Move FlatBuffer to GraphFloat32 converter into the common directory.

PiperOrigin-RevId: 306739537
Change-Id: I055e864b5c25afc75b45d3e067b56d38214ce99e

tensorflow/lite/delegates/gpu/cl/testing/BUILD

@@ -7,21 +7,11 @@ cc_binary(
     name = "performance_profiling",
     srcs = ["performance_profiling.cc"],
     deps = [
-        "//tensorflow/lite/core/api",
-        "//tensorflow/lite/delegates/gpu/cl:cl_command_queue",
         "//tensorflow/lite/delegates/gpu/cl:environment",
         "//tensorflow/lite/delegates/gpu/cl:inference_context",
-        "//tensorflow/lite/delegates/gpu/cl:model_hints",
-        "//tensorflow/lite/delegates/gpu/cl:opencl_wrapper",
-        "//tensorflow/lite/delegates/gpu/cl:precision",
-        "//tensorflow/lite/delegates/gpu/cl:tensor_type",
         "//tensorflow/lite/delegates/gpu/common:model",
-        "//tensorflow/lite/delegates/gpu/common:model_builder",
-        "//tensorflow/lite/delegates/gpu/common:model_transformer",
         "//tensorflow/lite/delegates/gpu/common:status",
-        "//tensorflow/lite/delegates/gpu/common/transformations:general_transformations",
-        "//tensorflow/lite/delegates/gpu/common/transformations:merge_padding_with",
-        "//tensorflow/lite/kernels:builtin_ops",
+        "//tensorflow/lite/delegates/gpu/common:tfl2model",
         "@com_google_absl//absl/time",
     ],
 )

tensorflow/lite/delegates/gpu/cl/testing/performance_profiling.cc

@@ -13,112 +13,25 @@ See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
 
+#include <algorithm>
 #include <iostream>
 #include <string>
 
-#include "absl/time/clock.h"
 #include "absl/time/time.h"
-#include "tensorflow/lite/core/api/op_resolver.h"
-#include "tensorflow/lite/delegates/gpu/cl/cl_command_queue.h"
 #include "tensorflow/lite/delegates/gpu/cl/environment.h"
 #include "tensorflow/lite/delegates/gpu/cl/inference_context.h"
-#include "tensorflow/lite/delegates/gpu/cl/model_hints.h"
-#include "tensorflow/lite/delegates/gpu/cl/opencl_wrapper.h"
-#include "tensorflow/lite/delegates/gpu/cl/precision.h"
-#include "tensorflow/lite/delegates/gpu/cl/tensor_type.h"
 #include "tensorflow/lite/delegates/gpu/common/model.h"
-#include "tensorflow/lite/delegates/gpu/common/model_builder.h"
-#include "tensorflow/lite/delegates/gpu/common/model_transformer.h"
 #include "tensorflow/lite/delegates/gpu/common/status.h"
-#include "tensorflow/lite/delegates/gpu/common/transformations/general_transformations.h"
-#include "tensorflow/lite/delegates/gpu/common/transformations/merge_padding_with.h"
-#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/delegates/gpu/common/tfl2model.h"
 
 namespace tflite {
 namespace gpu {
 namespace cl {
-namespace {
-
-class DelegateContext {
- public:
-  bool Init(TfLiteContext* context,
-            const TfLiteDelegateParams* delegate_params) {
-    auto denormalized_graph =
-        reinterpret_cast<GraphFloat32*>(delegate_params->delegate->data_);
-    absl::Status status =
-        BuildModel(context, delegate_params, denormalized_graph);
-    if (!status.ok()) {
-      context->ReportError(context, "Failed to convert a model: %s",
-                           std::string(status.message()).c_str());
-    }
-    return status.ok();
-  }
-};
-
-TfLiteStatus DelegatePrepare(TfLiteContext* context, TfLiteDelegate* delegate) {
-  const TfLiteRegistration kRegistration = {
-      .init = [](TfLiteContext* context, const char* buffer, size_t) -> void* {
-        auto* delegate_context = new DelegateContext();
-        if (!delegate_context->Init(
-                context,
-                reinterpret_cast<const TfLiteDelegateParams*>(buffer))) {
-          delete delegate_context;
-          return nullptr;
-        }
-        return delegate_context;
-      },
-      .free = [](TfLiteContext* context, void* buffer) -> void {
-        delete reinterpret_cast<DelegateContext*>(buffer);
-      },
-      .prepare = [](TfLiteContext* context, TfLiteNode* node) -> TfLiteStatus {
-        return node->user_data ? kTfLiteOk : kTfLiteError;
-      },
-      .invoke = nullptr,
-  };
-
-  TfLiteIntArray* ops_to_replace = GetOpsToReplace(context);
-  const auto status = context->ReplaceNodeSubsetsWithDelegateKernels(
-      context, kRegistration, ops_to_replace, delegate);
-  TfLiteIntArrayFree(ops_to_replace);
-  return status;
-}
-
-absl::Status FlatBufferToGPUGraph(
-    const std::unique_ptr<tflite::FlatBufferModel>& flatbuffer,
-    GraphFloat32* graph) {
-  tflite::ops::builtin::BuiltinOpResolver op_resolver;
-  std::unique_ptr<tflite::Interpreter> interpreter;
-  tflite::InterpreterBuilder interpreter_builder(*flatbuffer, op_resolver);
-  if (interpreter_builder(&interpreter) != kTfLiteOk || !interpreter) {
-    return absl::InternalError("Unable to prepare TfLite interpreter.");
-  }
-  interpreter->UseNNAPI(false);
-  TfLiteDelegate delegate;
-  delegate.data_ = graph;
-  delegate.flags = kTfLiteDelegateFlagsNone;
-  delegate.Prepare = DelegatePrepare;
-  delegate.CopyFromBufferHandle = nullptr;
-  delegate.CopyToBufferHandle = nullptr;
-  delegate.FreeBufferHandle = nullptr;
-
-  if (interpreter->ModifyGraphWithDelegate(&delegate) != kTfLiteOk) {
-    return absl::InternalError("Conversion from TfLite model failed.");
-  }
-
-  NullTransformationReporter reporter;
-  ModelTransformer transformer(graph, &reporter);
-  if (!ApplyGeneralTransformations(&transformer)) {
-    return absl::InternalError("Graph general transformations failed");
-  }
-
-  return absl::OkStatus();
-}
-}  // namespace
 
 absl::Status RunModelSample(const std::string& model_name) {
   auto flatbuffer = tflite::FlatBufferModel::BuildFromFile(model_name.c_str());
   GraphFloat32 graph_cl;
-  RETURN_IF_ERROR(FlatBufferToGPUGraph(flatbuffer, &graph_cl));
+  RETURN_IF_ERROR(BuildFromFlatBuffer(*flatbuffer, &graph_cl));
 
   Environment env;
   RETURN_IF_ERROR(CreateEnvironment(&env));

tensorflow/lite/delegates/gpu/common/BUILD

@@ -216,6 +216,32 @@ cc_library(
     ],
 )
 
+cc_library(
+    name = "tfl2model",
+    srcs = ["tfl2model.cc"],
+    hdrs = ["tfl2model.h"],
+    deps = [
+        "//tensorflow/lite:framework_lib",
+        "//tensorflow/lite:kernel_api",
+        "//tensorflow/lite:minimal_logging",
+        "//tensorflow/lite/c:common",
+        "//tensorflow/lite/delegates/gpu/cl:api",
+        "//tensorflow/lite/delegates/gpu/cl:opencl_wrapper",
+        "//tensorflow/lite/delegates/gpu/cl:tensor_type_util",
+        "//tensorflow/lite/delegates/gpu/common:model",
+        "//tensorflow/lite/delegates/gpu/common:model_builder",
+        "//tensorflow/lite/delegates/gpu/common:model_transformer",
+        "//tensorflow/lite/delegates/gpu/common:status",
+        "//tensorflow/lite/delegates/gpu/common/transformations:general_transformations",
+        "//tensorflow/lite/delegates/gpu/gl:api2",
+        "//tensorflow/lite/kernels:builtin_ops",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/types:span",
+    ],
+)
+
 cc_library(
     name = "types",
     hdrs = ["types.h"],

tensorflow/lite/delegates/gpu/common/tfl2model.cc

@@ -0,0 +1,104 @@
+/* Copyright 2020 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/delegates/gpu/common/tfl2model.h"
+
+#include <memory>
+
+#include "tensorflow/lite/builtin_ops.h"
+#include "tensorflow/lite/delegates/gpu/common/model.h"
+#include "tensorflow/lite/delegates/gpu/common/model_builder.h"
+#include "tensorflow/lite/delegates/gpu/common/status.h"
+#include "tensorflow/lite/delegates/gpu/common/transformations/general_transformations.h"
+#include "tensorflow/lite/interpreter.h"
+#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/model_builder.h"
+
+namespace tflite {
+namespace gpu {
+namespace {
+
+class DelegateContext {
+ public:
+  bool Init(TfLiteContext* context,
+            const TfLiteDelegateParams* delegate_params) {
+    auto denormalized_graph =
+        reinterpret_cast<GraphFloat32*>(delegate_params->delegate->data_);
+    return denormalized_graph
+               ? BuildModel(context, delegate_params, denormalized_graph).ok()
+               : false;
+  }
+};
+
+TfLiteStatus DelegatePrepare(TfLiteContext* context, TfLiteDelegate* delegate) {
+  const TfLiteRegistration kRegistration = {
+      .init = [](TfLiteContext* context, const char* buffer, size_t) -> void* {
+        auto* delegate_context = new DelegateContext();
+        if (!delegate_context->Init(
+                context,
+                reinterpret_cast<const TfLiteDelegateParams*>(buffer))) {
+          delete delegate_context;
+          return nullptr;
+        }
+        return delegate_context;
+      },
+      .free = [](TfLiteContext* context, void* buffer) -> void {
+        delete reinterpret_cast<DelegateContext*>(buffer);
+      },
+      .prepare = [](TfLiteContext* context, TfLiteNode* node) -> TfLiteStatus {
+        return node->user_data ? kTfLiteOk : kTfLiteError;
+      },
+      .invoke = nullptr,
+  };
+
+  TfLiteIntArray* ops_to_replace = GetOpsToReplace(context);
+  const auto status = context->ReplaceNodeSubsetsWithDelegateKernels(
+      context, kRegistration, ops_to_replace, delegate);
+  TfLiteIntArrayFree(ops_to_replace);
+  return status;
+}
+}  // namespace
+
+absl::Status BuildFromFlatBuffer(const tflite::FlatBufferModel& flatbuffer,
+                                 GraphFloat32* graph) {
+  ops::builtin::BuiltinOpResolver op_resolver;
+  std::unique_ptr<tflite::Interpreter> interpreter;
+  tflite::InterpreterBuilder interpreter_builder(flatbuffer, op_resolver);
+  if (interpreter_builder(&interpreter) != kTfLiteOk || !interpreter) {
+    return absl::InternalError("Unable to prepare TfLite interpreter.");
+  }
+  interpreter->UseNNAPI(false);
+  TfLiteDelegate delegate;
+  delegate.data_ = graph;
+  delegate.flags = kTfLiteDelegateFlagsNone;
+  delegate.Prepare = DelegatePrepare;
+  delegate.CopyFromBufferHandle = nullptr;
+  delegate.CopyToBufferHandle = nullptr;
+  delegate.FreeBufferHandle = nullptr;
+
+  if (interpreter->ModifyGraphWithDelegate(&delegate) != kTfLiteOk) {
+    return absl::InternalError("Conversion from TfLite model failed.");
+  }
+
+  NullTransformationReporter reporter;
+  ModelTransformer transformer(graph, &reporter);
+  if (!ApplyGeneralTransformations(&transformer)) {
+    return absl::InternalError("Graph general transformations failed");
+  }
+
+  return absl::OkStatus();
+}
+
+}  // namespace gpu
+}  // namespace tflite

tensorflow/lite/delegates/gpu/common/tfl2model.h

@@ -0,0 +1,32 @@
+/* Copyright 2020 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.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_DELEGATES_GPU_COMMON_TFL2MODEL_H_
+#define TENSORFLOW_LITE_DELEGATES_GPU_COMMON_TFL2MODEL_H_
+
+#include "tensorflow/lite/delegates/gpu/common/model.h"
+#include "tensorflow/lite/delegates/gpu/common/status.h"
+#include "tensorflow/lite/model_builder.h"
+
+namespace tflite {
+namespace gpu {
+
+// Generates GraphFloat32 basing on the FlatBufferModel without specifying a
+// delegate.
+absl::Status BuildFromFlatBuffer(const tflite::FlatBufferModel& flatbuffer,
+                                 GraphFloat32* graph);
+}  // namespace gpu
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_DELEGATES_GPU_COMMON_TFL2MODEL_H_