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Change for logical NHWC
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@YongseopKim
YongseopKim committed Jan 26, 2024
1 parent 7d498ea commit 74c9693
Showing 1 changed file with 40 additions and 40 deletions.
80 changes: 40 additions & 40 deletions compute/cker/include/cker/train/operation/Pad.h
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Original file line number Diff line number Diff line change
Expand Up @@ -69,87 +69,87 @@ inline void Depad(const int32_t *padding_data, int32_t pad_rank, const Shape &in
input_shape.Dims(i) - padding_list[i].first - padding_list[i].second);
}

// logical axis: row -> col -> plain -> cube
switch (pad_rank)
{
case 0:
case 1:
{
const int32_t out_width = output_shape.Dims(0);
const int32_t out_row_len = output_shape.Dims(0);
const int32_t padding_left = padding_list[0].first;
std::memcpy(output_data, input_data + padding_left, out_width * sizeof(T));
std::memcpy(output_data, input_data + padding_left, out_row_len * sizeof(T));
break;
}
case 2: // HW
{
const int32_t out_height = output_shape.Dims(0);
const int32_t out_width = output_shape.Dims(1);
const int32_t in_width = input_shape.Dims(1);
const int32_t out_col_len = output_shape.Dims(0);
const int32_t out_row_len = output_shape.Dims(1);
const int32_t in_row_len = input_shape.Dims(1);
const int32_t padding_top = padding_list[0].first;
const int32_t padding_left = padding_list[1].first;
for (auto h = 0; h < out_height; ++h)
for (auto i = 0; i < out_col_len; ++i)
{
const auto in_offset = (h + padding_top) * in_width + padding_left;
const auto out_offset = h * out_width;
const auto in_offset = (i + padding_top) * in_row_len + padding_left;
const auto out_offset = i * out_row_len;
// copy a row of input data to output data
std::memcpy(output_data + out_offset, input_data + in_offset, out_width * sizeof(T));
std::memcpy(output_data + out_offset, input_data + in_offset, out_row_len * sizeof(T));
}
break;
}
case 3: // HWC
{
const int32_t out_depth = output_shape.Dims(0);
const int32_t out_height = output_shape.Dims(1);
const int32_t out_width = output_shape.Dims(2);
const int32_t out_plain_size = out_height * out_width;
const int32_t in_height = input_shape.Dims(1);
const int32_t in_width = input_shape.Dims(2);
const int32_t in_plain_size = in_height * in_width;
const int32_t out_plain_len = output_shape.Dims(0);
const int32_t out_col_len = output_shape.Dims(1);
const int32_t out_row_len = output_shape.Dims(2);
const int32_t out_plain_size = out_col_len * out_row_len;
const int32_t in_col_len = input_shape.Dims(1);
const int32_t in_row_len = input_shape.Dims(2);
const int32_t in_plain_size = in_col_len * in_row_len;
const int32_t padding_depth = padding_list[0].first;
const int32_t padding_top = padding_list[1].first;
const int32_t padding_left = padding_list[2].first;
for (auto d = 0; d < out_depth; ++d)
for (auto d = 0; d < out_plain_len; ++d)
{
for (auto h = 0; h < out_height; ++h)
for (auto h = 0; h < out_col_len; ++h)
{
const auto in_offset =
(d + padding_depth) * in_plain_size + (h + padding_top) * in_width + (padding_left);
const auto out_offset = (d * out_plain_size) + (h * out_width);
(d + padding_depth) * in_plain_size + (h + padding_top) * in_row_len + (padding_left);
const auto out_offset = (d * out_plain_size) + (h * out_row_len);
// copy a row of input data to output data
std::memcpy(output_data + out_offset, input_data + in_offset, out_width * sizeof(T));
std::memcpy(output_data + out_offset, input_data + in_offset, out_row_len * sizeof(T));
}
}
break;
}
// NOTE: Assume that tensors' memory format is NHWC. In cker, it cannot be checked.
case 4:
case 4: // NHWC
{
const int32_t out_cube = output_shape.Dims(0);
const int32_t out_depth = output_shape.Dims(1);
const int32_t out_height = output_shape.Dims(2);
const int32_t out_width = output_shape.Dims(3);
const int32_t out_plain_size = out_height * out_width;
const int32_t out_cube_size = out_depth * out_plain_size;
const int32_t in_depth = input_shape.Dims(1);
const int32_t in_height = input_shape.Dims(2);
const int32_t in_width = input_shape.Dims(3);
const int32_t in_plain_size = in_height * in_width;
const int32_t in_cube_size = in_depth * in_plain_size;
const int32_t out_cube_len = output_shape.Dims(0);
const int32_t out_plain_len = output_shape.Dims(1);
const int32_t out_col_len = output_shape.Dims(2);
const int32_t out_row_len = output_shape.Dims(3);
const int32_t out_plain_size = out_col_len * out_row_len;
const int32_t out_cube_size = out_plain_len * out_plain_size;
const int32_t in_plain_len = input_shape.Dims(1);
const int32_t in_col_len = input_shape.Dims(2);
const int32_t in_row_len = input_shape.Dims(3);
const int32_t in_plain_size = in_col_len * in_row_len;
const int32_t in_cube_size = in_plain_len * in_plain_size;
const int32_t padding_cube = padding_list[0].first;
const int32_t padding_depth = padding_list[1].first;
const int32_t padding_top = padding_list[2].first;
const int32_t padding_left = padding_list[3].first;
for (auto c = 0; c < out_cube; ++c)
for (auto c = 0; c < out_cube_len; ++c)
{
for (auto d = 0; d < out_depth; ++d)
for (auto d = 0; d < out_plain_len; ++d)
{
for (auto h = 0; h < out_height; ++h)
for (auto h = 0; h < out_col_len; ++h)
{
const auto in_offset = (c + padding_cube) * in_cube_size +
(d + padding_depth) * in_plain_size +
(h + padding_top) * in_width + (padding_left);
const auto out_offset = (c * out_cube_size) + (d * out_plain_size) + (h * out_width);
(h + padding_top) * in_row_len + (padding_left);
const auto out_offset = (c * out_cube_size) + (d * out_plain_size) + (h * out_row_len);
// copy a row of input data to output data
std::memcpy(output_data + out_offset, input_data + in_offset, out_width * sizeof(T));
std::memcpy(output_data + out_offset, input_data + in_offset, out_row_len * sizeof(T));
}
}
}
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