Datasets:
Tasks:
Image Classification
Sub-tasks:
multi-class-classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
extended|imdb
License:
Francisco Castillo
commited on
Commit
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aa56354
1
Parent(s):
9ec5c9d
Use pickle5
Browse files
fashion_mnist_quality_drift.py
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@@ -17,7 +17,7 @@
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import datasets
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# TODO: Add BibTeX citation to our BLOG
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@@ -155,9 +155,6 @@ class FashionMNISTLabelDrift(datasets.GeneratorBasedBuilder):
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# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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def _generate_examples(self, filepath):
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import os
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os.system('!pip install pickle5')
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import pickle5 as pickle
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# This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
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# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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with open(filepath, 'rb') as pkl_file:
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import datasets
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import pickle5 as pickle
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# TODO: Add BibTeX citation to our BLOG
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# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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def _generate_examples(self, filepath):
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# This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
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# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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with open(filepath, 'rb') as pkl_file:
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