/usr/local/lib64/python3.6/site-packages/torch/include/ATen/native
Edit: /usr/local/lib64/python3.6/site-packages/torch/include/ATen/native/im2col_shape_check.h (6181B)
#include
#include
namespace at {
namespace native {
static inline void col2im_shape_check(
const Tensor& input,
const Tensor& grad_output,
int64_t output_height,
int64_t output_width,
int64_t kernel_height,
int64_t kernel_width,
int64_t dilation_height,
int64_t dilation_width,
int64_t pad_height,
int64_t pad_width,
int64_t stride_height,
int64_t stride_width) {
TORCH_CHECK(
kernel_width > 0 && kernel_height > 0,
"kernel size should be greater than zero, but got kernel_height: ",
kernel_height,
" kernel_width: ",
kernel_width);
TORCH_CHECK(
stride_width > 0 && stride_height > 0,
"stride should be greater than zero, but got stride_height: ",
stride_height,
" stride_width: ",
stride_width);
TORCH_CHECK(
dilation_width > 0 && dilation_height > 0,
"dilation should be greater than zero, but got dilation_height: ",
dilation_height,
" dilation_width: ",
dilation_width);
int64_t ndim = input.ndimension();
// allow dim=0 only the batch dimension.
TORCH_CHECK(
(ndim == 2 && input.size(0) != 0 && input.size(1) != 0) ||
(ndim == 3 && input.size(1) != 0 && input.size(2) != 0),
"Expected 2D or 3D (batch mode) tensor for input with possibly 0 batch size and non-zero dimensions for input, but got: ",
input.sizes());
int64_t batch_dim = (ndim == 3) ? 0 : -1;
int64_t n_input_plane = input.size(batch_dim + 1);
if (n_input_plane % (kernel_width * kernel_height) != 0) {
AT_ERROR(
"Expected size of input's dimension 1 to be divisible by the "
"product of kernel_size, but got input.size(1)=",
n_input_plane,
" and kernel_size=(",
kernel_height,
", ",
kernel_width,
").");
}
int64_t input_length = input.size(batch_dim + 2);
int64_t n_blocks_height =
div_rtn(
output_height + 2 * pad_height -
dilation_height * (kernel_height - 1) - 1,
stride_height) +
1;
int64_t n_blocks_width = div_rtn(
output_width + 2 * pad_width -
dilation_width * (kernel_width - 1) - 1,
stride_width) +
1;
if (input_length != (n_blocks_height * n_blocks_width)) {
AT_ERROR(
"Given output_size=(",
output_height,
", ",
output_width,
"), kernel_size=(",
kernel_height,
", ",
kernel_width,
"), dilation=(",
dilation_height,
", ",
dilation_width,
"), padding=(",
pad_height,
", ",
pad_width,
"), stride=(",
stride_height,
", ",
stride_width,
"), expected size of input's dimension 2 to match the calculated number of ",
"sliding blocks ",
n_blocks_height,
" * ",
n_blocks_width,
" = ",
(n_blocks_height * n_blocks_width),
", but got input.size(2)=",
input_length,
".");
}
if (output_width < 1 || output_height < 1) {
AT_ERROR(
"Expected output spatial size to be positive, but got: output_size=(",
output_height,
", ",
output_width,
").");
}
}
static inline void im2col_shape_check(
const Tensor& input,
const Tensor& grad_output,
int64_t kernel_height,
int64_t kernel_width,
int64_t dilation_height,
int64_t dilation_width,
int64_t pad_height,
int64_t pad_width,
int64_t stride_height,
int64_t stride_width) {
TORCH_CHECK(
kernel_width > 0 && kernel_height > 0,
"kernel size should be greater than zero, but got kernel_height: ",
kernel_height,
" kernel_width: ",
kernel_width);
TORCH_CHECK(
dilation_width > 0 && dilation_height > 0,
"dilation should be greater than zero, but got dilation_height: ",
dilation_height,
" dilation_width: ",
dilation_width);
TORCH_CHECK(
pad_width >= 0 && pad_height >= 0,
"padding should be non-negative, but got pad_height: ",
pad_height,
" pad_width: ",
pad_width);
TORCH_CHECK(
stride_width > 0 && stride_height > 0,
"stride should be greater than zero, but got stride_height: ",
stride_height,
" stride_width: ",
stride_width);
int64_t ndim = input.ndimension();
// allow dim=0 only the batch dimension.
bool valid_dims = input.size(1) != 0 && input.size(2) != 0;
TORCH_CHECK(
(ndim == 3 && input.size(0) && valid_dims) ||
(ndim == 4 && valid_dims && input.size(3) != 0),
"Expected 3D or 4D (batch mode) tensor with possibly 0 batch size and other non-zero dimensions for input, but got: ",
input.sizes());
int64_t dim_batch = 0;
if (ndim == 3) {
dim_batch = -1;
}
int64_t input_height = input.size(dim_batch + 2);
int64_t input_width = input.size(dim_batch + 3);
int64_t output_height = div_rtn(
input_height + 2 * pad_height -
(dilation_height * (kernel_height - 1) + 1),
stride_height) +
1;
int64_t output_width = div_rtn(
input_width + 2 * pad_width -
(dilation_width * (kernel_width - 1) + 1),
stride_width) +
1;
if (output_height < 1 || output_width < 1) {
AT_ERROR(
"Given input with spatial size (",
input_height,
", ",
input_height,
"), kernel_size=(",
kernel_height,
", ",
kernel_width,
"), dilation=(",
dilation_height,
", ",
dilation_width,
"), padding=(",
pad_height,
", ",
pad_width,
"), calculated shape of the array of sliding blocks as (",
output_height,
", ",
output_width,
"), which is too small (non-positive).");
}
}
} // namespace native
} // namespace at