Internal Change.

PiperOrigin-RevId: 175307445

1 files changed, 108 insertions, 0 deletions

diff --git a/tensorflow/contrib/lite/optional_debug_tools.cc b/tensorflow/contrib/lite/optional_debug_tools.cc
new file mode 100644
index 0000000000..1f762e6688
--- /dev/null
+++ b/tensorflow/contrib/lite/optional_debug_tools.cc
@@ -0,0 +1,108 @@
+/* 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/contrib/lite/optional_debug_tools.h"
+
+namespace tflite {
+
+void PrintIntVector(const std::vector<int>& v) {
+  for (const auto& it : v) {
+    printf(" %d", it);
+  }
+  printf("\n");
+}
+
+void PrintTfLiteIntVector(const TfLiteIntArray* v) {
+  if (!v) {
+    printf(" (null)");
+    return;
+  }
+  for (int k = 0; k < v->size; k++) {
+    printf(" %d", v->data[k]);
+  }
+  printf("\n");
+}
+
+const char* TensorTypeName(TfLiteType type) {
+  switch (type) {
+    case kTfLiteNoType:
+      return "kTfLiteNoType";
+    case kTfLiteFloat32:
+      return "kTfLiteFloat32";
+    case kTfLiteInt32:
+      return "kTfLiteInt32";
+    case kTfLiteUInt8:
+      return "kTfLiteUInt8";
+    case kTfLiteInt64:
+      return "kTfLiteInt64";
+    case kTfLiteString:
+      return "kTfLiteString";
+  }
+  return "(invalid)";
+}
+
+const char* AllocTypeName(TfLiteAllocationType type) {
+  switch (type) {
+    case kTfLiteMemNone:
+      return "kTfLiteMemNone";
+    case kTfLiteMmapRo:
+      return "kTfLiteMmapRo";
+    case kTfLiteDynamic:
+      return "kTfLiteDynamic";
+    case kTfLiteArenaRw:
+      return "kTfLiteArenaRw";
+    case kTfLiteArenaRwPersistent:
+      return "kTfLiteArenaRwPersistent";
+  }
+  return "(invalid)";
+}
+
+// Prints a dump of what tensors and what nodes are in the interpreter.
+void PrintInterpreterState(Interpreter* interpreter) {
+  printf("Interpreter has %d tensors and %d nodes\n",
+         interpreter->tensors_size(), interpreter->nodes_size());
+  printf("Inputs:");
+  PrintIntVector(interpreter->inputs());
+  printf("Outputs:");
+  PrintIntVector(interpreter->outputs());
+  printf("\n");
+  for (int tensor_index = 0; tensor_index < interpreter->tensors_size();
+       tensor_index++) {
+    TfLiteTensor* tensor = interpreter->tensor(tensor_index);
+    printf("Tensor %3d %10s %15s %10zu bytes (%4.1f MB) ", tensor_index,
+           TensorTypeName(tensor->type), AllocTypeName(tensor->allocation_type),
+           tensor->bytes, float(tensor->bytes) / float(1 << 20));
+    PrintTfLiteIntVector(tensor->dims);
+    printf("\n");
+  }
+
+  for (int node_index = 0; node_index < interpreter->nodes_size();
+       node_index++) {
+    const std::pair<TfLiteNode, TfLiteRegistration>* node_and_reg =
+        interpreter->node_and_registration(node_index);
+    const TfLiteNode& node = node_and_reg->first;
+    const TfLiteRegistration& reg = node_and_reg->second;
+    printf("Node %3d Operator Builtin Code %3d\n", node_index,
+           reg.builtin_code);
+    printf("  Inputs:");
+    PrintTfLiteIntVector(node.inputs);
+    printf("  Outputs:");
+    PrintTfLiteIntVector(node.outputs);
+  }
+}
+
+// Prints a dump of what tensors and what nodes are in the interpreter.
+TfLiteStatus ValidateInterpreterState(const Interpreter* interpreter);
+
+}  // namespace tflite