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      1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
      2 
      3 Licensed under the Apache License, Version 2.0 (the "License");
      4 you may not use this file except in compliance with the License.
      5 You may obtain a copy of the License at
      6 
      7     http://www.apache.org/licenses/LICENSE-2.0
      8 
      9 Unless required by applicable law or agreed to in writing, software
     10 distributed under the License is distributed on an "AS IS" BASIS,
     11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     12 See the License for the specific language governing permissions and
     13 limitations under the License.
     14 ==============================================================================*/
     15 #include <algorithm>
     16 #include <memory>
     17 #include <string>
     18 #include <unordered_map>
     19 #include <vector>
     20 
     21 #include "tensorflow/lite/toco/graph_transformations/graph_transformations.h"
     22 #include "tensorflow/lite/toco/model.h"
     23 #include "tensorflow/lite/toco/tooling_util.h"
     24 #include "tensorflow/core/platform/logging.h"
     25 
     26 namespace toco {
     27 
     28 namespace {
     29 
     30 void RenameArray(Model* model, const string& oldname,
     31                  const string& desired_newname) {
     32   const string& newname = AvailableArrayName(*model, desired_newname);
     33   auto& arrays = model->GetMutableArrayMap();
     34   arrays[newname] = std::move(arrays[oldname]);
     35   arrays.erase(oldname);
     36   for (const auto& op : model->operators) {
     37     for (string& input : op->inputs) {
     38       if (input == oldname) {
     39         input = newname;
     40       }
     41     }
     42     for (string& output : op->outputs) {
     43       if (output == oldname) {
     44         output = newname;
     45       }
     46     }
     47   }
     48 }
     49 
     50 }  // namespace
     51 
     52 // Reorder the elements of an input_array according to the input_axes_order and
     53 // output_axes_order. Then adjust the shapes of the input and output arrays
     54 // accordingly. Note that input_array must have a buffer (that is, it is a
     55 // constant array).
     56 template <typename T, ArrayDataType DataType>
     57 void ReorderAxes(AxesOrder input_axes_order, AxesOrder output_axes_order,
     58                  const Array& input_array, Array* output_array) {
     59   DCHECK(input_array.buffer->type == DataType);
     60   DCHECK(!output_array->buffer);
     61   const auto& input_data = input_array.GetBuffer<DataType>().data;
     62   auto& output_data = output_array->GetMutableBuffer<DataType>().data;
     63   output_data.resize(RequiredBufferSizeForShape(output_array->shape()));
     64   // TODO(b/62904716) Shapes should be used directly.
     65   Shape input_shape = input_array.shape();
     66   Shape output_shape = output_array->shape();
     67   if (AxesCount(input_axes_order) == 2) {
     68     UnextendShape(&input_shape, 2);
     69     UnextendShape(&output_shape, 2);
     70   }
     71   ShuffleArray(input_shape, input_axes_order, output_axes_order, output_shape,
     72                input_data.data(), output_data.data());
     73   if (input_array.minmax) {
     74     output_array->GetOrCreateMinMax() = input_array.GetMinMax();
     75   }
     76   if (input_array.narrow_range) {
     77     output_array->narrow_range = true;
     78   }
     79 }
     80 
     81 ::tensorflow::Status ResolveReorderAxes::Run(Model* model, std::size_t op_index,
     82                                              bool* modified) {
     83   *modified = false;
     84   auto it = model->operators.begin() + op_index;
     85   auto* op = it->get();
     86   if (op->type != OperatorType::kReorderAxes) {
     87     return ::tensorflow::Status::OK();
     88   }
     89   auto* reorder_op = static_cast<ReorderAxesOperator*>(op);
     90 
     91   // Intentionally copies, not references.
     92   const string input_array_name = reorder_op->inputs[0];
     93   const string output_array_name = reorder_op->outputs[0];
     94 
     95   auto& input_array = model->GetArray(input_array_name);
     96   auto& output_array = model->GetArray(output_array_name);
     97   if (!input_array.buffer) {
     98     return ::tensorflow::Status::OK();
     99   }
    100   // Yield until output dims have been resolved.
    101   if (!output_array.has_shape()) {
    102     return ::tensorflow::Status::OK();
    103   }
    104   // Reorder the input array dims and buffer data
    105   if (input_array.buffer->type == ArrayDataType::kFloat) {
    106     ReorderAxes<float, ArrayDataType::kFloat>(reorder_op->input_axes_order,
    107                                               reorder_op->output_axes_order,
    108                                               input_array, &output_array);
    109   } else if (input_array.buffer->type == ArrayDataType::kUint8) {
    110     // TODO(benoitjacob): This path seems unused.
    111     // ReorderAxes is only used when importing from
    112     // TensorFlow GraphDef, which does not support quantized nodes.
    113     ReorderAxes<uint8, ArrayDataType::kUint8>(reorder_op->input_axes_order,
    114                                               reorder_op->output_axes_order,
    115                                               input_array, &output_array);
    116   } else {
    117     LOG(FATAL) << "Cannot ReorderAxes unless input buffer is float or uint8.";
    118   }
    119 
    120   AddMessageF("Reordered axes for array %s", input_array_name);
    121 
    122   DeleteOpAndArraysIfUnused(model, op);
    123   RenameArray(model, output_array_name, input_array_name);
    124 
    125   *modified = true;
    126   return ::tensorflow::Status::OK();
    127 }
    128 
    129 }  // namespace toco
    130