experiments/STT-tensorflow
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Move TRT utility functions from convert_nodes to convert/utils

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This commit is contained in:
Tamas Bela Feher 2019-12-11 16:13:04 +01:00
parent aff962d3b0
commit 2cf2298880
3 changed files with 41 additions and 57 deletions
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49
tensorflow/compiler/tf2tensorrt/convert/convert_nodes.cc
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@ -200,18 +200,6 @@ int64 TFAttrs::get<int64>(const string& key) const {
return this->at(key)->i(); return this->at(key)->i();
} }
template <typename TensorShapeType>
inline nvinfer1::Dims TensorShapeToTrtDims(const TensorShapeType& shape,
bool ignore_first_dim) {
nvinfer1::Dims trt_dims;
const int offset = (ignore_first_dim ? 1 : 0);
for (int i = offset; i < shape.dims(); i++) {
trt_dims.d[i - offset] = shape.dim_size(i);
}
trt_dims.nbDims = shape.dims() - offset;
return trt_dims;
}
template <typename Container> template <typename Container>
Status TensorShapeArrayToTrtDims(const Container& shape, nvinfer1::Dims* out, Status TensorShapeArrayToTrtDims(const Container& shape, nvinfer1::Dims* out,
bool ignore_first_dim = false) { bool ignore_first_dim = false) {
@ -314,21 +302,6 @@ Status ValidateTensorProperties(const string& producer_node_type,
return Status::OK(); return Status::OK();
} }
string DebugString(const nvinfer1::DimensionType type) {
switch (type) {
case nvinfer1::DimensionType::kSPATIAL:
return "kSPATIAL";
case nvinfer1::DimensionType::kCHANNEL:
return "kCHANNEL";
case nvinfer1::DimensionType::kINDEX:
return "kINDEX";
case nvinfer1::DimensionType::kSEQUENCE:
return "kSEQUENCE";
default:
return StrCat(static_cast<int>(type), "=unknown");
}
}
string DebugString(const nvinfer1::DataType trt_dtype) { string DebugString(const nvinfer1::DataType trt_dtype) {
switch (trt_dtype) { switch (trt_dtype) {
case nvinfer1::DataType::kFLOAT: case nvinfer1::DataType::kFLOAT:
@ -344,20 +317,6 @@ string DebugString(const nvinfer1::DataType trt_dtype) {
} }
} }
string DebugString(const nvinfer1::Dims& dims) {
string out = StrCat("nvinfer1::Dims(nbDims=", dims.nbDims, ", d=");
for (int i = 0; i < dims.nbDims; ++i) {
StrAppend(&out, dims.d[i]);
if (VLOG_IS_ON(2)) {
StrAppend(&out, "[", DebugString(dims.type[i]), "],");
} else {
StrAppend(&out, ",");
}
}
StrAppend(&out, ")");
return out;
}
string DebugString(const nvinfer1::Permutation& permutation, int len) { string DebugString(const nvinfer1::Permutation& permutation, int len) {
string out = "nvinfer1::Permutation("; string out = "nvinfer1::Permutation(";
for (int i = 0; i < len; ++i) { for (int i = 0; i < len; ++i) {
@ -581,14 +540,6 @@ inline nvinfer1::Dims GetTrtDimsForTensor(const Tensor& tensor) {
return dims; return dims;
} }
inline bool HasStaticShape(const nvinfer1::Dims& dims) {
if (dims.nbDims < 0) return false;
for (int d = 0; d < dims.nbDims; ++d) {
if (dims.d[d] < 0) return false;
}
return true;
}
int64_t Prod(const nvinfer1::Dims& dims) { int64_t Prod(const nvinfer1::Dims& dims) {
int64_t count = 1; int64_t count = 1;
for (int d = 0; d < dims.nbDims; ++d) { for (int d = 0; d < dims.nbDims; ++d) {

8
tensorflow/compiler/tf2tensorrt/convert/convert_nodes.h
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@ -42,14 +42,6 @@ namespace tensorrt {
namespace convert { namespace convert {
using ::stream_executor::port::StatusOr; using ::stream_executor::port::StatusOr;
#define IS_TRT_VERSION_GE(major, minor, patch, build) \
((NV_TENSORRT_MAJOR > major) || \
(NV_TENSORRT_MAJOR == major && NV_TENSORRT_MINOR > minor) || \
(NV_TENSORRT_MAJOR == major && NV_TENSORRT_MINOR == minor && \
NV_TENSORRT_PATCH > patch) || \
(NV_TENSORRT_MAJOR == major && NV_TENSORRT_MINOR == minor && \
NV_TENSORRT_PATCH == patch && NV_TENSORRT_BUILD >= build))
struct EngineConnection { struct EngineConnection {
// Constructs a non-control edge. // Constructs a non-control edge.
EngineConnection(const string& outside, int out_id, int out_port, EngineConnection(const string& outside, int out_id, int out_port,

41
tensorflow/compiler/tf2tensorrt/convert/utils.h
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@ -17,9 +17,15 @@ limitations under the License.
#define TENSORFLOW_COMPILER_TF2TENSORRT_CONVERT_UTILS_H_ #define TENSORFLOW_COMPILER_TF2TENSORRT_CONVERT_UTILS_H_
#include <memory> #include <memory>
#include <vector>
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/lib/core/status.h" #include "tensorflow/core/lib/core/status.h"
#if GOOGLE_CUDA && GOOGLE_TENSORRT
#include "third_party/tensorrt/NvInfer.h"
#endif // GOOGLE_CUDA && GOOGLE_TENSORRT
namespace tensorflow { namespace tensorflow {
namespace tensorrt { namespace tensorrt {
@ -45,6 +51,41 @@ Status TrtPrecisionModeToName(TrtPrecisionMode mode, string* name);
Status TrtPrecisionModeFromName(const string& name, TrtPrecisionMode* mode); Status TrtPrecisionModeFromName(const string& name, TrtPrecisionMode* mode);
#if GOOGLE_CUDA && GOOGLE_TENSORRT
#define IS_TRT_VERSION_GE(major, minor, patch, build) \
((NV_TENSORRT_MAJOR > major) || \
(NV_TENSORRT_MAJOR == major && NV_TENSORRT_MINOR > minor) || \
(NV_TENSORRT_MAJOR == major && NV_TENSORRT_MINOR == minor && \
NV_TENSORRT_PATCH > patch) || \
(NV_TENSORRT_MAJOR == major && NV_TENSORRT_MINOR == minor && \
NV_TENSORRT_PATCH == patch && NV_TENSORRT_BUILD >= build))
string DebugString(const nvinfer1::DimensionType type);
string DebugString(const nvinfer1::Dims& dims);
inline bool HasStaticShape(const nvinfer1::Dims& dims) {
if (dims.nbDims < 0) return false;
for (int d = 0; d < dims.nbDims; ++d) {
if (dims.d[d] < 0) return false;
}
return true;
}
template <typename TensorShapeType>
inline nvinfer1::Dims TensorShapeToTrtDims(const TensorShapeType& shape,
bool ignore_first_dim) {
nvinfer1::Dims trt_dims;
const int offset = (ignore_first_dim ? 1 : 0);
for (int i = offset; i < shape.dims(); i++) {
trt_dims.d[i - offset] = shape.dim_size(i);
}
trt_dims.nbDims = shape.dims() - offset;
return trt_dims;
}
#endif // GOOGLE_CUDA && GOOGLE_TENSORRT
} // namespace tensorrt } // namespace tensorrt
} // namespace tensorflow } // namespace tensorflow