transformers-cli: LFS multipart uploads (> 5GB) (#8663)
* initial commit * [cli] lfs commands * Fix FileSlice * Tweak to FileSlice * [hf_api] Backport filetype arg from `datasets` cc @lhoestq * Silm down the CI while i'm working * Ok let's try this in CI * Update config.yml * Do not try this at home * one more try * Update lfs.py * Revert "Tweak to FileSlice" This reverts commit d7e32c4b3500400486411e85a2b74e57fb6b52f5. * Update test_hf_api.py * Update test_hf_api.py * Update test_hf_api.py * CI still green? * make CI green again? * Update test_hf_api.py * make CI red again? * Update test_hf_api.py * add CI style back * Fix CI? * oh my * doc + switch back to real staging endpoint * Apply suggestions from code review Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Pierric Cistac <Pierrci@users.noreply.github.com> * Fix docblock + f-strings Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Pierric Cistac <Pierrci@users.noreply.github.com>
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@@ -62,6 +62,7 @@ _run_slow_tests = parse_flag_from_env("RUN_SLOW", default=False)
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_run_pt_tf_cross_tests = parse_flag_from_env("RUN_PT_TF_CROSS_TESTS", default=False)
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_run_custom_tokenizers = parse_flag_from_env("RUN_CUSTOM_TOKENIZERS", default=False)
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_run_pipeline_tests = parse_flag_from_env("RUN_PIPELINE_TESTS", default=False)
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_run_git_lfs_tests = parse_flag_from_env("RUN_GIT_LFS_TESTS", default=False)
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_tf_gpu_memory_limit = parse_int_from_env("TF_GPU_MEMORY_LIMIT", default=None)
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@@ -129,6 +130,19 @@ def custom_tokenizers(test_case):
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return test_case
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def require_git_lfs(test_case):
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"""
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Decorator marking a test that requires git-lfs.
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git-lfs requires additional dependencies, and tests are skipped by default. Set the RUN_GIT_LFS_TESTS environment
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variable to a truthy value to run them.
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"""
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if not _run_git_lfs_tests:
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return unittest.skip("test of git lfs workflow")(test_case)
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else:
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return test_case
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def require_torch(test_case):
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"""
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Decorator marking a test that requires PyTorch.
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