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

Skip tests properly (#31308)

Browse Source 
* Skip tests properly

* [test_all]

* Add 'reason' as kwarg for skipTest

* [test_all] Fix up

* [test_all]
This commit is contained in:
amyeroberts
2024-06-26 21:59:08 +01:00
committed by GitHub
parent 1f9f57ab4c
commit 1de7dc7403
254 changed files with 1721 additions and 1298 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
tests/models/gemma/test_modeling_gemma.py
View File

@@ -398,11 +398,11 @@ class GemmaModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixi
(self.model_tester.batch_size, self.model_tester.seq_length, self.model_tester.num_labels),
)
@unittest.skip("Gemma buffers include complex numbers, which breaks this test")
@unittest.skip(reason="Gemma buffers include complex numbers, which breaks this test")
def test_save_load_fast_init_from_base(self):
pass
@unittest.skip("Gemma uses GQA on all models so the KV cache is a non standard format")
@unittest.skip(reason="Gemma uses GQA on all models so the KV cache is a non standard format")
def test_past_key_values_format(self):
pass
@@ -456,7 +456,7 @@ class GemmaModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixi
@pytest.mark.flash_attn_test
@slow
def test_flash_attn_2_inference_equivalence_right_padding(self):
self.skipTest("Gemma flash attention does not support right padding")
self.skipTest(reason="Gemma flash attention does not support right padding")
@require_torch_sdpa
@require_torch_gpu
@@ -464,7 +464,7 @@ class GemmaModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixi
def test_sdpa_equivalence(self):
for model_class in self.all_model_classes:
if not model_class._supports_sdpa:
return
self.skipTest(reason="Model does not support SDPA")
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
model = model_class(config)
@@ -498,7 +498,7 @@ class GemmaModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixi
def test_flash_attn_2_equivalence(self):
for model_class in self.all_model_classes:
if not model_class._supports_flash_attn_2:
return
self.skipTest(reason="Model does not support Flash Attention 2")
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
model = model_class(config)
@@ -749,7 +749,7 @@ class GemmaIntegrationTest(unittest.TestCase):
self.assertEqual(output_text, EXPECTED_TEXTS)
@unittest.skip("The test will not fit our CI runners")
@unittest.skip(reason="The test will not fit our CI runners")
@require_read_token
def test_model_7b_fp32(self):
model_id = "google/gemma-7b"
@@ -877,7 +877,7 @@ class GemmaIntegrationTest(unittest.TestCase):
# `torch==2.2` will throw an error on this test (as in other compilation tests), but torch==2.1.2 and torch>2.2
# work as intended. See https://github.com/pytorch/pytorch/issues/121943
if version.parse(torch.__version__) < version.parse("2.3.0"):
self.skipTest("This test requires torch >= 2.3 to run.")
self.skipTest(reason="This test requires torch >= 2.3 to run.")
NUM_TOKENS_TO_GENERATE = 40
# Note on `EXPECTED_TEXT_COMPLETION`'s diff: the current value matches the original test if the original test

19
tests/models/gemma/test_tokenization_gemma.py
View File

@@ -23,7 +23,6 @@ from transformers import (
AddedToken,
GemmaTokenizer,
GemmaTokenizerFast,
is_torch_available,
)
from transformers.convert_slow_tokenizer import convert_slow_tokenizer
from transformers.testing_utils import (
@@ -43,10 +42,6 @@ from ...test_tokenization_common import TokenizerTesterMixin
SAMPLE_VOCAB = get_tests_dir("fixtures/test_sentencepiece.model")
if is_torch_available():
pass
@require_sentencepiece
@require_tokenizers
class GemmaTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
@@ -68,7 +63,7 @@ class GemmaTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
@require_torch
def test_batch_tokenization(self):
if not self.test_seq2seq:
return
self.skipTest(reason="test_seq2seq is set to False")
tokenizers = self.get_tokenizers()
for tokenizer in tokenizers:
@@ -88,7 +83,7 @@ class GemmaTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
return_tensors="pt",
)
except NotImplementedError:
return
self.skipTest(reason="Encountered NotImplementedError when calling tokenizer")
self.assertEqual(batch.input_ids.shape[1], 3)
# max_target_length will default to max_length if not specified
batch = tokenizer(text, max_length=3, return_tensors="pt")
@@ -99,7 +94,7 @@ class GemmaTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
self.assertEqual(batch_encoder_only.attention_mask.shape[1], 3)
self.assertNotIn("decoder_input_ids", batch_encoder_only)
@unittest.skip("Unfortunately way too slow to build a BPE with SentencePiece.")
@unittest.skip(reason="Unfortunately way too slow to build a BPE with SentencePiece.")
def test_save_slow_from_fast_and_reload_fast(self):
pass
@@ -147,15 +142,15 @@ class GemmaTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
padding=False,
)
@unittest.skip("worker 'gw4' crashed on CI, passing locally.")
@unittest.skip(reason="worker 'gw4' crashed on CI, passing locally.")
def test_pickle_subword_regularization_tokenizer(self):
pass
@unittest.skip("worker 'gw4' crashed on CI, passing locally.")
@unittest.skip(reason="worker 'gw4' crashed on CI, passing locally.")
def test_subword_regularization_tokenizer(self):
pass
@unittest.skip("Skipping")
@unittest.skip(reason="Skipping")
def test_torch_encode_plus_sent_to_model(self):
pass
@@ -227,7 +222,7 @@ class GemmaIntegrationTest(unittest.TestCase):
self.tokenizer.add_eos_token = False
self.rust_tokenizer.add_eos_token = False
@unittest.skip("Not super important and always failing. Let's skip it")
@unittest.skip(reason="Not super important and always failing. Let's skip it")
@slow
def test_conversion(self):
# This is excruciatingly slow since it has to recreate the entire merge