diff options
Diffstat (limited to 'compiler/tfkit/src/UnpackCommand.cpp')
| -rw-r--r-- | compiler/tfkit/src/UnpackCommand.cpp | 202 |
1 files changed, 202 insertions, 0 deletions
diff --git a/compiler/tfkit/src/UnpackCommand.cpp b/compiler/tfkit/src/UnpackCommand.cpp new file mode 100644 index 000000000..77ec1edd8 --- /dev/null +++ b/compiler/tfkit/src/UnpackCommand.cpp @@ -0,0 +1,202 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include "UnpackCommand.hpp" +#include "Support.hpp" + +#include <tensorflow/core/framework/graph.pb.h> + +#include <google/protobuf/io/coded_stream.h> +#include <google/protobuf/io/zero_copy_stream_impl.h> +#include <google/protobuf/text_format.h> + +#include <cassert> +#include <stdexcept> + +namespace +{ + +template <typename T> void unpack(tensorflow::TensorProto *); + +template <> void unpack<float>(tensorflow::TensorProto *input_tensor) +{ + const auto &input_shape = input_tensor->tensor_shape(); + assert(input_shape.dim_size() <= 6); + int input_flat_size = tfkit::tf::GetElementCount(input_shape); + + // Adjust where shape is not set but actual value exist + if (input_tensor->tensor_content().size() > 0 && input_flat_size == -1) + { + input_flat_size = input_tensor->tensor_content().size() / sizeof(float); + } + + if (input_tensor->tensor_content().size() == 0) + { + // Do nothing as there is no tensor content to unpack + } + else if (input_tensor->tensor_content().size() == input_flat_size * sizeof(float)) + { + // clang-format off + // TODO fix indentation + input_tensor->clear_float_val(); + + const float *tensor_content = + reinterpret_cast<const float *>(input_tensor->tensor_content().data()); + for (int i = 0; i < input_flat_size; i++) + { + input_tensor->add_float_val(tensor_content[i]); + } + input_tensor->clear_tensor_content(); + // clang-format on + } + else + { + throw std::runtime_error{"Number of elements mismatch in unpack<float>."}; + // TODO: support for these + } +} + +template <> void unpack<int32_t>(tensorflow::TensorProto *input_tensor) +{ + const auto &input_shape = input_tensor->tensor_shape(); + assert(input_shape.dim_size() <= 6); + int input_flat_size = tfkit::tf::GetElementCount(input_shape); + + // Adjust where shape is not set but actual value exist + if (input_tensor->tensor_content().size() > 0 && input_flat_size == -1) + { + input_flat_size = input_tensor->tensor_content().size() / sizeof(int32_t); + } + + if (input_tensor->tensor_content().size() == 0) + { + // Do nothing as there is no tensor content to unpack + } + else if (input_tensor->tensor_content().size() == input_flat_size * sizeof(int32_t)) + { + input_tensor->clear_int_val(); + + const int32_t *tensor_content = + reinterpret_cast<const int32_t *>(input_tensor->tensor_content().data()); + for (int i = 0; i < input_flat_size; i++) + { + input_tensor->add_int_val(tensor_content[i]); + } + input_tensor->clear_tensor_content(); + } + else + { + throw std::runtime_error{"Number of elements mismatch in unpack<int32_t>."}; + // TODO: support for these + } +} + +template <> void unpack<int8_t>(tensorflow::TensorProto *input_tensor) +{ + const auto &input_shape = input_tensor->tensor_shape(); + assert(input_shape.dim_size() <= 6); + int input_flat_size = tfkit::tf::GetElementCount(input_shape); + + // Adjust where shape is not set but actual value exist + if (input_tensor->tensor_content().size() > 0 && input_flat_size == -1) + { + input_flat_size = input_tensor->tensor_content().size() / sizeof(int8_t); + } + + if (input_tensor->tensor_content().size() == 0) + { + // Do nothing as there is no tensor content to unpack + } + else if (input_tensor->tensor_content().size() == input_flat_size * sizeof(int8_t)) + { + input_tensor->clear_int_val(); + + const int8_t *tensor_content = + reinterpret_cast<const int8_t *>(input_tensor->tensor_content().data()); + for (int i = 0; i < input_flat_size; i++) + { + input_tensor->add_int_val(tensor_content[i]); + } + input_tensor->clear_tensor_content(); + } + else + { + throw std::runtime_error{"Number of elements mismatch in unpack<int8_t>."}; + // TODO: support for these + } +} + +void unpack(tensorflow::GraphDef &graph_def) +{ + auto nodes = graph_def.mutable_node(); + for (int i = 0; i < nodes->size(); ++i) + { + tensorflow::NodeDef *n = nodes->Mutable(i); + // TODO: handle for other operators + if (n->op() == "Const") + { + const auto dtype = tfkit::tf::GetDataTypeAttr(*n, "dtype"); + tensorflow::TensorProto *tensor = tfkit::tf::GetTensorAttr(*n, "value"); + + switch (dtype) + { + case tensorflow::DT_FLOAT: + unpack<float>(tensor); + break; + case tensorflow::DT_INT32: + unpack<int32_t>(tensor); + break; + case tensorflow::DT_INT8: + unpack<int8_t>(tensor); + break; + default: + throw std::runtime_error{"Unsupported dtype"}; + } + } + } +} + +} // namespace + +namespace tfkit +{ + +int UnpackCommand::run(int argc, const char *const *argv) const +{ + tensorflow::GraphDef graph_def; + + CmdArguments cmdargs(argc, argv); + + auto ioconfig = make_ioconfig(cmdargs); + + google::protobuf::io::IstreamInputStream is{ioconfig->in()}; + + if (!google::protobuf::TextFormat::Parse(&is, &graph_def)) + { + std::cerr << "ERROR: Failed to parse prototxt" << std::endl; + return 255; + } + + // convert tensor_content to float_val + unpack(graph_def); + + google::protobuf::io::OstreamOutputStream os{ioconfig->out()}; + google::protobuf::TextFormat::Print(graph_def, &os); + + return 0; +} + +} // namespace tfkit |