mmocr/tests/models/textrecog/decoders/test_abi_language_decoder.py
2022-07-21 10:58:04 +08:00

59 lines
2.2 KiB
Python

# Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
from unittest import TestCase
import torch
from mmocr.models.textrecog.decoders import ABILanguageDecoder
from mmocr.testing import create_dummy_dict_file
class TestABILanguageDecoder(TestCase):
def test_init(self):
with tempfile.TemporaryDirectory() as tmp_dir:
dict_file = osp.join(tmp_dir, 'fake_chars.txt')
create_dummy_dict_file(dict_file)
dict_cfg = dict(
type='Dictionary', dict_file=dict_file, with_end=False)
# No padding token
with self.assertRaises(AssertionError):
ABILanguageDecoder(dict_cfg)
def test_forward(self):
with tempfile.TemporaryDirectory() as tmp_dir:
dict_file = osp.join(tmp_dir, 'fake_chars.txt')
create_dummy_dict_file(dict_file)
# test diction cfg
dict_cfg = dict(
type='Dictionary',
dict_file=dict_file,
with_start=True,
with_end=True,
same_start_end=False,
with_padding=True,
with_unknown=False)
decoder = ABILanguageDecoder(
dict_cfg, d_model=16, d_inner=16, max_seq_len=10)
logits = torch.randn(2, 10, 39)
result = decoder.forward_train(None, logits, None)
self.assertIn('feature', result)
self.assertIn('logits', result)
self.assertEqual(result['feature'].shape, torch.Size([2, 10, 16]))
self.assertEqual(result['logits'].shape, torch.Size([2, 10, 39]))
decoder = ABILanguageDecoder(
dict_cfg,
d_model=16,
d_inner=16,
max_seq_len=10,
with_self_attn=True,
detach_tokens=False)
logits = torch.randn(2, 10, 39)
result = decoder.forward_test(None, logits, None)
self.assertIn('feature', result)
self.assertIn('logits', result)
self.assertEqual(result['feature'].shape, torch.Size([2, 10, 16]))
self.assertEqual(result['logits'].shape, torch.Size([2, 10, 39]))