compiler/locomotiv/src/Node/Reshape.cpp

   1 /*
   2  * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
   3  *
   4  * Licensed under the Apache License, Version 2.0 (the "License");
   5  * you may not use this file except in compliance with the License.
   6  * You may obtain a copy of the License at
   7  *
   8  *    http://www.apache.org/licenses/LICENSE-2.0
   9  *
  10  * Unless required by applicable law or agreed to in writing, software
  11  * distributed under the License is distributed on an "AS IS" BASIS,
  12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13  * See the License for the specific language governing permissions and
  14  * limitations under the License.
  15  */
  16
  17 #include "NodeExecution.h"
  18
  19 #include "NodeDataImpl.h"
  20 #include "NodeDomain.h"
  21 #include "Validation.h"
  22
  23 #include <nncc/core/ADT/tensor/Shape.h>
  24 #include <nncc/core/ADT/tensor/Buffer.h>
  25 #include <nncc/core/ADT/tensor/Index.h>
  26 #include <nncc/core/ADT/tensor/IndexEnumerator.h>
  27 #include <nncc/core/ADT/tensor/LexicalLayout.h>
  28
  29 using nncc::core::ADT::tensor::IndexEnumerator;
  30 using nncc::core::ADT::tensor::LexicalLayout;
  31 using nncc::core::ADT::tensor::make_buffer;
  32 using nncc::core::ADT::tensor::num_elements;
  33
  34 #include <cassert>
  35 #include <stdexcept>
  36 #include <cstring>
  37 #include <vector>
  38
  39 namespace locomotiv
  40 {
  41
  42 void NodeExecution::execute(loco::Reshape<loco::ReshapeType::Fixed> *reshape)
  43 {
  44   auto input_data = annot_data(reshape->input());
  45
  46   validate(input_data, "Input not ready");
  47   validate(annot_domain(reshape->input()) == loco::Domain::Tensor,
  48            "Input domain of Reshape is not Tensor");
  49
  50   std::unique_ptr<NodeData> reshape_data = nullptr;
  51
  52   switch (input_data->dtype())
  53   {
  54     case loco::DataType::FLOAT32:
  55     {
  56       auto input_bufptr = input_data->as_f32_bufptr();
  57       auto *input_shape = input_data->shape();
  58
  59       using Shape = nncc::core::ADT::tensor::Shape;
  60       std::unique_ptr<Shape> output_shape(new Shape());
  61
  62       output_shape->resize(reshape->rank());
  63       for (uint32_t axis = 0; axis < output_shape->rank(); ++axis)
  64       {
  65         output_shape->dim(axis) = reshape->dim(axis).value();
  66       }
  67
  68       auto reshape_bufptr = make_buffer<float, LexicalLayout>(*output_shape);
  69
  70       float *input_ptr = const_cast<float *>(input_bufptr->base());
  71       uint64_t input_len = num_elements(*input_shape) * sizeof(float);
  72
  73       float *output_ptr = reshape_bufptr.base();
  74
  75       assert(input_len == num_elements(*output_shape) * sizeof(float));
  76       memcpy(output_ptr, input_ptr, input_len);
  77
  78       reshape_data = make_data(reshape_bufptr);
  79       break;
  80     }
  81     default:
  82       throw std::runtime_error("NYI for this DataType");
  83   }
  84
  85   assert(reshape_data != nullptr);
  86   annot_data(reshape, std::move(reshape_data));
  87   annot_domain(reshape, annot_domain(reshape->input()));
  88 }
  89
  90 } // namespace locomotiv