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Rework pipeline tests (#19366)

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* Rework pipeline tests

* Try to fix Flax tests

* Try to put it before

* Use a new decorator instead

* Remove ignore marker since it doesn't work

* Filter pipeline tests

* Woopsie

* Use the fitlered list

* Clean up and fake modif

* Remove init

* Revert fake modif
This commit is contained in:
Sylvain Gugger
2022-10-07 18:01:58 -04:00
committed by GitHub
parent 983451a13e
commit 9ac586b3c8
27 changed files with 95 additions and 149 deletions
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32
src/transformers/testing_utils.py
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@@ -133,7 +133,6 @@ _run_pt_tf_cross_tests = parse_flag_from_env("RUN_PT_TF_CROSS_TESTS", default=Fa
_run_pt_flax_cross_tests = parse_flag_from_env("RUN_PT_FLAX_CROSS_TESTS", default=False)
_run_custom_tokenizers = parse_flag_from_env("RUN_CUSTOM_TOKENIZERS", default=False)
_run_staging = parse_flag_from_env("HUGGINGFACE_CO_STAGING", default=False)
_run_pipeline_tests = parse_flag_from_env("RUN_PIPELINE_TESTS", default=False)
_run_git_lfs_tests = parse_flag_from_env("RUN_GIT_LFS_TESTS", default=False)
_tf_gpu_memory_limit = parse_int_from_env("TF_GPU_MEMORY_LIMIT", default=None)
@@ -176,25 +175,6 @@ def is_pt_flax_cross_test(test_case):
return pytest.mark.is_pt_flax_cross_test()(test_case)
def is_pipeline_test(test_case):
"""
Decorator marking a test as a pipeline test.
Pipeline tests are skipped by default and we can run only them by setting RUN_PIPELINE_TESTS environment variable
to a truthy value and selecting the is_pipeline_test pytest mark.
"""
if not _run_pipeline_tests:
return unittest.skip("test is pipeline test")(test_case)
else:
try:
import pytest # We don't need a hard dependency on pytest in the main library
except ImportError:
return test_case
else:
return pytest.mark.is_pipeline_test()(test_case)
def is_staging_test(test_case):
"""
Decorator marking a test as a staging test.
@@ -309,6 +289,18 @@ def require_torch(test_case):
return unittest.skipUnless(is_torch_available(), "test requires PyTorch")(test_case)
def require_torch_or_tf(test_case):
"""
Decorator marking a test that requires PyTorch or TensorFlow.
These tests are skipped when neither PyTorch not TensorFlow is installed.
"""
return unittest.skipUnless(is_torch_available() or is_tf_available(), "test requires PyTorch or TensorFlow")(
test_case
)
def require_intel_extension_for_pytorch(test_case):
"""
Decorator marking a test that requires Intel Extension for PyTorch.