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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import unittest
from typing import Sequence
import torch
from detectron2.structures import ImageList
class TestImageList(unittest.TestCase):
def test_imagelist_padding_shape(self):
class TensorToImageList(torch.nn.Module):
def forward(self, tensors: Sequence[torch.Tensor]):
return ImageList.from_tensors(tensors, 4).tensor
func = torch.jit.trace(
TensorToImageList(), ([torch.ones((3, 10, 10), dtype=torch.float32)],)
)
ret = func([torch.ones((3, 15, 20), dtype=torch.float32)])
self.assertEqual(list(ret.shape), [1, 3, 16, 20], str(ret.shape))
func = torch.jit.trace(
TensorToImageList(),
(
[
torch.ones((3, 16, 10), dtype=torch.float32),
torch.ones((3, 13, 11), dtype=torch.float32),
],
),
)
ret = func(
[
torch.ones((3, 25, 20), dtype=torch.float32),
torch.ones((3, 10, 10), dtype=torch.float32),
]
)
# does not support calling with different #images
self.assertEqual(list(ret.shape), [2, 3, 28, 20], str(ret.shape))
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