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

Fix RequestCounter to make it more future-proof (#27406)

Browse Source 
* Fix RequestCounter to make it more future-proof

* code quality
This commit is contained in:
Lucain
2023-11-09 18:53:26 +01:00
committed by GitHub
parent c8b6052ff6
commit e38348ae8f
5 changed files with 48 additions and 45 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
tests/models/auto/test_modeling_auto.py
View File

@@ -482,25 +482,22 @@ class AutoModelTest(unittest.TestCase):
with self.assertRaisesRegex(EnvironmentError, "Use `from_flax=True` to load this model"):
_ = AutoModel.from_pretrained("hf-internal-testing/tiny-bert-flax-only")
@unittest.skip(
"Currently failing with new huggingface_hub release. See: https://github.com/huggingface/transformers/pull/27389"
)
def test_cached_model_has_minimum_calls_to_head(self):
# Make sure we have cached the model.
_ = AutoModel.from_pretrained("hf-internal-testing/tiny-random-bert")
with RequestCounter() as counter:
_ = AutoModel.from_pretrained("hf-internal-testing/tiny-random-bert")
self.assertEqual(counter.get_request_count, 0)
self.assertEqual(counter.head_request_count, 1)
self.assertEqual(counter.other_request_count, 0)
self.assertEqual(counter["GET"], 0)
self.assertEqual(counter["HEAD"], 1)
self.assertEqual(counter.total_calls, 1)
# With a sharded checkpoint
_ = AutoModel.from_pretrained("hf-internal-testing/tiny-random-bert-sharded")
with RequestCounter() as counter:
_ = AutoModel.from_pretrained("hf-internal-testing/tiny-random-bert-sharded")
self.assertEqual(counter.get_request_count, 0)
self.assertEqual(counter.head_request_count, 1)
self.assertEqual(counter.other_request_count, 0)
self.assertEqual(counter["GET"], 0)
self.assertEqual(counter["HEAD"], 1)
self.assertEqual(counter.total_calls, 1)
def test_attr_not_existing(self):
from transformers.models.auto.auto_factory import _LazyAutoMapping

12
tests/models/auto/test_modeling_tf_auto.py
View File

@@ -301,14 +301,14 @@ class TFAutoModelTest(unittest.TestCase):
_ = TFAutoModel.from_pretrained("hf-internal-testing/tiny-random-bert")
with RequestCounter() as counter:
_ = TFAutoModel.from_pretrained("hf-internal-testing/tiny-random-bert")
self.assertEqual(counter.get_request_count, 0)
self.assertEqual(counter.head_request_count, 1)
self.assertEqual(counter.other_request_count, 0)
self.assertEqual(counter["GET"], 0)
self.assertEqual(counter["HEAD"], 1)
self.assertEqual(counter.total_calls, 1)
# With a sharded checkpoint
_ = TFAutoModel.from_pretrained("ArthurZ/tiny-random-bert-sharded")
with RequestCounter() as counter:
_ = TFAutoModel.from_pretrained("ArthurZ/tiny-random-bert-sharded")
self.assertEqual(counter.get_request_count, 0)
self.assertEqual(counter.head_request_count, 1)
self.assertEqual(counter.other_request_count, 0)
self.assertEqual(counter["GET"], 0)
self.assertEqual(counter["HEAD"], 1)
self.assertEqual(counter.total_calls, 1)

9
tests/models/auto/test_tokenization_auto.py
View File

@@ -419,14 +419,11 @@ class AutoTokenizerTest(unittest.TestCase):
):
_ = AutoTokenizer.from_pretrained(DUMMY_UNKNOWN_IDENTIFIER, revision="aaaaaa")
@unittest.skip(
"Currently failing with new huggingface_hub release. See: https://github.com/huggingface/transformers/pull/27389"
)
def test_cached_tokenizer_has_minimum_calls_to_head(self):
# Make sure we have cached the tokenizer.
_ = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert")
with RequestCounter() as counter:
_ = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert")
self.assertEqual(counter.get_request_count, 0)
self.assertEqual(counter.head_request_count, 1)
self.assertEqual(counter.other_request_count, 0)
self.assertEqual(counter["GET"], 0)
self.assertEqual(counter["HEAD"], 1)
self.assertEqual(counter.total_calls, 1)

6
tests/pipelines/test_pipelines_common.py
View File

@@ -763,9 +763,9 @@ class CustomPipelineTest(unittest.TestCase):
_ = pipeline("text-classification", model="hf-internal-testing/tiny-random-bert")
with RequestCounter() as counter:
_ = pipeline("text-classification", model="hf-internal-testing/tiny-random-bert")
self.assertEqual(counter.get_request_count, 0)
self.assertEqual(counter.head_request_count, 1)
self.assertEqual(counter.other_request_count, 0)
self.assertEqual(counter["GET"], 0)
self.assertEqual(counter["HEAD"], 1)
self.assertEqual(counter.total_calls, 1)
@require_torch
def test_chunk_pipeline_batching_single_file(self):