Assign default value for MAX_CAPTION_LENGTH
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@ -12,6 +12,8 @@ from typing import TypeVar, Iterable
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from tqdm import tqdm
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DEFAULT_MAX_CAPTION_LENGTH = 2048
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def overlay(overlay, base):
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return overlay if overlay is not None else base
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@ -235,7 +237,7 @@ class Dataset:
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rating=config.rating or 1.0,
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tags=tags,
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tag_weights=tag_weights,
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max_target_length=config.max_caption_length,
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max_target_length=config.max_caption_length or DEFAULT_MAX_CAPTION_LENGTH,
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use_weights=use_weights)
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item = ImageTrainItem(
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@ -29,7 +29,6 @@ from torchvision import transforms
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_RANDOM_TRIM = 0.04
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DEFAULT_MAX_CAPTION_LENGTH = 2048
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OptionalImageCaption = typing.Optional['ImageCaption']
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@ -1,5 +1,5 @@
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import os
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from data.dataset import Dataset, ImageConfig, Tag
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from data.dataset import Dataset, ImageConfig, Tag, DEFAULT_MAX_CAPTION_LENGTH
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from textwrap import dedent
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from pyfakefs.fake_filesystem_unittest import TestCase
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@ -276,8 +276,8 @@ class TestDataset(TestCase):
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self.assertEqual(actual[0].cond_dropout, 0.01)
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self.assertEqual(actual[0].caption.rating(), 1.1)
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self.assertEqual(actual[0].caption.get_caption(), "first caption, tag, tag_2")
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# Can't test this
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# self.assertTrue(actual[0].caption.__use_weights)
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self.assertTrue(actual[0].caption._ImageCaption__use_weights)
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self.assertEqual(actual[0].caption._ImageCaption__max_target_length, 1024)
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self.assertEqual(actual[1].pathname, os.path.abspath('2.jpg'))
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self.assertEqual(actual[1].multiplier, 1.0)
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@ -285,5 +285,5 @@ class TestDataset(TestCase):
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self.assertIsNone(actual[1].cond_dropout)
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self.assertEqual(actual[1].caption.rating(), 1.0)
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self.assertEqual(actual[1].caption.get_caption(), "single caption")
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# Can't test this
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# self.assertFalse(actual[1].caption.__use_weights)
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self.assertFalse(actual[1].caption._ImageCaption__use_weights)
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self.assertEqual(actual[1].caption._ImageCaption__max_target_length, DEFAULT_MAX_CAPTION_LENGTH)
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