1 files changed, 0 insertions, 106 deletions
diff --git a/tensorflow/contrib/lite/toco/graph_transformations/quantize_weights.cc b/tensorflow/contrib/lite/toco/graph_transformations/quantize_weights.cc
deleted file mode 100644
index 7a8515f6d1..0000000000
--- a/tensorflow/contrib/lite/toco/graph_transformations/quantize_weights.cc
+++ /dev/null
@@ -1,106 +0,0 @@
-/* Copyright 2018 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 <string>
-#include <vector>
-
-#include "tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.h"
-#include "tensorflow/contrib/lite/toco/graph_transformations/quantization_util.h"
-#include "tensorflow/contrib/lite/toco/model.h"
-#include "tensorflow/contrib/lite/toco/tooling_util.h"
-
-namespace toco {
-
-namespace {
-
-// The minimum number of elements a weights array must have to be quantized
-// by this transformation.
-// TODO(suharshs): Make this minimum size configurable.
-const int kWeightsMinSize = 1024;
-
-// Gets the quantization params from the float array.
-void GetQuantizationParamsFromArray(const Array& array,
-                                    QuantizationParams* params) {
-  const std::vector<float>& float_vals =
-      array.GetBuffer<ArrayDataType::kFloat>().data;
-  auto minmax = std::minmax_element(float_vals.begin(), float_vals.end());
-  *params = tflite::ChooseQuantizationParams<uint8>(
-      *minmax.first, *minmax.second, array.narrow_range);
-}
-
-}  // namespace
-
-bool QuantizeWeights::Run(Model* model, std::size_t op_index) {
-  const auto op_it = model->operators.begin() + op_index;
-  Operator* op = op_it->get();
-
-  // Get the weights tensor, if the current operator has one.
-  int weights_index;
-  if (op->type == OperatorType::kConv ||
-      op->type == OperatorType::kDepthwiseConv ||
-      op->type == OperatorType::kFullyConnected) {
-    weights_index = 1;
-  } else if (op->type == OperatorType::kLstmCell) {
-    weights_index = LstmCellOperator::WEIGHTS_INPUT;
-  } else {
-    return false;
-  }
-
-  // Return early if the array isn't a constant param, this can happen in early
-  // transformation passes until transpose operations following the weight array
-  // are resolved.
-  const string weights = op->inputs[weights_index];
-  if (!IsConstantParameterArray(*model, weights)) {
-    return false;
-  }
-
-  // Return early if the weight tensor is not type float.
-  Array& weights_array = model->GetArray(weights);
-  if (weights_array.data_type != ArrayDataType::kFloat) {
-    return false;
-  }
-
-  // Return early if the tensor is too small. Small tensors don't take up too
-  // much space and can result in bad quantization results.
-  if (weights_array.GetBuffer<ArrayDataType::kFloat>().data.size() <
-      kWeightsMinSize) {
-    return false;
-  }
-
-  // Quantize the weight tensor to type kUint8.
-  QuantizationParams params;
-  GetQuantizationParamsFromArray(weights_array, &params);
-  QuantizeArray(this, model, weights, ArrayDataType::kUint8, params);
-
-  // Insert a Dequantize operation after the quantized weights tensor.
-  auto* dequantize_op = new DequantizeOperator;
-  model->operators.emplace(op_it, dequantize_op);
-
-  // Create a new intermediate tensor to connect the Dequantize op to the
-  // original op.
-  const string dequantized_output =
-      AvailableArrayName(*model, weights + "_dequantized");
-  Array& dequantized_output_array = model->GetOrCreateArray(dequantized_output);
-  dequantized_output_array.data_type = ArrayDataType::kFloat;
-
-  // Connect up the new Dequantize op with the weights and original op.
-  op->inputs[weights_index] = dequantized_output;
-  dequantize_op->inputs = {weights};
-  dequantize_op->outputs = {dequantized_output};
-
-  return true;
-}
-
-}  // namespace toco