Shuyue Lan
3ec7b425cf
Signed-off-by: Shuyue Lan <shuyuel@nvidia.com> Signed-off-by: Rajeev Rao <rajeevrao@nvidia.com>
108 lines
3.1 KiB
C++
108 lines
3.1 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "utils.h"
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namespace tensorrt
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{
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namespace utils
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{
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void issueDeprecationWarning(char const* useInstead)
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{
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std::string msg{"Use " + std::string{useInstead} + " instead."};
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py::gil_scoped_acquire acquire{};
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PyErr_WarnEx(PyExc_DeprecationWarning, msg.c_str(), 1);
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}
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// Returns the size in bytes of the specified data type.
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size_t size(nvinfer1::DataType type)
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{
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switch (type)
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{
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case nvinfer1::DataType::kFLOAT: return 4;
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case nvinfer1::DataType::kHALF: return 2;
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case nvinfer1::DataType::kINT8: return 1;
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case nvinfer1::DataType::kINT32: return 4;
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case nvinfer1::DataType::kBOOL: return 1;
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case nvinfer1::DataType::kUINT8: return 1;
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case nvinfer1::DataType::kFP8: return 1;
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}
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return -1;
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}
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// Converts a TRT datatype to its corresponding numpy dtype.
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py::dtype nptype(nvinfer1::DataType type)
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{
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switch (type)
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{
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case nvinfer1::DataType::kFLOAT: return py::dtype("f4");
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case nvinfer1::DataType::kHALF: return py::dtype("f2");
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case nvinfer1::DataType::kINT8: return py::dtype("i1");
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case nvinfer1::DataType::kINT32: return py::dtype("i4");
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case nvinfer1::DataType::kBOOL: return py::dtype("b1");
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case nvinfer1::DataType::kUINT8: return py::dtype("u1");
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case nvinfer1::DataType::kFP8: return py::dtype("f1");
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}
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return py::dtype("unknown");
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}
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nvinfer1::DataType type(py::dtype const& type)
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{
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if (type.is(py::dtype("f4")))
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{
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return nvinfer1::DataType::kFLOAT;
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}
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else if (type.is(py::dtype("f2")))
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{
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return nvinfer1::DataType::kHALF;
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}
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else if (type.is(py::dtype("i4")))
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{
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return nvinfer1::DataType::kINT32;
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}
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else if (type.is(py::dtype("i1")))
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{
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return nvinfer1::DataType::kINT8;
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}
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else if (type.is(py::dtype("b1")))
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{
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return nvinfer1::DataType::kBOOL;
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}
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else if (type.is(py::dtype("u1")))
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{
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return nvinfer1::DataType::kUINT8;
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}
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int32_t constexpr kBITS_PER_BYTE{8};
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std::stringstream ss{};
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ss << "[TRT] [E] Could not implicitly convert NumPy data type: " << type.kind()
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<< (type.itemsize() * kBITS_PER_BYTE) << " to TensorRT.";
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std::cerr << ss.str() << std::endl;
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PY_ASSERT_VALUE_ERROR(false, ss.str());
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return nvinfer1::DataType::kFLOAT;
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}
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void throwPyError(PyObject* type, std::string const& message)
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{
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PyErr_SetString(type, message.data());
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throw py::error_already_set();
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}
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} // namespace utils
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} // namespace tensorrt
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