experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Separate model.cc into model_builder.cc and interpreter_builder.cc.

Browse Source 
PiperOrigin-RevId: 302570223
Change-Id: I9b26c21dc7db0a1fb225986db20b1ed66f6fcc82
This commit is contained in:
Nupur Garg 2020-03-23 19:05:36 -07:00 committed by TensorFlower Gardener
parent e918c6e6fa
commit dcf212b2a5
6 changed files with 496 additions and 378 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
tensorflow/lite/BUILD
View File

@ -72,6 +72,8 @@ FRAMEWORK_LIB_HDRS = [
"graph_info.h",
"interpreter.h",
"model.h",
"model_builder.h",
"interpreter_builder.h",
"mutable_op_resolver.h",
"op_resolver.h",
"optional_debug_tools.h",
@ -222,7 +224,8 @@ cc_library(
"core/subgraph.cc",
"graph_info.cc",
"interpreter.cc",
"model.cc",
"interpreter_builder.cc",
"model_builder.cc",
"mutable_op_resolver.cc",
"optional_debug_tools.cc",
"stderr_reporter.cc",

160
tensorflow/lite/model.cc → tensorflow/lite/interpreter_builder.cc
View File

@ -12,7 +12,7 @@ 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/lite/model.h"
#include "tensorflow/lite/interpreter_builder.h"
#include <fcntl.h>
#include <stdint.h>
@ -37,6 +37,7 @@ limitations under the License.
namespace tflite {
namespace {
// Ensure that ErrorReporter is non-null.
ErrorReporter* ValidateErrorReporter(ErrorReporter* e) {
return e ? e : DefaultErrorReporter();
@ -91,6 +92,7 @@ TfLiteStatus ParseSparseIndexVector(const DimensionMetadata* src,
}
return kTfLiteError;
}
} // namespace
const char* kEmptyTensorName = "";
@ -114,162 +116,6 @@ __attribute__((weak)) Interpreter::TfLiteDelegatePtr AcquireFlexDelegate() {
Interpreter::TfLiteDelegatePtr (*AcquireFlexDelegate)() = nullptr;
#endif
#ifndef TFLITE_MCU
// Loads a model from `filename`. If `mmap_file` is true then use mmap,
// otherwise make a copy of the model in a buffer.
std::unique_ptr<Allocation> GetAllocationFromFile(const char* filename,
bool mmap_file,
ErrorReporter* error_reporter,
bool use_nnapi) {
std::unique_ptr<Allocation> allocation;
if (mmap_file && MMAPAllocation::IsSupported()) {
allocation.reset(new MMAPAllocation(filename, error_reporter));
} else {
allocation.reset(new FileCopyAllocation(filename, error_reporter));
}
return allocation;
}
std::unique_ptr<FlatBufferModel> FlatBufferModel::BuildFromFile(
const char* filename, ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
std::unique_ptr<FlatBufferModel> model;
auto allocation = GetAllocationFromFile(filename, /*mmap_file=*/true,
error_reporter, /*use_nnapi=*/true);
model.reset(new FlatBufferModel(std::move(allocation), error_reporter));
if (!model->initialized()) model.reset();
return model;
}
std::unique_ptr<FlatBufferModel> FlatBufferModel::VerifyAndBuildFromFile(
const char* filename, TfLiteVerifier* extra_verifier,
ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
std::unique_ptr<FlatBufferModel> model;
auto allocation = GetAllocationFromFile(filename, /*mmap_file=*/true,
error_reporter, /*use_nnapi=*/true);
flatbuffers::Verifier base_verifier(
reinterpret_cast<const uint8_t*>(allocation->base()),
allocation->bytes());
if (!VerifyModelBuffer(base_verifier)) {
TF_LITE_REPORT_ERROR(error_reporter,
"The model is not a valid Flatbuffer file");
return nullptr;
}
if (extra_verifier &&
!extra_verifier->Verify(static_cast<const char*>(allocation->base()),
allocation->bytes(), error_reporter)) {
return model;
}
model.reset(new FlatBufferModel(std::move(allocation), error_reporter));
if (!model->initialized()) model.reset();
return model;
}
#endif
std::unique_ptr<FlatBufferModel> FlatBufferModel::BuildFromBuffer(
const char* caller_owned_buffer, size_t buffer_size,
ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
std::unique_ptr<FlatBufferModel> model;
std::unique_ptr<Allocation> allocation(
new MemoryAllocation(caller_owned_buffer, buffer_size, error_reporter));
model.reset(new FlatBufferModel(std::move(allocation), error_reporter));
if (!model->initialized()) model.reset();
return model;
}
std::unique_ptr<FlatBufferModel> FlatBufferModel::VerifyAndBuildFromBuffer(
const char* caller_owned_buffer, size_t buffer_size,
TfLiteVerifier* extra_verifier, ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
flatbuffers::Verifier base_verifier(
reinterpret_cast<const uint8_t*>(caller_owned_buffer), buffer_size);
if (!VerifyModelBuffer(base_verifier)) {
TF_LITE_REPORT_ERROR(error_reporter,
"The model is not a valid Flatbuffer buffer");
return nullptr;
}
if (extra_verifier && !extra_verifier->Verify(caller_owned_buffer,
buffer_size, error_reporter)) {
return nullptr;
}
return BuildFromBuffer(caller_owned_buffer, buffer_size, error_reporter);
}
std::unique_ptr<FlatBufferModel> FlatBufferModel::BuildFromModel(
const tflite::Model* caller_owned_model_spec,
ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
std::unique_ptr<FlatBufferModel> model;
model.reset(new FlatBufferModel(caller_owned_model_spec, error_reporter));
if (!model->initialized()) model.reset();
return model;
}
string FlatBufferModel::GetMinimumRuntime() const {
if (!model_ || !model_->metadata()) return "";
for (int i = 0; i < model_->metadata()->size(); ++i) {
auto metadata = model_->metadata()->Get(i);
if (metadata->name()->str() == "min_runtime_version") {
auto buf = metadata->buffer();
auto* buffer = (*model_->buffers())[buf];
auto* array = buffer->data();
// Get the real length of the runtime string, since there might be
// trailing
// '\0's in the buffer.
for (int len = 0; len < array->size(); ++len) {
if (array->data()[len] == '\0') {
return string(reinterpret_cast<const char*>(array->data()), len);
}
}
// If there is no '\0' in the buffer, this indicates that the flatbuffer
// is malformed.
TF_LITE_REPORT_ERROR(
error_reporter_,
"Min_runtime_version in model metadata is malformed");
break;
}
}
return "";
}
bool FlatBufferModel::CheckModelIdentifier() const {
if (!tflite::ModelBufferHasIdentifier(allocation_->base())) {
const char* ident = flatbuffers::GetBufferIdentifier(allocation_->base());
error_reporter_->Report(
"Model provided has model identifier '%c%c%c%c', should be '%s'\n",
ident[0], ident[1], ident[2], ident[3], tflite::ModelIdentifier());
return false;
}
return true;
}
FlatBufferModel::FlatBufferModel(const Model* model,
ErrorReporter* error_reporter)
: model_(model), error_reporter_(ValidateErrorReporter(error_reporter)) {}
FlatBufferModel::FlatBufferModel(std::unique_ptr<Allocation> allocation,
ErrorReporter* error_reporter)
: error_reporter_(ValidateErrorReporter(error_reporter)),
allocation_(std::move(allocation)) {
if (!allocation_->valid() || !CheckModelIdentifier()) return;
model_ = ::tflite::GetModel(allocation_->base());
}
FlatBufferModel::~FlatBufferModel() {}
namespace impl {
InterpreterBuilder::InterpreterBuilder(const FlatBufferModel& model,

104
tensorflow/lite/interpreter_builder.h Normal file
View File

@ -0,0 +1,104 @@
/* Copyright 2017 The TensorFlow Authors. 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.
==============================================================================*/
/// Deserialization infrastructure for tflite. Provides functionality
/// to go from a serialized tflite model in flatbuffer format to an
/// interpreter.
///
#ifndef TENSORFLOW_LITE_INTERPRETER_BUILDER_H_
#define TENSORFLOW_LITE_INTERPRETER_BUILDER_H_
#include <memory>
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/core/api/error_reporter.h"
#include "tensorflow/lite/core/api/op_resolver.h"
#include "tensorflow/lite/interpreter.h"
#include "tensorflow/lite/model_builder.h"
#include "tensorflow/lite/mutable_op_resolver.h"
#include "tensorflow/lite/schema/schema_generated.h"
namespace tflite {
namespace impl {
/// Build an interpreter capable of interpreting `model`.
///
/// model: A model whose lifetime must be at least as long as any
/// interpreter(s) created by the builder. In principle multiple interpreters
/// can be made from a single model.
/// op_resolver: An instance that implements the OpResolver interface, which
/// maps
/// custom op names and builtin op codes to op registrations. The lifetime
/// of the provided `op_resolver` object must be at least as long as the
/// InterpreterBuilder; unlike `model` and `error_reporter`, the `op_resolver`
/// does not need to exist for the duration of any created Interpreter
/// objects.
/// error_reporter: a functor that is called to report errors that handles
/// printf var arg semantics. The lifetime of the `error_reporter` object must
/// be greater than or equal to the Interpreter created by operator().
///
/// Returns a kTfLiteOk when successful and sets interpreter to a valid
/// Interpreter. Note: The user must ensure the model lifetime (and error
/// reporter, if provided) is at least as long as interpreter's lifetime.
class InterpreterBuilder {
public:
InterpreterBuilder(const FlatBufferModel& model,
const OpResolver& op_resolver);
/// Builds an interpreter given only the raw flatbuffer Model object (instead
/// of a FlatBufferModel). Mostly used for testing.
/// If `error_reporter` is null, then DefaultErrorReporter() is used.
InterpreterBuilder(const ::tflite::Model* model,
const OpResolver& op_resolver,
ErrorReporter* error_reporter = DefaultErrorReporter());
~InterpreterBuilder();
InterpreterBuilder(const InterpreterBuilder&) = delete;
InterpreterBuilder& operator=(const InterpreterBuilder&) = delete;
TfLiteStatus operator()(std::unique_ptr<Interpreter>* interpreter);
TfLiteStatus operator()(std::unique_ptr<Interpreter>* interpreter,
int num_threads);
private:
TfLiteStatus BuildLocalIndexToRegistrationMapping();
TfLiteStatus ParseNodes(
const flatbuffers::Vector<flatbuffers::Offset<Operator>>* operators,
Subgraph* subgraph);
TfLiteStatus ParseTensors(
const flatbuffers::Vector<flatbuffers::Offset<Buffer>>* buffers,
const flatbuffers::Vector<flatbuffers::Offset<Tensor>>* tensors,
Subgraph* subgraph);
TfLiteStatus ApplyDelegates(Interpreter* interpreter);
TfLiteStatus ParseQuantization(const QuantizationParameters* src_quantization,
TfLiteQuantization* quantization,
const std::vector<int>& dims);
TfLiteStatus ParseSparsity(const SparsityParameters* src_sparsity,
TfLiteSparsity** sparsity);
const ::tflite::Model* model_;
const OpResolver& op_resolver_;
ErrorReporter* error_reporter_;
std::vector<const TfLiteRegistration*> flatbuffer_op_index_to_registration_;
std::vector<TfLiteRegistration> unresolved_custom_ops_;
std::vector<BuiltinOperator> flatbuffer_op_index_to_registration_types_;
const Allocation* allocation_ = nullptr;
bool has_flex_op_ = false;
};
} // namespace impl
} // namespace tflite
#endif // TENSORFLOW_LITE_INTERPRETER_BUILDER_H_

222
tensorflow/lite/model.h
View File

@ -19,229 +19,11 @@ limitations under the License.
#ifndef TENSORFLOW_LITE_MODEL_H_
#define TENSORFLOW_LITE_MODEL_H_
#include <memory>
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/core/api/error_reporter.h"
#include "tensorflow/lite/core/api/op_resolver.h"
#include "tensorflow/lite/interpreter.h"
#include "tensorflow/lite/mutable_op_resolver.h"
#include "tensorflow/lite/schema/schema_generated.h"
#include "tensorflow/lite/interpreter_builder.h"
#include "tensorflow/lite/model_builder.h"
namespace tflite {
/// Abstract interface that verifies whether a given model is legit.
/// It facilitates the use-case to verify and build a model without loading it
/// twice.
class TfLiteVerifier {
public:
/// Returns true if the model is legit.
virtual bool Verify(const char* data, int length,
ErrorReporter* reporter) = 0;
virtual ~TfLiteVerifier() {}
};
/// An RAII object that represents a read-only tflite model, copied from disk,
/// or mmapped. This uses flatbuffers as the serialization format.
///
/// NOTE: The current API requires that a FlatBufferModel instance be kept alive
/// by the client as long as it is in use by any dependent Interpreter
/// instances.
/// <pre><code>
/// using namespace tflite;
/// StderrReporter error_reporter;
/// auto model = FlatBufferModel::BuildFromFile("interesting_model.tflite",
/// &error_reporter);
/// MyOpResolver resolver; // You need to subclass OpResolver to provide
/// // implementations.
/// InterpreterBuilder builder(*model, resolver);
/// std::unique_ptr<Interpreter> interpreter;
/// if(builder(&interpreter) == kTfLiteOk) {
/// .. run model inference with interpreter
/// }
/// </code></pre>
///
/// OpResolver must be defined to provide your kernel implementations to the
/// interpreter. This is environment specific and may consist of just the
/// builtin ops, or some custom operators you defined to extend tflite.
class FlatBufferModel {
public:
/// Builds a model based on a file.
/// Caller retains ownership of `error_reporter` and must ensure its lifetime
/// is longer than the FlatBufferModel instance.
/// Returns a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> BuildFromFile(
const char* filename,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Verifies whether the content of the file is legit, then builds a model
/// based on the file.
/// The extra_verifier argument is an additional optional verifier for the
/// file contents. By default, we always check with tflite::VerifyModelBuffer.
/// If extra_verifier is supplied, the file contents is also checked against
/// the extra_verifier after the check against tflite::VerifyModelBuilder.
/// Caller retains ownership of `error_reporter` and must ensure its lifetime
/// is longer than the FlatBufferModel instance.
/// Returns a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> VerifyAndBuildFromFile(
const char* filename, TfLiteVerifier* extra_verifier = nullptr,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Builds a model based on a pre-loaded flatbuffer.
/// Caller retains ownership of the buffer and should keep it alive until
/// the returned object is destroyed. Caller also retains ownership of
/// `error_reporter` and must ensure its lifetime is longer than the
/// FlatBufferModel instance.
/// Returns a nullptr in case of failure.
/// NOTE: this does NOT validate the buffer so it should NOT be called on
/// invalid/untrusted input. Use VerifyAndBuildFromBuffer in that case
static std::unique_ptr<FlatBufferModel> BuildFromBuffer(
const char* caller_owned_buffer, size_t buffer_size,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Verifies whether the content of the buffer is legit, then builds a model
/// based on the pre-loaded flatbuffer.
/// The extra_verifier argument is an additional optional verifier for the
/// buffer. By default, we always check with tflite::VerifyModelBuffer. If
/// extra_verifier is supplied, the buffer is checked against the
/// extra_verifier after the check against tflite::VerifyModelBuilder. The
/// caller retains ownership of the buffer and should keep it alive until the
/// returned object is destroyed. Caller retains ownership of `error_reporter`
/// and must ensure its lifetime is longer than the FlatBufferModel instance.
/// Returns a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> VerifyAndBuildFromBuffer(
const char* caller_owned_buffer, size_t buffer_size,
TfLiteVerifier* extra_verifier = nullptr,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Builds a model directly from a flatbuffer pointer
/// Caller retains ownership of the buffer and should keep it alive until the
/// returned object is destroyed. Caller retains ownership of `error_reporter`
/// and must ensure its lifetime is longer than the FlatBufferModel instance.
/// Returns a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> BuildFromModel(
const tflite::Model* caller_owned_model_spec,
ErrorReporter* error_reporter = DefaultErrorReporter());
// Releases memory or unmaps mmaped memory.
~FlatBufferModel();
// Copying or assignment is disallowed to simplify ownership semantics.
FlatBufferModel(const FlatBufferModel&) = delete;
FlatBufferModel& operator=(const FlatBufferModel&) = delete;
bool initialized() const { return model_ != nullptr; }
const tflite::Model* operator->() const { return model_; }
const tflite::Model* GetModel() const { return model_; }
ErrorReporter* error_reporter() const { return error_reporter_; }
const Allocation* allocation() const { return allocation_.get(); }
// Returns the minimum runtime version from the flatbuffer. This runtime
// version encodes the minimum required interpreter version to run the
// flatbuffer model. If the minimum version can't be determined, an empty
// string will be returned.
// Note that the returned minimum version is a lower-bound but not a strict
// lower-bound; ops in the graph may not have an associated runtime version,
// in which case the actual required runtime might be greater than the
// reported minimum.
string GetMinimumRuntime() const;
/// Returns true if the model identifier is correct (otherwise false and
/// reports an error).
bool CheckModelIdentifier() const;
private:
/// Loads a model from a given allocation. FlatBufferModel will take over the
/// ownership of `allocation`, and delete it in destructor. The ownership of
/// `error_reporter`remains with the caller and must have lifetime at least
/// as much as FlatBufferModel. This is to allow multiple models to use the
/// same ErrorReporter instance.
FlatBufferModel(std::unique_ptr<Allocation> allocation,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Loads a model from Model flatbuffer. The `model` has to remain alive and
/// unchanged until the end of this flatbuffermodel's lifetime.
FlatBufferModel(const Model* model, ErrorReporter* error_reporter);
/// Flatbuffer traverser pointer. (Model* is a pointer that is within the
/// allocated memory of the data allocated by allocation's internals.
const tflite::Model* model_ = nullptr;
/// The error reporter to use for model errors and subsequent errors when
/// the interpreter is created
ErrorReporter* error_reporter_;
/// The allocator used for holding memory of the model. Note that this will
/// be null if the client provides a tflite::Model directly.
std::unique_ptr<Allocation> allocation_;
};
namespace impl {
/// Build an interpreter capable of interpreting `model`.
///
/// model: A model whose lifetime must be at least as long as any
/// interpreter(s) created by the builder. In principle multiple interpreters
/// can be made from a single model.
/// op_resolver: An instance that implements the OpResolver interface, which
/// maps
/// custom op names and builtin op codes to op registrations. The lifetime
/// of the provided `op_resolver` object must be at least as long as the
/// InterpreterBuilder; unlike `model` and `error_reporter`, the `op_resolver`
/// does not need to exist for the duration of any created Interpreter
/// objects.
/// error_reporter: a functor that is called to report errors that handles
/// printf var arg semantics. The lifetime of the `error_reporter` object must
/// be greater than or equal to the Interpreter created by operator().
///
/// Returns a kTfLiteOk when successful and sets interpreter to a valid
/// Interpreter. Note: The user must ensure the model lifetime (and error
/// reporter, if provided) is at least as long as interpreter's lifetime.
class InterpreterBuilder {
public:
InterpreterBuilder(const FlatBufferModel& model,
const OpResolver& op_resolver);
/// Builds an interpreter given only the raw flatbuffer Model object (instead
/// of a FlatBufferModel). Mostly used for testing.
/// If `error_reporter` is null, then DefaultErrorReporter() is used.
InterpreterBuilder(const ::tflite::Model* model,
const OpResolver& op_resolver,
ErrorReporter* error_reporter = DefaultErrorReporter());
~InterpreterBuilder();
InterpreterBuilder(const InterpreterBuilder&) = delete;
InterpreterBuilder& operator=(const InterpreterBuilder&) = delete;
TfLiteStatus operator()(std::unique_ptr<Interpreter>* interpreter);
TfLiteStatus operator()(std::unique_ptr<Interpreter>* interpreter,
int num_threads);
private:
TfLiteStatus BuildLocalIndexToRegistrationMapping();
TfLiteStatus ParseNodes(
const flatbuffers::Vector<flatbuffers::Offset<Operator>>* operators,
Subgraph* subgraph);
TfLiteStatus ParseTensors(
const flatbuffers::Vector<flatbuffers::Offset<Buffer>>* buffers,
const flatbuffers::Vector<flatbuffers::Offset<Tensor>>* tensors,
Subgraph* subgraph);
TfLiteStatus ApplyDelegates(Interpreter* interpreter);
TfLiteStatus ParseQuantization(const QuantizationParameters* src_quantization,
TfLiteQuantization* quantization,
const std::vector<int>& dims);
TfLiteStatus ParseSparsity(const SparsityParameters* src_sparsity,
TfLiteSparsity** sparsity);
const ::tflite::Model* model_;
const OpResolver& op_resolver_;
ErrorReporter* error_reporter_;
std::vector<const TfLiteRegistration*> flatbuffer_op_index_to_registration_;
std::vector<TfLiteRegistration> unresolved_custom_ops_;
std::vector<BuiltinOperator> flatbuffer_op_index_to_registration_types_;
const Allocation* allocation_ = nullptr;
bool has_flex_op_ = false;
};
} // namespace impl
using InterpreterBuilder = impl::InterpreterBuilder;
} // namespace tflite

204
tensorflow/lite/model_builder.cc Normal file
View File

@ -0,0 +1,204 @@
/* Copyright 2017 The TensorFlow Authors. 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/lite/model_builder.h"
#include <fcntl.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <sys/stat.h>
#include <sys/types.h>
#include "tensorflow/lite/allocation.h"
#include "tensorflow/lite/c/builtin_op_data.h"
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/core/api/error_reporter.h"
#include "tensorflow/lite/core/api/flatbuffer_conversions.h"
#include "tensorflow/lite/schema/schema_generated.h"
#include "tensorflow/lite/util.h"
#include "tensorflow/lite/version.h"
#if defined(TFLITE_ENABLE_DEFAULT_PROFILER)
#include "tensorflow/lite/profiling/platform_profiler.h"
#endif
namespace tflite {
namespace {
// Ensure that ErrorReporter is non-null.
ErrorReporter* ValidateErrorReporter(ErrorReporter* e) {
return e ? e : DefaultErrorReporter();
}
} // namespace
#ifndef TFLITE_MCU
// Loads a model from `filename`. If `mmap_file` is true then use mmap,
// otherwise make a copy of the model in a buffer.
std::unique_ptr<Allocation> GetAllocationFromFile(const char* filename,
bool mmap_file,
ErrorReporter* error_reporter,
bool use_nnapi) {
std::unique_ptr<Allocation> allocation;
if (mmap_file && MMAPAllocation::IsSupported()) {
allocation.reset(new MMAPAllocation(filename, error_reporter));
} else {
allocation.reset(new FileCopyAllocation(filename, error_reporter));
}
return allocation;
}
std::unique_ptr<FlatBufferModel> FlatBufferModel::BuildFromFile(
const char* filename, ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
std::unique_ptr<FlatBufferModel> model;
auto allocation = GetAllocationFromFile(filename, /*mmap_file=*/true,
error_reporter, /*use_nnapi=*/true);
model.reset(new FlatBufferModel(std::move(allocation), error_reporter));
if (!model->initialized()) model.reset();
return model;
}
std::unique_ptr<FlatBufferModel> FlatBufferModel::VerifyAndBuildFromFile(
const char* filename, TfLiteVerifier* extra_verifier,
ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
std::unique_ptr<FlatBufferModel> model;
auto allocation = GetAllocationFromFile(filename, /*mmap_file=*/true,
error_reporter, /*use_nnapi=*/true);
flatbuffers::Verifier base_verifier(
reinterpret_cast<const uint8_t*>(allocation->base()),
allocation->bytes());
if (!VerifyModelBuffer(base_verifier)) {
TF_LITE_REPORT_ERROR(error_reporter,
"The model is not a valid Flatbuffer file");
return nullptr;
}
if (extra_verifier &&
!extra_verifier->Verify(static_cast<const char*>(allocation->base()),
allocation->bytes(), error_reporter)) {
return model;
}
model.reset(new FlatBufferModel(std::move(allocation), error_reporter));
if (!model->initialized()) model.reset();
return model;
}
#endif
std::unique_ptr<FlatBufferModel> FlatBufferModel::BuildFromBuffer(
const char* caller_owned_buffer, size_t buffer_size,
ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
std::unique_ptr<FlatBufferModel> model;
std::unique_ptr<Allocation> allocation(
new MemoryAllocation(caller_owned_buffer, buffer_size, error_reporter));
model.reset(new FlatBufferModel(std::move(allocation), error_reporter));
if (!model->initialized()) model.reset();
return model;
}
std::unique_ptr<FlatBufferModel> FlatBufferModel::VerifyAndBuildFromBuffer(
const char* caller_owned_buffer, size_t buffer_size,
TfLiteVerifier* extra_verifier, ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
flatbuffers::Verifier base_verifier(
reinterpret_cast<const uint8_t*>(caller_owned_buffer), buffer_size);
if (!VerifyModelBuffer(base_verifier)) {
TF_LITE_REPORT_ERROR(error_reporter,
"The model is not a valid Flatbuffer buffer");
return nullptr;
}
if (extra_verifier && !extra_verifier->Verify(caller_owned_buffer,
buffer_size, error_reporter)) {
return nullptr;
}
return BuildFromBuffer(caller_owned_buffer, buffer_size, error_reporter);
}
std::unique_ptr<FlatBufferModel> FlatBufferModel::BuildFromModel(
const tflite::Model* caller_owned_model_spec,
ErrorReporter* error_reporter) {
error_reporter = ValidateErrorReporter(error_reporter);
std::unique_ptr<FlatBufferModel> model;
model.reset(new FlatBufferModel(caller_owned_model_spec, error_reporter));
if (!model->initialized()) model.reset();
return model;
}
string FlatBufferModel::GetMinimumRuntime() const {
if (!model_ || !model_->metadata()) return "";
for (int i = 0; i < model_->metadata()->size(); ++i) {
auto metadata = model_->metadata()->Get(i);
if (metadata->name()->str() == "min_runtime_version") {
auto buf = metadata->buffer();
auto* buffer = (*model_->buffers())[buf];
auto* array = buffer->data();
// Get the real length of the runtime string, since there might be
// trailing
// '\0's in the buffer.
for (int len = 0; len < array->size(); ++len) {
if (array->data()[len] == '\0') {
return string(reinterpret_cast<const char*>(array->data()), len);
}
}
// If there is no '\0' in the buffer, this indicates that the flatbuffer
// is malformed.
TF_LITE_REPORT_ERROR(
error_reporter_,
"Min_runtime_version in model metadata is malformed");
break;
}
}
return "";
}
bool FlatBufferModel::CheckModelIdentifier() const {
if (!tflite::ModelBufferHasIdentifier(allocation_->base())) {
const char* ident = flatbuffers::GetBufferIdentifier(allocation_->base());
error_reporter_->Report(
"Model provided has model identifier '%c%c%c%c', should be '%s'\n",
ident[0], ident[1], ident[2], ident[3], tflite::ModelIdentifier());
return false;
}
return true;
}
FlatBufferModel::FlatBufferModel(const Model* model,
ErrorReporter* error_reporter)
: model_(model), error_reporter_(ValidateErrorReporter(error_reporter)) {}
FlatBufferModel::FlatBufferModel(std::unique_ptr<Allocation> allocation,
ErrorReporter* error_reporter)
: error_reporter_(ValidateErrorReporter(error_reporter)),
allocation_(std::move(allocation)) {
if (!allocation_->valid() || !CheckModelIdentifier()) return;
model_ = ::tflite::GetModel(allocation_->base());
}
FlatBufferModel::~FlatBufferModel() {}
} // namespace tflite

179
tensorflow/lite/model_builder.h Normal file
View File

@ -0,0 +1,179 @@
/* Copyright 2017 The TensorFlow Authors. 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.
==============================================================================*/
/// Deserialization infrastructure for tflite. Provides functionality
/// to go from a serialized tflite model in flatbuffer format to an
/// interpreter.
///
#ifndef TENSORFLOW_LITE_MODEL_BUILDER_H_
#define TENSORFLOW_LITE_MODEL_BUILDER_H_
#include <memory>
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/core/api/error_reporter.h"
#include "tensorflow/lite/core/api/op_resolver.h"
#include "tensorflow/lite/interpreter.h"
#include "tensorflow/lite/mutable_op_resolver.h"
#include "tensorflow/lite/schema/schema_generated.h"
namespace tflite {
/// Abstract interface that verifies whether a given model is legit.
/// It facilitates the use-case to verify and build a model without loading it
/// twice.
class TfLiteVerifier {
public:
/// Returns true if the model is legit.
virtual bool Verify(const char* data, int length,
ErrorReporter* reporter) = 0;
virtual ~TfLiteVerifier() {}
};
/// An RAII object that represents a read-only tflite model, copied from disk,
/// or mmapped. This uses flatbuffers as the serialization format.
///
/// NOTE: The current API requires that a FlatBufferModel instance be kept alive
/// by the client as long as it is in use by any dependent Interpreter
/// instances.
/// <pre><code>
/// using namespace tflite;
/// StderrReporter error_reporter;
/// auto model = FlatBufferModel::BuildFromFile("interesting_model.tflite",
/// &error_reporter);
/// MyOpResolver resolver; // You need to subclass OpResolver to provide
/// // implementations.
/// InterpreterBuilder builder(*model, resolver);
/// std::unique_ptr<Interpreter> interpreter;
/// if(builder(&interpreter) == kTfLiteOk) {
/// .. run model inference with interpreter
/// }
/// </code></pre>
///
/// OpResolver must be defined to provide your kernel implementations to the
/// interpreter. This is environment specific and may consist of just the
/// builtin ops, or some custom operators you defined to extend tflite.
class FlatBufferModel {
public:
/// Builds a model based on a file.
/// Caller retains ownership of `error_reporter` and must ensure its lifetime
/// is longer than the FlatBufferModel instance.
/// Returns a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> BuildFromFile(
const char* filename,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Verifies whether the content of the file is legit, then builds a model
/// based on the file.
/// The extra_verifier argument is an additional optional verifier for the
/// file contents. By default, we always check with tflite::VerifyModelBuffer.
/// If extra_verifier is supplied, the file contents is also checked against
/// the extra_verifier after the check against tflite::VerifyModelBuilder.
/// Caller retains ownership of `error_reporter` and must ensure its lifetime
/// is longer than the FlatBufferModel instance.
/// Returns a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> VerifyAndBuildFromFile(
const char* filename, TfLiteVerifier* extra_verifier = nullptr,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Builds a model based on a pre-loaded flatbuffer.
/// Caller retains ownership of the buffer and should keep it alive until
/// the returned object is destroyed. Caller also retains ownership of
/// `error_reporter` and must ensure its lifetime is longer than the
/// FlatBufferModel instance.
/// Returns a nullptr in case of failure.
/// NOTE: this does NOT validate the buffer so it should NOT be called on
/// invalid/untrusted input. Use VerifyAndBuildFromBuffer in that case
static std::unique_ptr<FlatBufferModel> BuildFromBuffer(
const char* caller_owned_buffer, size_t buffer_size,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Verifies whether the content of the buffer is legit, then builds a model
/// based on the pre-loaded flatbuffer.
/// The extra_verifier argument is an additional optional verifier for the
/// buffer. By default, we always check with tflite::VerifyModelBuffer. If
/// extra_verifier is supplied, the buffer is checked against the
/// extra_verifier after the check against tflite::VerifyModelBuilder. The
/// caller retains ownership of the buffer and should keep it alive until the
/// returned object is destroyed. Caller retains ownership of `error_reporter`
/// and must ensure its lifetime is longer than the FlatBufferModel instance.
/// Returns a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> VerifyAndBuildFromBuffer(
const char* caller_owned_buffer, size_t buffer_size,
TfLiteVerifier* extra_verifier = nullptr,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Builds a model directly from a flatbuffer pointer
/// Caller retains ownership of the buffer and should keep it alive until the
/// returned object is destroyed. Caller retains ownership of `error_reporter`
/// and must ensure its lifetime is longer than the FlatBufferModel instance.
/// Returns a nullptr in case of failure.
static std::unique_ptr<FlatBufferModel> BuildFromModel(
const tflite::Model* caller_owned_model_spec,
ErrorReporter* error_reporter = DefaultErrorReporter());
// Releases memory or unmaps mmaped memory.
~FlatBufferModel();
// Copying or assignment is disallowed to simplify ownership semantics.
FlatBufferModel(const FlatBufferModel&) = delete;
FlatBufferModel& operator=(const FlatBufferModel&) = delete;
bool initialized() const { return model_ != nullptr; }
const tflite::Model* operator->() const { return model_; }
const tflite::Model* GetModel() const { return model_; }
ErrorReporter* error_reporter() const { return error_reporter_; }
const Allocation* allocation() const { return allocation_.get(); }
// Returns the minimum runtime version from the flatbuffer. This runtime
// version encodes the minimum required interpreter version to run the
// flatbuffer model. If the minimum version can't be determined, an empty
// string will be returned.
// Note that the returned minimum version is a lower-bound but not a strict
// lower-bound; ops in the graph may not have an associated runtime version,
// in which case the actual required runtime might be greater than the
// reported minimum.
string GetMinimumRuntime() const;
/// Returns true if the model identifier is correct (otherwise false and
/// reports an error).
bool CheckModelIdentifier() const;
private:
/// Loads a model from a given allocation. FlatBufferModel will take over the
/// ownership of `allocation`, and delete it in destructor. The ownership of
/// `error_reporter`remains with the caller and must have lifetime at least
/// as much as FlatBufferModel. This is to allow multiple models to use the
/// same ErrorReporter instance.
FlatBufferModel(std::unique_ptr<Allocation> allocation,
ErrorReporter* error_reporter = DefaultErrorReporter());
/// Loads a model from Model flatbuffer. The `model` has to remain alive and
/// unchanged until the end of this flatbuffermodel's lifetime.
FlatBufferModel(const Model* model, ErrorReporter* error_reporter);
/// Flatbuffer traverser pointer. (Model* is a pointer that is within the
/// allocated memory of the data allocated by allocation's internals.
const tflite::Model* model_ = nullptr;
/// The error reporter to use for model errors and subsequent errors when
/// the interpreter is created
ErrorReporter* error_reporter_;
/// The allocator used for holding memory of the model. Note that this will
/// be null if the client provides a tflite::Model directly.
std::unique_ptr<Allocation> allocation_;
};
} // namespace tflite
#endif // TENSORFLOW_LITE_MODEL_BUILDER_H_