stride_, work_shape_, reinterpret_cast<cudaStream_t>(stream_ptr));
return true;
}
@ -138,7 +141,7 @@ class ScatterNdGpuFwdKernel : public GpuKernel {
// calculate indices dim 0/1
indices_dim_0_ = indices_shapes_[0];
indices_dim_1_ = indices_shapes_[1];
indices_dim_1_ = indices_shapes_[indices_shapes_.size() - 1];
// calculate block_size
for (size_t i = indices_dim_1_; i < output_shapes_.size(); i++) {
@ -146,10 +149,7 @@ class ScatterNdGpuFwdKernel : public GpuKernel {
}
// calculate indices_stride
for (size_t i = 0; i < indices_dim_1_; i++) {
vec_indices_stride_.push_back(0);
}
vec_indices_stride_.resize(indices_dim_1_, 0);
vec_indices_stride_[indices_dim_1_ - 1] = block_size_;
for (size_t i = indices_dim_1_ - 1; i > 0; --i) {

6
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/iou_impl.cu
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@ -50,12 +50,12 @@ __global__ void IOUKernel(const size_t size, const T *box1, const T *box2, T *io
T area1 = (location_coordinate[0][2] - location_coordinate[0][0] + 1) * (location_coordinate[0][3] -
location_coordinate[0][1] + 1);
T area2 = (location_coordinate[1][2] - location_coordinate[1][0] + 1) * (location_coordinate[1][3] -
location_coordinate[1][1] + 1);
if (mode == 0) {
T area2 = (location_coordinate[1][2] - location_coordinate[1][0] + 1) * (location_coordinate[1][3] -
location_coordinate[1][1] + 1);
iou_results[i] = overlaps / (area1 + area2 - overlaps + epsilon);
} else {
iou_results[i] = overlaps / (area1 + epsilon);
iou_results[i] = overlaps / (area2 + epsilon);
}
}

6
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/scatter_nd.cu
View File

@ -15,7 +15,9 @@
*/
#include "backend/kernel_compiler/gpu/cuda_impl/scatter_nd.cuh"
#include "backend/kernel_compiler/gpu/cuda_impl/util.cuh"
#include "runtime/device/gpu/cuda_common.h"
template <typename T, typename S>
__global__ void ScatterNdKernel(S *indices, T *update, T *output, const size_t block_size, const size_t input_size,
const size_t output_size, const size_t indices_dim_0, const size_t indices_dim_1,
@ -39,7 +41,7 @@ __global__ void ScatterNdKernel(S *indices, T *update, T *output, const size_t b
out_bound |= write_index >= output_size;
if (!out_bound) {
output[write_index] = update[read_index];
ms_atomic_add(&output[write_index], update[read_index]);
}
}
}
@ -48,7 +50,7 @@ template <typename T, typename S>
void ScatterNd(S *indices, T *update, T *output, const size_t &block_size, const size_t &input_size,
const size_t &output_size, const size_t &indices_dim_0, const size_t &indices_dim_1, S *indices_stride,
S *work_shape, cudaStream_t stream) {
ScatterNdKernel<<<GET_BLOCKS(input_size), GET_THREADS, 0, stream>>>(indices, update, output, block_size, input_size,
ScatterNdKernel<<<GET_BLOCKS(output_size), GET_THREADS, 0, stream>>>(indices, update, output, block_size, input_size,
output_size, indices_dim_0, indices_dim_1,
indices_stride, work_shape);
return;

6
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sgd_impl.cu
View File

@ -22,12 +22,12 @@ __global__ void SGDKernel(const int size, const T dampening, const T weight_deca
const T *momentum, const T *lr, T *param, T *accum, T *stat) {
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < (size); i += blockDim.x * gridDim.x) {
T grad_new = grad[i];
if (weight_decay != static_cast<T>(0)) {
if (weight_decay > static_cast<T>(0)) {
grad_new += param[i] * weight_decay;
}
if (momentum[0] != static_cast<T>(0)) {
if (stat[i] == static_cast<T>(0)) {
if (momentum[0] > static_cast<T>(0)) {
if (stat[i] > static_cast<T>(0)) {
accum[i] = grad_new;
stat[i] = 0;
} else {

4
mindspore/ops/operations/other_ops.py
View File

@ -101,6 +101,8 @@ class BoundingBoxEncode(PrimitiveWithInfer):
def infer_shape(self, anchor_box, groundtruth_box):
validator.check('anchor_box shape[0]', anchor_box[0], 'groundtruth_box shape[0]', groundtruth_box[0], Rel.EQ,
self.name)
validator.check("anchor_box rank", len(anchor_box), "", 2, Rel.EQ, self.name)
validator.check("groundtruth_box rank", len(groundtruth_box), "", 2, Rel.EQ, self.name)
validator.check_integer('anchor_box shape[1]', anchor_box[1], 4, Rel.EQ, self.name)
validator.check_integer('groundtruth_box shape[1]', groundtruth_box[1], 4, Rel.EQ, self.name)
return anchor_box
@ -152,6 +154,8 @@ class BoundingBoxDecode(PrimitiveWithInfer):
def infer_shape(self, anchor_box, deltas):
validator.check('anchor_box shape[0]', anchor_box[0], 'deltas shape[0]', deltas[0], Rel.EQ, self.name)
validator.check("anchor_box rank", len(anchor_box), "", 2, Rel.EQ, self.name)
validator.check("deltas rank", len(deltas), "", 2, Rel.EQ, self.name)
validator.check_integer('anchor_box shape[1]', anchor_box[1], 4, Rel.EQ, self.name)
validator.check_integer('deltas shape[1]', deltas[1], 4, Rel.EQ, self.name)
return anchor_box