common_shape.h

/* Copyright (c) 2021 PaddlePaddle 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. */

#pragma once

#include "paddle/pten/core/dense_tensor.h"

namespace pten {
namespace funcs {

inline void SetXShape(const DenseTensor &x, DenseTensor *xshape) {
  const auto &in_dims = x.meta().dims;
  std::vector<int64_t> xshape_dims(in_dims.size() + 1);
  xshape_dims[0] = 0;
  for (int i = 0; i < in_dims.size(); ++i) {
    xshape_dims[i + 1] = in_dims[i];
  }
  xshape->ResizeAndAllocate(pten::framework::make_ddim(xshape_dims));
  xshape->ResetLoD(x.meta().lod);
}

inline void GetBroadcastDimsArrays(const DDim &x_dims,
                                   const DDim &y_dims,
                                   int *x_dims_array,
                                   int *y_dims_array,
                                   int *out_dims_array,
                                   const int max_dim,
                                   const int axis) {
  PADDLE_ENFORCE_GE(
      axis,
      0,
      paddle::platform::errors::InvalidArgument(
          "Axis should be great than or equal to 0, but received axis is %d.",
          axis));
  PADDLE_ENFORCE_LT(axis,
                    max_dim,
                    paddle::platform::errors::InvalidArgument(
                        "Axis should be less than %d, but received axis is %d.",
                        max_dim,
                        axis));
  if (x_dims.size() > y_dims.size()) {
    std::fill(y_dims_array, y_dims_array + axis, 1);
    if (axis + y_dims.size() < max_dim) {
      std::fill(y_dims_array + axis + y_dims.size(), y_dims_array + max_dim, 1);
    }
    std::copy(x_dims.Get(), x_dims.Get() + x_dims.size(), x_dims_array);
    std::copy(y_dims.Get(), y_dims.Get() + y_dims.size(), y_dims_array + axis);
  } else {
    std::fill(x_dims_array, x_dims_array + axis, 1);
    if (axis + x_dims.size() < max_dim) {
      std::fill(x_dims_array + axis + x_dims.size(), x_dims_array + max_dim, 1);
    }
    std::copy(x_dims.Get(), x_dims.Get() + x_dims.size(), x_dims_array + axis);
    std::copy(y_dims.Get(), y_dims.Get() + y_dims.size(), y_dims_array);
  }

  for (int i = 0; i < max_dim; i++) {
    PADDLE_ENFORCE_EQ(
        x_dims_array[i] == y_dims_array[i] || x_dims_array[i] <= 1 ||
            y_dims_array[i] <= 1,
        true,
        paddle::platform::errors::InvalidArgument(
            "Broadcast dimension mismatch. Operands could "
            "not be broadcast together with the shape of X = [%s] and "
            "the shape of Y = [%s]. Received [%d] in X is not equal to "
            "[%d] in Y at i:%d.",
            x_dims,
            y_dims,
            x_dims_array[i],
            y_dims_array[i],
            i));
    if ((x_dims_array[i] > 1 || y_dims_array[i] > 1) ||
        (x_dims_array[i] == 1 && y_dims_array[i] == 1)) {
      out_dims_array[i] = (std::max)(x_dims_array[i], y_dims_array[i]);
    } else {
      out_dims_array[i] = -1;
    }
  }
}

inline void GetPrePostNumel(
    const framework::DDim &dim, int axis, int *pre, int *n, int *post) {
  *pre = 1;
  *post = 1;
  *n = dim[axis];
  for (int i = 0; i < axis; ++i) {
    (*pre) *= dim[i];
  }
  for (int i = axis + 1; i < dim.size(); ++i) {
    (*post) *= dim[i];
  }
}

}  // namespace funcs
}  // namespace pten