CircleReshape.cpp

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/*
 * Copyright (c) 2021 Samsung Electronics Co., Ltd. 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 "luci/Service/CircleShapeInference.h"
#include "Check.h"
 
#include "CircleShapeInferenceHelper.h"
#include "CircleCloneNode.h"
 
#include <luci/Log.h>
 
#include <oops/InternalExn.h>
 
namespace
{
 
std::ostream &operator<<(std::ostream &os, const loco::TensorShape &tensor_shape)
{
  os << "[";
  for (uint32_t r = 0; r < tensor_shape.rank(); ++r)
  {
    if (r)
      os << ",";
 
    if (tensor_shape.dim(r).known())
      os << tensor_shape.dim(r).value();
    else
      os << "?";
  }
  os << "]";
  return os;
}
 
} // namespace
 
namespace luci
{
 
luci::CircleNode *CloneNodeLet<CN::OPQR>::visit(const luci::CircleReshape *node)
{
  auto *cloned = _graph->nodes()->create<luci::CircleReshape>();
  {
    uint32_t rank = node->newShape()->rank();
    cloned->newShape()->rank(rank);
    for (uint32_t r = 0; r < rank; ++r)
    {
      cloned->newShape()->dim(r) = node->newShape()->dim(r);
    }
  }
  return cloned;
}
luci::CircleNode *CloneNodeLet<CN::OPQR>::visit(const luci::CircleReshape *node) {…}
 
namespace sinf
{
 
loco::TensorShape Algorithm::visit(const luci::CircleReshape *node)
{
  LOGGER(l);
 
  const loco::DataType S32 = loco::DataType::S32;
 
  bool is_static_shape = true;
 
  loco::TensorShape shape_by_input;
  {
    LUCI_ASSERT(node->shape(), "2nd input shape() should not be nullptr");
 
    // Only support node's shape() is CircleConst with S32
    // TODO support other node with other types
    auto const_shape_node = dynamic_cast<luci::CircleConst *>(node->shape());
    if (const_shape_node != nullptr)
    {
      LUCI_ASSERT(const_shape_node->dtype() == S32, "Only support int32 CircleConst");
 
      shape_by_input.rank(const_shape_node->size<S32>());
 
      for (uint32_t axis = 0; axis < shape_by_input.rank(); ++axis)
      {
        if (const_shape_node->at<S32>(axis) < 0)
        {
          shape_by_input.dim(axis).unset();
        }
        else if (const_shape_node->at<S32>(axis) == 0)
        {
          const auto node_tensor = loco::must_cast<luci::CircleNode *>(node->tensor());
          // set dim value to input
          if (node_tensor->shape_status() == luci::ShapeStatus::VALID && axis < node_tensor->rank())
            shape_by_input.dim(axis) = node_tensor->dim(axis);
          else
          {
            // stop to check if this case exist for debugging
            INTERNAL_EXN("Check Reshape shape with 0");
          }
        }
        else
        {
          shape_by_input.dim(axis).set(const_shape_node->at<S32>(axis));
        }
        // check valid or stop for debugging
        LUCI_ASSERT(shape_by_input.dim(axis).value() > 0 || !shape_by_input.dim(axis).known(),
                    "Reshape infer shape is invalid.");
      }
    }
    else
    {
      // NOTE assumption is that `shape` and `newShape` having same value.
      // for non-existing `shape`, we can use `newShape` if it's valid
      auto new_shape = node->newShape();
      auto rank = new_shape->rank();
      auto shape_dummy = dynamic_cast<luci::CircleOutputDummy *>(node->shape());
      if (shape_dummy && rank > 0)
      {
        is_static_shape = true;
        shape_by_input.rank(rank);
        for (uint32_t i = 0; i < rank; ++i)
        {
          if (new_shape->dim(i) > 0)
            shape_by_input.dim(i) = static_cast<uint32_t>(new_shape->dim(i));
          else
          {
            is_static_shape = false;
            shape_by_input.dim(i).unset();
          }
        }
      }
      else
      {
        auto shape_node = loco::must_cast<luci::CircleNode *>(node->shape());
        assert(shape_node->rank() == 1);
        // shape_node tensor values will provide new shape, like [2, 3, 4]
        auto num_elements = shape_node->dim(0).value(); // above example will give 3
        shape_by_input.rank(num_elements);
        is_static_shape = false;
      }
    }
  }
 
  loco::TensorShape shape_by_attr;
  {
    shape_by_attr.rank(node->newShape()->rank());
 
    for (uint32_t axis = 0; axis < shape_by_attr.rank(); ++axis)
    {
      shape_by_attr.dim(axis) = node->newShape()->dim(axis);
    }
  }
 
  if (!(shape_by_input == shape_by_attr))
  {
    INFO(l) << "CircleReshape: Two new shape information mismatched : " << std::endl;
    INFO(l) << "   shape_by_input : " << shape_by_input << std::endl;
    INFO(l) << "   shape_by_attr : " << shape_by_attr << std::endl;
  }
 
  loco::TensorShape output_shape = shape_by_input;
 
  // One of the dimensions can have special value -1, meaning its actual value should be inferred.
  const auto input = loco::must_cast<luci::CircleNode *>(node->tensor());
  const auto input_shape = circle_shape(input);
  uint32_t input_element_count = 1;
  uint32_t output_element_count = 1;
  uint32_t unknown_dim_index = UINT32_MAX;
  for (uint32_t i = 0; i < input_shape.rank(); ++i)
  {
    if (input_shape.dim(i).known())
      input_element_count *= input_shape.dim(i).value();
    else
      is_static_shape = false;
  }
 
  if (is_static_shape)
  {
    for (uint32_t dim_index = 0; dim_index < output_shape.rank(); ++dim_index)
    {
      uint32_t dim_value = output_shape.dim(dim_index).value();
      if (not output_shape.dim(dim_index).known())
      {
        LUCI_ASSERT(unknown_dim_index == UINT32_MAX, "More than one unknown dimension");
        unknown_dim_index = dim_index;
      }
      else
      {
        if (!dim_value)
        {
          // refer https://github.com/Samsung/ONE/issues/14074#issuecomment-2370795003
          // set dim value to follow input
          if (dim_index < input_shape.rank())
            dim_value = input_shape.dim(dim_index).value();
          else
          {
            // stop to check if this case exist for debugging
            INTERNAL_EXN("Check Reshape shape with 0");
          }
        }
        output_element_count *= dim_value;
      }
    }
    if (unknown_dim_index != UINT32_MAX)
    {
      if (input_element_count % output_element_count != 0)
      {
        INTERNAL_EXN("Reshape Op cannot infer unknown dimension from inputs.");
      }
      output_shape.dim(unknown_dim_index) = input_element_count / output_element_count;
    }
  }
 
  return output_shape;
}
loco::TensorShape Algorithm::visit(const luci::CircleReshape *node) {…}
 
} // namespace sinf
} // namespace luci