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# Copyright (c) OpenMMLab. All rights reserved. | |
import torch | |
from mmocr.models.textrecog.necks import FPNOCR | |
def test_fpn_ocr(): | |
in_s1 = torch.rand(1, 128, 32, 256) | |
in_s2 = torch.rand(1, 256, 16, 128) | |
in_s3 = torch.rand(1, 512, 8, 64) | |
in_s4 = torch.rand(1, 512, 4, 32) | |
fpn_ocr = FPNOCR(in_channels=[128, 256, 512, 512], out_channels=256) | |
fpn_ocr.init_weights() | |
fpn_ocr.train() | |
out_neck = fpn_ocr((in_s1, in_s2, in_s3, in_s4)) | |
assert out_neck[0].shape == torch.Size([1, 256, 32, 256]) | |