Support streaming
#3
by
albertvillanova
HF staff
- opened
- data.zip +3 -0
- fashion_mnist_corrupted.py +11 -11
data.zip
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:008da37ffe6fd498247a6d4d4a29d0aba4fa694018087bd9816dcad4ef525265
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size 27512552
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fashion_mnist_corrupted.py
CHANGED
@@ -3,7 +3,7 @@
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This module contains the huggingface dataset adaptation of
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the Corrupted Fashion-Mnist Data Set.
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Find the full code at `https://github.com/testingautomated-usi/fashion-mnist-c`."""
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import
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import datasets
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import numpy as np
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@@ -38,11 +38,9 @@ if CONFIG.version == datasets.Version("1.0.0"):
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else:
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raise ValueError("Unsupported version.")
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-
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-
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-
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_URLS = {
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"train_images": "fmnist-c-train.npy",
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"train_labels": "fmnist-c-train-labels.npy",
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"test_images": "fmnist-c-test.npy",
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@@ -86,10 +84,10 @@ class FashionMnistCorrupted(datasets.GeneratorBasedBuilder):
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)
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def _split_generators(self, dl_manager):
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-
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}
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downloaded_files = dl_manager.download_and_extract(urls_to_download)
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return [
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datasets.SplitGenerator(
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@@ -117,8 +115,10 @@ class FashionMnistCorrupted(datasets.GeneratorBasedBuilder):
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def _generate_examples(self, filepath, split):
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"""This function returns the examples in the raw form."""
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# Images
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-
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-
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if images.shape[0] != labels.shape[0]:
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raise ValueError(
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This module contains the huggingface dataset adaptation of
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the Corrupted Fashion-Mnist Data Set.
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Find the full code at `https://github.com/testingautomated-usi/fashion-mnist-c`."""
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import os.path
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import datasets
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import numpy as np
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else:
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raise ValueError("Unsupported version.")
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# Downloaded from: f"https://raw.githubusercontent.com/testingautomated-usi/fashion-mnist-c/{tag}/generated/npy/
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_URL = "data.zip"
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_FILENAMES = {
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"train_images": "fmnist-c-train.npy",
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"train_labels": "fmnist-c-train-labels.npy",
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"test_images": "fmnist-c-test.npy",
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)
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def _split_generators(self, dl_manager):
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data_dir = dl_manager.download_and_extract(_URL)
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downloaded_files = {
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key: os.path.join(data_dir, fname) for key, fname in _FILENAMES.items()
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}
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return [
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datasets.SplitGenerator(
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def _generate_examples(self, filepath, split):
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"""This function returns the examples in the raw form."""
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# Images
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with open(filepath[0], "rb") as f:
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images = np.load(f)
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with open(filepath[1], "rb") as f:
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labels = np.load(f)
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if images.shape[0] != labels.shape[0]:
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raise ValueError(
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