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!21002 [MS][LITE][STABLE]support NCHW input tensor 

Merge pull request !21002 from chenjianping/kernel_reg
This commit is contained in:
i-robot 2021-08-02 01:29:47 +00:00 committed by Gitee
parent 9720bab9c9 8c52cde0f4
commit 799772455b
21 changed files with 67 additions and 11 deletions
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1
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/errorcode.h
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@ -24,6 +24,7 @@ typedef enum ErrorCodeCommonEnum {
NNACL_PARAM_INVALID,
NNACL_INFER_INVALID,
NNACL_INPUT_TENSOR_ERROR,
NNACL_FORMAT_ERROR,
NNACL_COMMON_END = 9999
} ErrorCodeCommonEnum;

2
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/batch_to_space_infer.c
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@ -122,7 +122,7 @@ int BatchToSpaceInferShape(const TensorC *const *inputs, size_t inputs_size, Ten
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_ERR;
return NNACL_FORMAT_ERROR;
}
SetDataTypeFormat(outputs[0], input);
if (!InferFlag(inputs, inputs_size)) {

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/bn_grad_infer.c
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@ -25,6 +25,9 @@ int BnGradInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC *
}
const TensorC *in = inputs[1];
if (inputs[0]->format_ != Format_NHWC || in->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
const TensorC *scale = inputs[2];
if (in->shape_size_ != 4) {
return NNACL_INPUT_TENSOR_ERROR;

18
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/common_infer.c
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@ -358,6 +358,22 @@ int CommonInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC *
return NNACL_OK;
}
int CommonInferShapeWithNHWC(const TensorC *const *inputs, size_t inputs_size, TensorC **outputs, size_t outputs_size,
OpParameter *parameter) {
if (parameter == NULL || inputs[0] == NULL || outputs[0] == NULL) {
return NNACL_NULL_PTR;
}
if (inputs[0]->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
SetDataTypeFormat(outputs[0], inputs[0]);
if (!InferFlag(inputs, inputs_size)) {
return NNACL_INFER_INVALID;
}
SetShapeTensor(outputs[0], inputs[0]);
return NNACL_OK;
}
int FftInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC **outputs, size_t outputs_size,
const OpParameter *parameter) {
int ret = CheckAugmentWithMinSize(inputs, inputs_size, outputs, outputs_size, parameter, 1, 1);
@ -523,7 +539,7 @@ REG_INFER(LeakyRelu, PrimType_LeakyRelu, CommonInferShape)
REG_INFER(Log, PrimType_Log, CommonInferShape)
REG_INFER(LogGrad, PrimType_LogGrad, CommonInferShape)
REG_INFER(LogicalNot, PrimType_LogicalNot, CommonInferShape)
REG_INFER(LRN, PrimType_LRN, CommonInferShape)
REG_INFER(LRN, PrimType_LRN, CommonInferShapeWithNHWC)
REG_INFER(L2Normalize, PrimType_L2NormalizeFusion, CommonInferShape)
REG_INFER(Neg, PrimType_Neg, CommonInferShape)
REG_INFER(NegGrad, PrimType_NegGrad, CommonInferShape)

5
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/common_infer.h
View File

@ -47,8 +47,11 @@ typedef enum FormatC {
Format_NC4 = 12,
Format_NC4HW4 = 13,
Format_NUM_OF_FORMAT = 14,
Format_NCDHW = 15,
Format_NWC = 16,
Format_NCW = 17,
Format_MIN = Format_NCHW,
Format_MAX = Format_NUM_OF_FORMAT
Format_MAX = Format_NCW
} FormatC;
typedef enum TypeIdC {

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/conv2d_grad_filter_infer.c
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@ -26,6 +26,9 @@ int Conv2dGradFilterInferShape(const TensorC *const *inputs, size_t inputs_size,
if (inputs_size < 3 || outputs_size != 1) {
return NNACL_ERR;
}
if (inputs[0]->format_ != Format_NHWC || inputs[1]->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
SetDataTypeFormat(outputs[0], inputs[0]);
if (inputs[2]->shape_size_ < 1 || inputs[2]->data_ == NULL) {

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/conv2d_grad_input_infer.c
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@ -32,6 +32,9 @@ int Conv2dGradInputInferShape(const TensorC *const *inputs, size_t inputs_size,
if (in0 == NULL || out == NULL) {
return NNACL_NULL_PTR;
}
if (in0->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
SetDataTypeFormat(out, in0);
if (inputs[2]->shape_size_ < 1 || inputs[2]->data_ == NULL) {

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/conv2d_infer.c
View File

@ -62,6 +62,9 @@ int Conv2dInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC *
}
const TensorC *input_tensor = inputs[0];
if (input_tensor->format_ != Format_NHWC && input_tensor->format_ != Format_KHWC) {
return NNACL_FORMAT_ERROR;
}
const TensorC *weight_tensor = inputs[1];
TensorC *out_tensor = outputs[0];

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/deconv2d_infer.c
View File

@ -25,6 +25,9 @@ int Deconv2dInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC
}
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
const TensorC *weight = inputs[1];
TensorC *output = outputs[0];
output->format_ = input->format_;

2
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/depth_to_space_infer.c
View File

@ -26,7 +26,7 @@ int DepthToSpaceInferShape(const TensorC *const *inputs, size_t inputs_size, Ten
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_ERR;
return NNACL_FORMAT_ERROR;
}
SetDataTypeFormat(outputs[0], input);
DepthToSpaceParameter *param = (DepthToSpaceParameter *)parameter;

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/pooling_grad_infer.c
View File

@ -26,6 +26,9 @@ int PoolingGradInferShape(const TensorC *const *inputs, size_t inputs_size, Tens
}
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
int input_h = input->shape_[1];
int input_w = input->shape_[2];
if (input->shape_size_ != 4) {

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/pooling_infer.c
View File

@ -26,6 +26,9 @@ int PoolingInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC
}
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
TensorC *output = outputs[0];
SetDataTypeFormat(output, input);
PoolingParameter *param = (PoolingParameter *)parameter;

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/resize_grad_infer.c
View File

@ -25,6 +25,9 @@ int ResizeGradInferShape(const TensorC *const *inputs, size_t inputs_size, Tenso
}
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
if (input->shape_size_ != 4) {
return NNACL_ERR;
}

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/resize_infer.c
View File

@ -123,6 +123,9 @@ int ResizeInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC *
}
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
TensorC *output = outputs[0];
SetDataTypeFormat(output, input);
if (!InferFlag(inputs, inputs_size)) {

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/roi_pooling_infer.c
View File

@ -28,6 +28,9 @@ int ROIPoolingInferShape(const TensorC *const *inputs, size_t inputs_size, Tenso
}
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
const TensorC *roi = inputs[1];
TensorC *output = outputs[0];
SetDataTypeFormat(output, input);

2
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/space_to_batch_infer.c
View File

@ -26,7 +26,7 @@ int SpaceToBatchInferShape(const TensorC *const *inputs, size_t inputs_size, Ten
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_ERR;
return NNACL_FORMAT_ERROR;
}
SetDataTypeFormat(outputs[0], input);
SpaceToBatchParameter *param = (SpaceToBatchParameter *)parameter;

3
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/space_to_batch_nd_infer.c
View File

@ -21,6 +21,9 @@
int SpaceSetOutputShapeFromParam(const TensorC *const *inputs, size_t inputs_size, TensorC **outputs,
size_t outputs_size, OpParameter *parameter) {
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_FORMAT_ERROR;
}
if (input->shape_size_ != 4) {
return NNACL_ERR;
}

2
mindspore/ccsrc/backend/kernel_compiler/cpu/nnacl/infer/space_to_depth_infer.c
View File

@ -27,7 +27,7 @@ int SpaceToDepthInferShape(const TensorC *const *inputs, size_t inputs_size, Ten
const TensorC *input = inputs[0];
if (input->format_ != Format_NHWC) {
return NNACL_ERR;
return NNACL_FORMAT_ERROR;
}
SetDataTypeFormat(outputs[0], input);
SpaceToDepthParameter *param = (SpaceToDepthParameter *)parameter;

4
mindspore/lite/src/lite_model.cc
View File

@ -278,10 +278,6 @@ bool LiteModel::ModelVerify() const {
MS_LOG(ERROR) << "Tensor in all tensors is nullptr.";
return false;
}
if (tensor->format() != schema::Format_NHWC) {
MS_LOG(ERROR) << "Graph input tensor should be NHWC";
return false;
}
}
if (std::any_of(this->output_indices_.begin(), this->output_indices_.end(),

7
mindspore/lite/src/runtime/infer_manager.cc
View File

@ -67,6 +67,10 @@ int KernelInferShape(const std::vector<lite::Tensor *> &inputs, const std::vecto
int KernelInferShape(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
OpParameter *parameter) {
if (inputs.empty()) {
MS_LOG(ERROR) << "No input!";
return RET_ERROR;
}
std::vector<TensorC *> in_tensors;
std::vector<TensorC *> out_tensors;
if (parameter->type_ == schema::PrimitiveType_PartialFusion || parameter->type_ == schema::PrimitiveType_Switch ||
@ -119,6 +123,9 @@ int KernelInferShape(const std::vector<lite::Tensor *> &inputs, const std::vecto
if (ret == NNACL_INFER_INVALID) {
return RET_INFER_INVALID;
} else if (ret != NNACL_OK) {
if (ret == NNACL_FORMAT_ERROR) {
MS_LOG(ERROR) << "Unexpected input format " << inputs[0]->format();
}
return RET_INFER_ERR;
}
return RET_OK;

2
mindspore/lite/tools/optimizer/fusion/constant_folding_fusion.cc
View File

@ -193,7 +193,7 @@ kernel::LiteKernel *GetLiteKernel(std::vector<Tensor *> inputs, std::vector<Tens
auto ret = KernelInferShape(inputs, *outputs, parameter);
if (ret != lite::RET_OK) {
free(parameter);
MS_LOG(ERROR) << "infershape failed.";
MS_LOG(ERROR) << "infershape failed!type: " << schema::EnumNamePrimitiveType(prim->value_type());
return nullptr;
}
auto data_type = inputs.front()->data_type();