forked from tensorflow/tensorflow
-
Notifications
You must be signed in to change notification settings - Fork 1
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Add ExtractExampleParserConfiguration method
- Extract the fixed length and variable length feature configurations output tensor names from a given GraphDef. - This will allow for the use case of bypassing an unnecessary tensorflow.Example serialize/deserialize at serving/inference time by extracting the configuration, running the proto -> tensor helpers directly and feeding the graph with the properly named tensors Change: 122636456
- Loading branch information
1 parent
91615e7
commit 60adf6f
Showing
6 changed files
with
752 additions
and
3 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
160 changes: 160 additions & 0 deletions
160
tensorflow/core/example/example_parser_configuration.cc
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,160 @@ | ||
| /* Copyright 2016 Google Inc. 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 "tensorflow/core/example/example_parser_configuration.h" | ||
|
|
||
| #include <vector> | ||
|
|
||
| #include "tensorflow/core/example/example.pb.h" | ||
| #include "tensorflow/core/example/feature.pb_text.h" | ||
| #include "tensorflow/core/framework/numeric_op.h" | ||
| #include "tensorflow/core/framework/register_types.h" | ||
| #include "tensorflow/core/lib/core/errors.h" | ||
| #include "tensorflow/core/lib/strings/strcat.h" | ||
| #include "tensorflow/core/platform/logging.h" | ||
| #include "tensorflow/core/platform/protobuf.h" | ||
|
|
||
| namespace tensorflow { | ||
|
|
||
| Status FindNodeIndexByName(const tensorflow::GraphDef& graph, | ||
| const string& node_name, int* node_idx) { | ||
| for (int i = 0; i < graph.node_size(); ++i) { | ||
| const auto& node = graph.node(i); | ||
| if (node.name() == node_name) { | ||
| *node_idx = i; | ||
| return Status::OK(); | ||
| } | ||
| } | ||
| return errors::InvalidArgument(node_name, " not found in GraphDef"); | ||
| } | ||
|
|
||
| Status ExtractExampleParserConfiguration( | ||
| const tensorflow::GraphDef& graph, const string& node_name, | ||
| tensorflow::Session* session, | ||
| std::vector<FixedLenFeature>* fixed_len_features, | ||
| std::vector<VarLenFeature>* var_len_features) { | ||
| int node_idx; | ||
| TF_RETURN_IF_ERROR(FindNodeIndexByName(graph, node_name, &node_idx)); | ||
|
|
||
| const auto& node = graph.node(node_idx); | ||
| if (node.op() != "ParseExample") { | ||
| return errors::InvalidArgument(node_name, " node is not a ParseExample op"); | ||
| } | ||
|
|
||
| auto& attr_map = node.attr(); | ||
| auto num_sparse = attr_map.at("Nsparse").i(); | ||
| auto num_dense = attr_map.at("Ndense").i(); | ||
| fixed_len_features->resize(num_dense); | ||
| var_len_features->resize(num_sparse); | ||
|
|
||
| auto tdense = attr_map.at("Tdense"); | ||
| auto dense_shapes = attr_map.at("dense_shapes"); | ||
| auto sparse_types = attr_map.at("sparse_types"); | ||
|
|
||
| // Consistency check attributes. | ||
| if (tdense.list().type_size() != num_dense) { | ||
| return errors::InvalidArgument("Node attr Tdense has ", | ||
| tdense.list().type_size(), | ||
| " elements != Ndense attr: ", num_dense); | ||
| } | ||
|
|
||
| if (dense_shapes.list().shape_size() != num_dense) { | ||
| return errors::InvalidArgument("Node attr dense_shapes has ", | ||
| dense_shapes.list().shape_size(), | ||
| " elements != Ndense attr: ", num_dense); | ||
| } | ||
|
|
||
| if (sparse_types.list().type_size() != num_sparse) { | ||
| return errors::InvalidArgument("Node attr sparse_types has ", | ||
| sparse_types.list().type_size(), | ||
| " elements != NSparse attr: ", num_sparse); | ||
| } | ||
|
|
||
| for (int i = 0; i < tdense.list().type_size(); ++i) { | ||
| (*fixed_len_features)[i].dtype = tdense.list().type(i); | ||
| // Convert TensorShapeProto to TensorShape. | ||
| (*fixed_len_features)[i].shape = TensorShape(dense_shapes.list().shape(i)); | ||
| } | ||
|
|
||
| for (int i = 0; i < sparse_types.list().type_size(); ++i) { | ||
| (*var_len_features)[i].dtype = sparse_types.list().type(i); | ||
| } | ||
|
|
||
| // We must fetch the configuration input tensors to the ParseExample op. | ||
| // Skipping index = 0, which is the serialized proto input. | ||
| std::vector<string> fetch_names(node.input_size() - 1); | ||
| for (int i = 1; i < node.input_size(); ++i) { | ||
| fetch_names[i - 1] = node.input(i); | ||
| } | ||
|
|
||
| std::vector<Tensor> op_input_tensors; | ||
|
|
||
| TF_RETURN_IF_ERROR(session->Run({}, // no_inputs, | ||
| fetch_names, {}, // no target_node_names, | ||
| &op_input_tensors)); | ||
|
|
||
| // The input tensors are laid out sequentially in a flat manner. | ||
| // Here are the various start offsets. | ||
| int sparse_keys_start = 1; | ||
| int dense_keys_start = sparse_keys_start + num_sparse; | ||
| int dense_defaults_start = dense_keys_start + num_dense; | ||
|
|
||
| for (int i = 0; i < num_sparse; ++i) { | ||
| int input_idx = sparse_keys_start + i; | ||
| (*var_len_features)[i].key = op_input_tensors[input_idx].scalar<string>()(); | ||
| } | ||
|
|
||
| for (int i = 0; i < num_dense; ++i) { | ||
| FixedLenFeature& config = (*fixed_len_features)[i]; | ||
| int dense_keys_offset = dense_keys_start + i; | ||
| config.key = op_input_tensors[dense_keys_offset].scalar<string>()(); | ||
|
|
||
| int defaults_offset = dense_defaults_start + i; | ||
| config.default_value = op_input_tensors[defaults_offset]; | ||
| } | ||
|
|
||
| // The output tensors are laid out sequentially in a flat manner. | ||
| // Here are the various start offsets. | ||
| int sparse_indices_output_start = 0; | ||
| int sparse_values_output_start = sparse_indices_output_start + num_sparse; | ||
| int sparse_shapes_output_start = sparse_values_output_start + num_sparse; | ||
| int dense_values_output_start = sparse_shapes_output_start + num_sparse; | ||
|
|
||
| string node_output_prefix = strings::StrCat(node_name, ":"); | ||
|
|
||
| for (int i = 0; i < num_sparse; ++i) { | ||
| VarLenFeature& config = (*var_len_features)[i]; | ||
|
|
||
| int indices_offset = sparse_indices_output_start + i; | ||
| config.indices_output_tensor_name = | ||
| strings::StrCat(node_output_prefix, indices_offset); | ||
|
|
||
| int values_offset = sparse_values_output_start + i; | ||
| config.values_output_tensor_name = | ||
| strings::StrCat(node_output_prefix, values_offset); | ||
|
|
||
| int shapes_offset = sparse_shapes_output_start + i; | ||
| config.shapes_output_tensor_name = | ||
| strings::StrCat(node_output_prefix, shapes_offset); | ||
| } | ||
|
|
||
| for (int i = 0; i < num_dense; ++i) { | ||
| int output_idx = dense_values_output_start + i; | ||
| (*fixed_len_features)[i].values_output_tensor_name = | ||
| strings::StrCat(node_output_prefix, output_idx); | ||
| } | ||
| return Status::OK(); | ||
| } | ||
|
|
||
| } // namespace tensorflow |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,47 @@ | ||
| /* Copyright 2016 Google Inc. 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. | ||
| ==============================================================================*/ | ||
|
|
||
| #ifndef THIRD_PARTY_TENSORFLOW_CORE_EXAMPLE_EXAMPLE_PARSER_CONFIGURATION_H_ | ||
| #define THIRD_PARTY_TENSORFLOW_CORE_EXAMPLE_EXAMPLE_PARSER_CONFIGURATION_H_ | ||
|
|
||
| #include <string> | ||
| #include <vector> | ||
|
|
||
| #include "tensorflow/core/example/example.pb.h" | ||
| #include "tensorflow/core/framework/allocator.h" | ||
| #include "tensorflow/core/framework/graph.pb.h" | ||
| #include "tensorflow/core/framework/tensor.h" | ||
| #include "tensorflow/core/framework/types.h" | ||
| #include "tensorflow/core/platform/types.h" | ||
| #include "tensorflow/core/public/session.h" | ||
| #include "tensorflow/core/util/example_proto_helper.h" | ||
| #include "tensorflow/core/util/sparse/sparse_tensor.h" | ||
|
|
||
| // This is a set of helper methods that will make it possible to share | ||
| // tensorflow::Example proto Tensor conversion code inside the ExampleParserOp | ||
| // OpKernel as well as in external code. | ||
| namespace tensorflow { | ||
|
|
||
| // Given a graph and the node_name of a ParseExample op, | ||
| // extract the FixedLenFeature/VarLenFeature configurations. | ||
| Status ExtractExampleParserConfiguration( | ||
| const tensorflow::GraphDef& graph, const string& node_name, | ||
| tensorflow::Session* session, | ||
| std::vector<FixedLenFeature>* fixed_len_features, | ||
| std::vector<VarLenFeature>* var_len_features); | ||
|
|
||
| } // namespace tensorflow | ||
|
|
||
| #endif // THIRD_PARTY_TENSORFLOW_CORE_EXAMPLE_EXAMPLE_PARSE_CONFIGURATION_H_ |
Oops, something went wrong.