Cherie Ho
Initial upload
fd01725
raw
history blame
1.23 kB
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the Apache License, Version 2.0
# found in the LICENSE file in the root directory of this source tree.
import warnings
import torch.nn.functional as F
def resize(input, size=None, scale_factor=None, mode="nearest", align_corners=None, warning=False):
if warning:
if size is not None and align_corners:
input_h, input_w = tuple(int(x) for x in input.shape[2:])
output_h, output_w = tuple(int(x) for x in size)
if output_h > input_h or output_w > output_h:
if (
(output_h > 1 and output_w > 1 and input_h > 1 and input_w > 1)
and (output_h - 1) % (input_h - 1)
and (output_w - 1) % (input_w - 1)
):
warnings.warn(
f"When align_corners={align_corners}, "
"the output would more aligned if "
f"input size {(input_h, input_w)} is `x+1` and "
f"out size {(output_h, output_w)} is `nx+1`"
)
return F.interpolate(input, size, scale_factor, mode, align_corners)