mindspore-Ecosystem
/
mindspore
21
0
Fork 27
Code Issues Pull Requests 6 Projects Releases Wiki Activity

!6146 Fix bug of quantize operator. 

Merge pull request !6146 from wangshaocong/lite_quant
This commit is contained in:
mindspore-ci-bot 2020-09-14 11:07:31 +08:00 committed by Gitee
parent 07389e408a bc8b9245a2
commit 12f3665167
3 changed files with 24 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
mindspore/lite/src/ops/primitive_c.h
View File

@ -39,7 +39,8 @@ constexpr uint32_t kDoubleNum = 2;
constexpr uint32_t kMultiNum = 3;
constexpr uint32_t kDimension_4d = 4;
const std::set<int> kSupportDataType = {kNumberTypeUInt8, kNumberTypeInt32, kNumberTypeFloat32, kNumberTypeFloat16};
const std::set<int> kSupportDataType = {kNumberTypeUInt8, kNumberTypeInt8, kNumberTypeInt32,
kNumberTypeFloat32, kNumberTypeFloat16};
#ifdef PRIMITIVE_WRITEABLE
using TensorPtr = std::shared_ptr<mindspore::tensor::Tensor>;

1
mindspore/lite/src/runtime/kernel/arm/fp32/cast.cc
View File

@ -147,6 +147,7 @@ kernel::LiteKernel *CpuCastFp32KernelCreator(const std::vector<lite::Tensor *> &
REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_Cast, CpuCastFp32KernelCreator)
REG_KERNEL(kCPU, kNumberTypeUInt8, PrimitiveType_Cast, CpuCastFp32KernelCreator)
REG_KERNEL(kCPU, kNumberTypeInt8, PrimitiveType_Cast, CpuCastFp32KernelCreator)
REG_KERNEL(kCPU, kNumberTypeInt32, PrimitiveType_Cast, CpuCastFp32KernelCreator)
#ifndef ENABLE_ARM64
REG_KERNEL(kCPU, kNumberTypeFloat16, PrimitiveType_Cast, CpuCastFp32KernelCreator)

32
mindspore/lite/tools/converter/parser/tflite/tflite_quantize_parser.cc
View File

@ -36,27 +36,37 @@ STATUS TfliteQuantizeParser::Parse(const std::unique_ptr<tflite::OperatorT> &tfl
return RET_NULL_PTR;
}
std::unique_ptr<schema::QuantDTypeCastT> attr = std::make_unique<schema::QuantDTypeCastT>();
if (attr == nullptr) {
MS_LOG(ERROR) << "new op failed";
return RET_NULL_PTR;
}
const auto &in_tensor = tflite_tensors[tflite_op->inputs[0]];
if (in_tensor == nullptr) {
MS_LOG(ERROR) << "input tensor is null";
return RET_NULL_PTR;
}
attr->srcT = GetTfliteDataType(in_tensor->type);
const auto &out_tensor = tflite_tensors[tflite_op->outputs[0]];
if (out_tensor == nullptr) {
MS_LOG(ERROR) << "output tensor is null";
return RET_NULL_PTR;
}
attr->dstT = GetTfliteDataType(out_tensor->type);
op->primitive->value.type = schema::PrimitiveType_QuantDTypeCast;
op->primitive->value.value = attr.release();
if (GetTfliteDataType(in_tensor->type) != kNumberTypeInt8) {
std::unique_ptr<schema::QuantDTypeCastT> attr = std::make_unique<schema::QuantDTypeCastT>();
if (attr == nullptr) {
MS_LOG(ERROR) << "new op failed";
return RET_NULL_PTR;
}
attr->srcT = GetTfliteDataType(in_tensor->type);
attr->dstT = GetTfliteDataType(out_tensor->type);
op->primitive->value.type = schema::PrimitiveType_QuantDTypeCast;
op->primitive->value.value = attr.release();
} else {
std::unique_ptr<schema::CastT> attr = std::make_unique<schema::CastT>();
if (attr == nullptr) {
MS_LOG(ERROR) << "new op failed";
return RET_NULL_PTR;
}
attr->srcT = GetTfliteDataType(in_tensor->type);
attr->dstT = GetTfliteDataType(out_tensor->type);
op->primitive->value.type = schema::PrimitiveType_Cast;
op->primitive->value.value = attr.release();
}
AddOpInput(op, tensors_id, tensors_format, tensors_id_map, tflite_op->inputs[0], tensors_id->size(),
tflite_tensors.size(), schema::Format_NHWC);