SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Pass datasets trust_remote_code (#31406)

Browse Source 
* Pass datasets trust_remote_code

* Pass trust_remote_code in more tests

* Add trust_remote_dataset_code arg to some tests

* Revert "Temporarily pin datasets upper version to fix CI"

This reverts commit b7672826ca.

* Pass trust_remote_code in librispeech_asr_dummy docstrings

* Revert "Pin datasets<2.20.0 for examples"

This reverts commit 833fc17a3e.

* Pass trust_remote_code to all examples

* Revert "Add trust_remote_dataset_code arg to some tests" to research_projects

* Pass trust_remote_code to tests

* Pass trust_remote_code to docstrings

* Fix flax examples tests requirements

* Pass trust_remote_dataset_code arg to tests

* Replace trust_remote_dataset_code with trust_remote_code in one example

* Fix duplicate trust_remote_code

* Replace args.trust_remote_dataset_code with args.trust_remote_code

* Replace trust_remote_dataset_code with trust_remote_code in parser

* Replace trust_remote_dataset_code with trust_remote_code in dataclasses

* Replace trust_remote_dataset_code with trust_remote_code arg
This commit is contained in:
Albert Villanova del Moral
2024-06-17 18:29:13 +02:00
committed by GitHub
parent 485fd81471
commit a14b055b65
168 changed files with 804 additions and 410 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
tests/models/beit/test_modeling_beit.py
View File

@@ -484,7 +484,7 @@ class BeitModelIntegrationTest(unittest.TestCase):
image_processor = BeitImageProcessor(do_resize=True, size=640, do_center_crop=False)
ds = load_dataset("hf-internal-testing/fixtures_ade20k", split="test")
ds = load_dataset("hf-internal-testing/fixtures_ade20k", split="test", trust_remote_code=True)
image = Image.open(ds[0]["file"])
inputs = image_processor(images=image, return_tensors="pt").to(torch_device)
@@ -527,7 +527,7 @@ class BeitModelIntegrationTest(unittest.TestCase):
image_processor = BeitImageProcessor(do_resize=True, size=640, do_center_crop=False)
ds = load_dataset("hf-internal-testing/fixtures_ade20k", split="test")
ds = load_dataset("hf-internal-testing/fixtures_ade20k", split="test", trust_remote_code=True)
image = Image.open(ds[0]["file"])
inputs = image_processor(images=image, return_tensors="pt").to(torch_device)