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!13252 [MS][LITE][Develop] fix some problems for gpu ops 

From: @pengyongrong
Reviewed-by: @ddwsky,@zhanghaibo5
Signed-off-by: @ddwsky
This commit is contained in:
mindspore-ci-bot 2021-03-13 11:00:34 +08:00 committed by Gitee
parent 75faccfcdc 1177c11705
commit d8a5b2e06a
7 changed files with 51 additions and 32 deletions
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12
mindspore/lite/src/runtime/kernel/opencl/cl/cast.cl
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@ -8,7 +8,7 @@ __kernel void Cast_fp32_to_fp16(__read_only image2d_t input, __write_only image2
if (x >= XY.x || y >= XY.y) {
return;
}
half4 result = convert_half4(READ_IMAGE(input, smp_none, (int2)(x, y)));
half4 result = convert_half4(read_imagef(input, smp_none, (int2)(x, y)));
write_imageh(output, (int2)(x, y), result);
}
@ -18,8 +18,8 @@ __kernel void Cast_fp32_to_fp32(__read_only image2d_t input, __write_only image2
if (x >= XY.x || y >= XY.y) {
return;
}
float4 result = READ_IMAGE(input, smp_none, (int2)(x, y));
write_imageh(output, (int2)(x, y), result);
float4 result = read_imagef(input, smp_none, (int2)(x, y));
write_imagef(output, (int2)(x, y), result);
}
__kernel void Cast_fp16_to_fp16(__read_only image2d_t input, __write_only image2d_t output, int2 XY) {
@ -28,7 +28,7 @@ __kernel void Cast_fp16_to_fp16(__read_only image2d_t input, __write_only image2
if (x >= XY.x || y >= XY.y) {
return;
}
half4 result = READ_IMAGE(input, smp_none, (int2)(x, y));
half4 result = read_imageh(input, smp_none, (int2)(x, y));
write_imageh(output, (int2)(x, y), result);
}
@ -38,6 +38,6 @@ __kernel void Cast_fp16_to_fp32(__read_only image2d_t input, __write_only image2
if (x >= XY.x || y >= XY.y) {
return;
}
float4 result = convert_float4(READ_IMAGE(input, smp_none, (int2)(x, y)));
write_imageh(output, (int2)(x, y), result);
float4 result = convert_float4(read_imageh(input, smp_none, (int2)(x, y)));
write_imagef(output, (int2)(x, y), result);
}

22
mindspore/lite/src/runtime/kernel/opencl/cl/sparse_to_dense.cl
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@ -10,16 +10,17 @@ __kernel void SparseToDenseScalar(__read_only image2d_t input, __global float *o
return;
}
FLT4 index_input = READ_IMAGE(input, smp_zero, (int2)(Y, X));
int4 index_input_int = *((int4 *)&index_input);
int index = 0;
if (inshapeindex1_dim == 1) {
index = ((int)index_input.x) * stride_w;
index = (index_input_int.x) * stride_w;
} else if (inshapeindex1_dim == 2) {
index = ((int)index_input.x) * stride_w + ((int)index_input.y);
index = (index_input_int.x) * stride_w + (index_input_int.y);
} else if (inshapeindex1_dim == 3) {
index = ((int)index_input.x) * stride_w + ((int)index_input.y) * outputshape.w * C4NUM + ((int)index_input.z);
index = (index_input_int.x) * stride_w + (index_input_int.y) * outputshape.w * C4NUM + (index_input_int.z);
} else {
index = ((int)index_input.x) * outputshape.y * stride_w + ((int)index_input.y) * stride_w +
((int)index_input.z) * outputshape.w * C4NUM + (int)index_input.w;
index = (index_input_int.x) * outputshape.y * stride_w + (index_input_int.y) * stride_w +
(index_input_int.z) * outputshape.w * C4NUM + index_input_int.w;
}
output[index] = weight;
}
@ -33,16 +34,17 @@ __kernel void SparseToDenseVector(__read_only image2d_t input, __global float *o
return;
}
FLT4 index_input = READ_IMAGE(input, smp_zero, (int2)(Y, X));
int4 index_input_int = *((int4 *)&index_input);
int index = 0;
if (inshapeindex1_dim == 1) {
index = ((int)index_input.x) * stride_w;
index = (index_input_int.x) * stride_w;
} else if (inshapeindex1_dim == 2) {
index = ((int)index_input.x) * stride_w + (int)index_input.y;
index = (index_input_int.x) * stride_w + index_input_int.y;
} else if (inshapeindex1_dim == 3) {
index = ((int)index_input.x) * stride_w + ((int)index_input.y) * outputshape.w * C4NUM + (int)index_input.z;
index = (index_input_int.x) * stride_w + (index_input_int.y) * outputshape.w * C4NUM + index_input_int.z;
} else {
index = ((int)index_input.x) * outputshape.y * stride_w + ((int)index_input.y) * stride_w +
((int)index_input.z) * outputshape.w * C4NUM + (int)index_input.w;
index = (index_input_int.x) * outputshape.y * stride_w + (index_input_int.y) * stride_w +
(index_input_int.z) * outputshape.w * C4NUM + index_input_int.w;
}
output[index] = weight_vector[X];
}

4
mindspore/lite/src/runtime/kernel/opencl/kernel/cast.cc
View File

@ -45,16 +45,18 @@ int CastOpenCLKernel::CheckSpecs() {
auto input_dtype = in_tensors_.front()->data_type();
if (input_dtype != kNumberTypeFloat32 && input_dtype != kNumberTypeFloat16) {
MS_LOG(ERROR) << "input dtype must be float32/float16";
return RET_ERROR;
}
auto output_dtype = out_tensors_.front()->data_type();
if (output_dtype != kNumberTypeFloat32 && output_dtype != kNumberTypeFloat16) {
MS_LOG(ERROR) << "output dtype must be float32/float16";
return RET_ERROR;
}
return RET_OK;
}
void CastOpenCLKernel::SetConstArgs() {
cl_int4 shape = {static_cast<int>(shape_.width), static_cast<int>(shape_.height)};
cl_int2 shape = {static_cast<int>(shape_.width), static_cast<int>(shape_.height)};
ocl_runtime_->SetKernelArg(kernel_, 2, shape);
}

4
mindspore/lite/src/runtime/kernel/opencl/kernel/sparse_to_dense.cc
View File

@ -108,10 +108,6 @@ int SparseToDenseOpenCLKernel::CheckSpecs() {
return ERROR;
}
}
if (inshapeindex1_dim > 4) {
MS_LOG(ERROR) << "Unsupported input_indices[1] > 4: ";
return ERROR;
}
auto param = reinterpret_cast<SparseToDenseParameter *>(op_parameter_);
if (param->validate_indices_) {
MS_LOG(ERROR) << "Unsupported unordered for in_tensors_indices";

17
mindspore/lite/src/runtime/kernel/opencl/kernel/split.cc
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@ -59,15 +59,9 @@ int SplitOpenCLKernel::RunAxis0() {
int SplitOpenCLKernel::CheckSpecs() {
auto param = reinterpret_cast<SplitParameter *>(this->op_parameter_);
if (param->split_dim_) {
if (out_tensors_.size() != 2 || in_tensors_.size() != 1) {
MS_LOG(ERROR) << "in size: " << in_tensors_.size() << ", out size: " << out_tensors_.size();
return RET_ERROR;
}
if (param->num_split_ != 2) {
MS_LOG(ERROR) << "num_split_(should be 2): " << param->num_split_;
return RET_ERROR;
}
if ((out_tensors_.size() != 2 || (out_tensors_.size() != 3 && param->split_dim_ == 0)) && in_tensors_.size() != 1) {
MS_LOG(ERROR) << "in size: " << in_tensors_.size() << ", out size: " << out_tensors_.size();
return RET_ERROR;
}
if (in_tensors_.at(0)->IsConst()) {
MS_LOG(ERROR) << "in_tensors_ must be tensor";
@ -79,6 +73,11 @@ int SplitOpenCLKernel::CheckSpecs() {
return RET_ERROR;
}
}
if (param->num_split_ != 2 && (param->num_split_ != 3 && param->split_dim_ == 0)) {
MS_LOG(ERROR) << "num_split_ only supported 2 or (3 && split_dim_ = 0) yet";
return RET_ERROR;
}
if (param->split_dim_ < 0 || param->split_dim_ > 3) {
MS_LOG(ERROR) << "split_dim_ must between 0~3";
return RET_ERROR;

4
mindspore/lite/src/runtime/kernel/opencl/kernel/stack.cc
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@ -67,8 +67,8 @@ void StackGetWorkGroup(const std::vector<size_t> &global, std::vector<size_t> *l
int StackOpenCLKernel::CheckSpecs() {
auto param = reinterpret_cast<StackParameter *>(this->op_parameter_);
axis_ = param->axis_;
if (in_tensors_.size() != 2 && (axis_ != 0)) {
MS_LOG(ERROR) << " only support input size = 2 ";
if (in_tensors_.size() != 2 && out_tensors_.size() != 1) {
MS_LOG(ERROR) << " only support input size = 2 and output size = 1";
return RET_ERROR;
}
if (in_tensors_[0]->shape().size() > 4 || in_tensors_[0]->shape().size() <= 0) {

20
mindspore/lite/test/ut/src/runtime/kernel/opencl/split_tests.cc
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@ -54,4 +54,24 @@ TEST_F(TestOpenCL_Split, input2_axis3) {
fp16_enable, fp16_enable ? 1e-3 : 1e-9);
}
}
TEST_F(TestOpenCL_Split, input3_axis0) {
std::vector<int> input_shape = {8, 1, 1, 1};
std::vector<int> output_shape1 = {2, 1, 1, 1};
std::vector<int> output_shape2 = {3, 1, 1, 1};
std::vector<int> output_shape3 = {3, 1, 1, 1};
int split_dim_ = 0;
int num_split_ = 3; // len of split_sizes_
std::vector<int> split_sizes_{2, 3, 3};
float input_data[] = {0.75, 0.06, 0.74, 0.30, 0.9, 0.59, 0.03, 0.37};
float output_data1[] = {0.75, 0.06};
float output_data2[] = {0.74, 0.30, 0.9};
float output_data3[] = {0.59, 0.03, 0.37};
for (auto fp16_enable : {false}) {
auto *param = CreateParameter(split_dim_, num_split_, split_sizes_);
TestMain({{input_shape, input_data, VAR}},
{{output_shape1, output_data1}, {output_shape2, output_data2}, {output_shape3, output_data3}}, param,
fp16_enable, fp16_enable ? 1e-3 : 1e-9);
}
}
} // namespace mindspore::lite::opencl::test