Update test_dataset.py
Browse files- test_dataset.py +37 -22
test_dataset.py
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@@ -5,21 +5,18 @@ import os
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_VERSION = datasets.Version("0.0.2")
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_DESCRIPTION = "
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_HOMEPAGE = "
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_LICENSE = "
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_CITATION = ""
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"conditioning_image": datasets.Value("string"),
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"text": datasets.Value("string"),
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})
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METADATA_URL = hf_hub_url(
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"spine-crook/test_dataset",
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@@ -41,7 +38,8 @@ CONDITIONING_IMAGES_URL = hf_hub_url(
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_DEFAULT_CONFIG = datasets.BuilderConfig(name="default", version=_VERSION)
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BUILDER_CONFIGS = [_DEFAULT_CONFIG]
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DEFAULT_CONFIG_NAME = "default"
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@@ -58,11 +56,14 @@ class Fill50k(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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metadata_path = dl_manager.download(METADATA_URL)
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images_dir = dl_manager.download_and_extract(IMAGES_URL)
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conditioning_images_dir = dl_manager.download_and_extract(
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"metadata_path": metadata_path,
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"images_dir": images_dir,
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@@ -76,11 +77,25 @@ class Fill50k(datasets.GeneratorBasedBuilder):
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for _, row in metadata.iterrows():
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text = row["text"]
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yield row["image"], {
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"text": text,
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"image":
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_VERSION = datasets.Version("0.0.2")
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_DESCRIPTION = "TODO"
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_HOMEPAGE = "TODO"
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_LICENSE = "TODO"
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_CITATION = "TODO"
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_FEATURES = datasets.Features(
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{
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"image": datasets.Image(),
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"conditioning_image": datasets.Image(),
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"text": datasets.Value("string"),
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},
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)
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METADATA_URL = hf_hub_url(
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"spine-crook/test_dataset",
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_DEFAULT_CONFIG = datasets.BuilderConfig(name="default", version=_VERSION)
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class Test_Dataset(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [_DEFAULT_CONFIG]
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DEFAULT_CONFIG_NAME = "default"
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def _split_generators(self, dl_manager):
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metadata_path = dl_manager.download(METADATA_URL)
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images_dir = dl_manager.download_and_extract(IMAGES_URL)
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conditioning_images_dir = dl_manager.download_and_extract(
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CONDITIONING_IMAGES_URL
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)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"metadata_path": metadata_path,
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"images_dir": images_dir,
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for _, row in metadata.iterrows():
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text = row["text"]
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image_path = row["image"]
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image_path = os.path.join(images_dir, image_path)
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image = open(image_path, "rb").read()
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conditioning_image_path = row["conditioning_image"]
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conditioning_image_path = os.path.join(
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conditioning_images_dir, row["conditioning_image"]
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)
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conditioning_image = open(conditioning_image_path, "rb").read()
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yield row["image"], {
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"text": text,
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"image": {
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"path": image_path,
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"bytes": image,
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},
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"conditioning_image": {
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"path": conditioning_image_path,
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"bytes": conditioning_image,
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},
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}
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