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!10188 [ms][lite][CPU] tensorlist stack bug 

From: @lzkcode
Reviewed-by: 
Signed-off-by:
This commit is contained in:
mindspore-ci-bot 2020-12-19 15:19:02 +08:00 committed by Gitee
parent 723a56f474 c525b85036
commit ccd83ffa42
3 changed files with 26 additions and 30 deletions
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7
mindspore/lite/src/ops/tensorlist_stack.cc
View File

@ -95,7 +95,7 @@ int TensorListStack::UnPackToFlatBuilder(const schema::Primitive *primitive, fla
MS_LOG(ERROR) << "value_as_TensorListStack return nullptr";
return RET_ERROR;
}
auto val_offset = schema::CreateTensorListStack(*fbb, attr->elementDType(), attr->numElements());
auto val_offset = schema::CreateTensorListStack(*fbb, attr->numElements(), attr->elementDType());
auto prim_offset = schema::CreatePrimitive(*fbb, schema::PrimitiveType_TensorListStack, val_offset.o);
fbb->Finish(prim_offset);
return RET_OK;
@ -159,9 +159,8 @@ int TensorListStack::InferShape(std::vector<lite::Tensor *> inputs_, std::vector
auto output = outputs_.front();
MS_ASSERT(output != nullptr);
output->set_data_type(input0->tensors_data_type());
output->set_shape(std::vector<int>(
1,
input0->ElementsNum() * std::accumulate(output_shape_.begin(), output_shape_.end(), 1LL, std::multiplies<int>())));
output_shape_.insert(output_shape_.begin(), input0->ElementsNum());
output->set_shape(output_shape_);
return RET_OK;
}

2
mindspore/lite/src/runtime/kernel/arm/fp32/tensorlist_setitem_fp32.cc
View File

@ -32,7 +32,7 @@ int TensorListSetItemCPUKernel::Init() { return RET_OK; }
int TensorListSetItemCPUKernel::Run() {
input0_ = reinterpret_cast<lite::TensorList *>(in_tensors_[0]);
if (dtype_ != input0_->data_type()) {
if (dtype_ != input0_->tensors_data_type()) {
MS_LOG(ERROR) << "op dtype:" << dtype_ << " is not equal in_tensors[0] dtype:" << input0_->data_type();
return RET_ERROR;
}

47
mindspore/lite/src/runtime/kernel/arm/fp32/tensorlist_stack_fp32.cc
View File

@ -42,6 +42,16 @@ int TensorListStackCPUKernel::CheckParam() {
return RET_ERROR;
}
num_element_ = input0_->ElementsNum();
if (output0_->shape().size() < 1) {
MS_LOG(ERROR) << "out_tensors_[0].shape().size():" << output0_->shape().size()
<< " must be greater than or equal to 1!";
return RET_ERROR;
}
int dim0 = output0_->shape()[0];
if (dim0 != num_element_) {
MS_LOG(ERROR) << "out_tensors_[0].shape()[0] must be:" << num_element_ << ", but now is:" << dim0;
return RET_ERROR;
}
return RET_OK;
}
@ -50,16 +60,7 @@ int TensorListStackCPUKernel::Init() {
MS_ASSERT(input0_ != nullptr);
output0_ = out_tensors_[0];
MS_ASSERT(output0_ != nullptr);
if (output0_->shape().size() != 2) {
MS_LOG(ERROR) << "out_tensors_[0].shape().size():" << output0_->shape().size() << " must be equal to 2!";
return RET_ERROR;
}
int dim0 = output0_->shape()[0];
if (dim0 != 1) { // dim0 must be 1
MS_LOG(ERROR) << "out_tensors_[0].shape()[0] must be 1, but now is:" << dim0;
return RET_ERROR;
}
return CheckParam();
return RET_OK;
}
bool TensorListStackCPUKernel::IsFullyDefined(const std::vector<int> &shape) const {
@ -129,26 +130,22 @@ int TensorListStackCPUKernel::MergeSubShape(const std::vector<int> &shape) {
}
int TensorListStackCPUKernel::Run() {
if (CheckParam() != RET_OK) {
MS_LOG(ERROR) << "CheckParam failed!";
return RET_ERROR;
}
if (output0_->ElementsNum() == 0) {
return RET_OK;
}
size_t in_ele_num = 0;
for (int i = 0; i < num_element_; ++i) {
auto tensor = input0_->GetTensorIndex(i);
MS_ASSERT(tensor != nullptr);
if (tensor->data_type() == kTypeUnknown) {
if (TypeUnknownSize == 0) {
TypeUnknownSize = MergeElementShape();
}
in_ele_num += TypeUnknownSize;
} else {
in_ele_num += std::accumulate(tensor->shape().begin(), tensor->shape().end(), 1LL, std::multiplies<int>());
}
auto ret = MergeElementShape();
if (ret != RET_OK) {
MS_LOG(ERROR) << "MergeElementShape failed!";
return RET_ERROR;
}
size_t in_ele_num = num_element_ * TypeUnknownSize;
size_t out_ele_num = output0_->ElementsNum();
if (in_ele_num > out_ele_num) {
MS_LOG(ERROR) << "out_tensors_[0]->ElementsNum():" << out_ele_num
<< "must be greater than or equal to in_ele_num:" << in_ele_num;
if (in_ele_num != out_ele_num) {
MS_LOG(ERROR) << "out_tensors_[0]->ElementsNum():" << out_ele_num << "must be equal to in_ele_num:" << in_ele_num;
return RET_ERROR;
}
auto out_ptr = reinterpret_cast<float *>(output0_->MutableData());