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diff --git a/tensorflow/contrib/lite/toco/graph_transformations/remove_trivial_reshape.cc b/tensorflow/contrib/lite/toco/graph_transformations/remove_trivial_reshape.cc
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+++ b/tensorflow/contrib/lite/toco/graph_transformations/remove_trivial_reshape.cc
@@ -0,0 +1,92 @@
+/* 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 <iterator>
+#include <memory>
+#include <string>
+#include <unordered_map>
+#include <vector>
+
+#include "tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.h"
+#include "tensorflow/contrib/lite/toco/graph_transformations/remove_trivial_passthrough.h"
+#include "tensorflow/contrib/lite/toco/model.h"
+#include "tensorflow/contrib/lite/toco/tooling_util.h"
+#include "tensorflow/core/platform/logging.h"
+
+namespace toco {
+
+namespace {
+
+bool IsReshapeTrivial(const Model& model, const Operator& op,
+                      RemoveTrivialReshape* transformation) {
+  CHECK(op.type == OperatorType::kTensorFlowReshape);
+
+  // One way in which a reshape can be trivial is if its
+  // output shape is == its input shape
+  const auto& input_array = model.GetArray(op.inputs[0]);
+  const auto& output_array = model.GetArray(op.outputs[0]);
+  if (input_array.has_shape() && output_array.has_shape()) {
+    if (transformation->treat_expand_dims_as_trivial() &&
+        ShapesAgreeUpToExtending(input_array.shape(), output_array.shape())) {
+      transformation->AddMessageF(
+          "%s is trivial because its input and output shapes are equal up to "
+          "extending "
+          "by 1's, and we are told to aggressively discard such Reshape ops.",
+          LogName(op));
+      return true;
+    }
+    if (input_array.shape().dims() == output_array.shape().dims()) {
+      transformation->AddMessageF(
+          "%s is trivial because its input and output shapes are equal",
+          LogName(op));
+      return true;
+    }
+  }
+
+  // Another way in which a reshape can be trivial is if its output
+  // is only consumed by another reshape.
+  if (CountOpsWithInput(model, op.outputs[0]) == 1) {
+    const auto* next_op = GetOpWithInput(model, op.outputs[0]);
+    if (next_op->type == OperatorType::kTensorFlowReshape) {
+      transformation->AddMessageF(
+          "%s is trivial because its output is only consumed by another "
+          "Reshape op",
+          LogName(op));
+      return true;
+    }
+  }
+
+  return false;
+}
+
+}  // namespace
+
+bool RemoveTrivialReshape::Run(Model* model, std::size_t op_index) {
+  const auto reshape_it = model->operators.begin() + op_index;
+  auto* reshape_op = reshape_it->get();
+  if (reshape_op->type != OperatorType::kTensorFlowReshape) {
+    return false;
+  }
+
+  if (!IsReshapeTrivial(*model, *reshape_op, this)) {
+    return false;
+  }
+
+  AddMessageF("Removing trivial %s", LogName(*reshape_op));
+
+  CHECK_EQ(reshape_op->inputs.size(), 2);
+  return RemoveTrivialPassthroughOp(this, model, op_index);
+}
+
+}  // namespace toco