Disable GCE check (#21)

Author: mathpluscode

imgx_datasets/amos_ct/amos_ct_dataset_builder.py

@@ -1,6 +1,7 @@
 """AMOS CT image dataset."""
 
 import json
+import os
 from collections.abc import Generator
 from pathlib import Path
 from typing import ClassVar
@@ -21,6 +22,10 @@
 from imgx_datasets.preprocess import load_and_preprocess_image_and_label
 from imgx_datasets.save import save_uids
 
+# https://github.com/tensorflow/datasets/issues/2761
+tfds.core.utils.gcs_utils._is_gcs_disabled = True  # pylint: disable=protected-access
+os.environ["NO_GCE_CHECK"] = "true"
+
 _DESCRIPTION = """
 The data set includes 500 CT and 100 MR images from Amos:
 A large-scale abdominal multi-organ benchmark for versatile medical

imgx_datasets/brats2021_mr/brats2021_mr_dataset_builder.py

@@ -1,6 +1,7 @@
 """brats2021_mr dataset."""
 from __future__ import annotations
 
+import os
 from collections.abc import Generator
 from pathlib import Path
 from typing import ClassVar
@@ -24,6 +25,10 @@
 from imgx_datasets.preprocess import clip_and_normalise_intensity
 from imgx_datasets.save import save_uids
 
+# https://github.com/tensorflow/datasets/issues/2761
+tfds.core.utils.gcs_utils._is_gcs_disabled = True  # pylint: disable=protected-access
+os.environ["NO_GCE_CHECK"] = "true"
+
 _DESCRIPTION = """
 All BraTS mpMRI scans are available as NIfTI files (.nii.gz) and describe
 a) native (T1) and b) post-contrast T1-weighted (T1Gd), c) T2-weighted (T2),

imgx_datasets/male_pelvic_mr/male_pelvic_mr_dataset_builder.py

@@ -1,5 +1,6 @@
 """male_pelvic_mr dataset."""
 
+import os
 from collections.abc import Generator
 from pathlib import Path
 from typing import ClassVar
@@ -21,6 +22,10 @@
 from imgx_datasets.preprocess import load_and_preprocess_image_and_label
 from imgx_datasets.save import save_uids
 
+# https://github.com/tensorflow/datasets/issues/2761
+tfds.core.utils.gcs_utils._is_gcs_disabled = True  # pylint: disable=protected-access
+os.environ["NO_GCE_CHECK"] = "true"
+
 _DESCRIPTION = """
 The data set includes 589 T2-weighted images acquired from the same number of
 patients collected by seven studies,

imgx_datasets/muscle_us/muscle_us_dataset_builder.py

@@ -1,6 +1,7 @@
 """muscle_us dataset."""
 from __future__ import annotations
 
+import os
 from collections.abc import Generator
 from pathlib import Path
 from typing import ClassVar
@@ -23,6 +24,10 @@
 from imgx_datasets.dataset_info import OneHotLabeledDatasetInfo
 from imgx_datasets.save import load_2d_grayscale_image, save_2d_grayscale_image, save_uids
 
+# https://github.com/tensorflow/datasets/issues/2761
+tfds.core.utils.gcs_utils._is_gcs_disabled = True  # pylint: disable=protected-access
+os.environ["NO_GCE_CHECK"] = "true"
+
 _DESCRIPTION = """
 The dataset included 3917 images of biceps brachii, tibialis anterior and
 gastrocnemius medialis acquired on 1283 subjects.