🔥py38 + torch 2 🔥🔥🔥🚀 (#22204)
* py38 + torch 2 * increment cache versions --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
@@ -12,7 +12,7 @@ jobs:
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# Ensure running with CircleCI/huggingface
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check_circleci_user:
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docker:
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- image: cimg/python:3.7.12
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- image: cimg/python:3.8.12
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parallelism: 1
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steps:
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- run: echo $CIRCLE_PROJECT_USERNAME
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@@ -26,7 +26,7 @@ jobs:
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fetch_tests:
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working_directory: ~/transformers
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docker:
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- image: cimg/python:3.7.12
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- image: cimg/python:3.8.12
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parallelism: 1
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steps:
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- checkout
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@@ -85,7 +85,7 @@ jobs:
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fetch_all_tests:
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working_directory: ~/transformers
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docker:
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- image: cimg/python:3.7.12
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- image: cimg/python:3.8.12
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parallelism: 1
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steps:
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- checkout
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@@ -111,7 +111,7 @@ jobs:
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check_code_quality:
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working_directory: ~/transformers
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docker:
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- image: cimg/python:3.7.12
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- image: cimg/python:3.8.12
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resource_class: large
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environment:
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TRANSFORMERS_IS_CI: yes
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@@ -121,8 +121,8 @@ jobs:
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- checkout
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- restore_cache:
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keys:
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- v0.5-code_quality-{{ checksum "setup.py" }}
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- v0.5-code-quality
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- v0.6-code_quality-{{ checksum "setup.py" }}
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- v0.6-code-quality
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- run: pip install --upgrade pip
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- run: pip install .[all,quality]
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- save_cache:
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@@ -144,7 +144,7 @@ jobs:
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check_repository_consistency:
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working_directory: ~/transformers
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docker:
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- image: cimg/python:3.7.12
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- image: cimg/python:3.8.12
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resource_class: large
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environment:
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TRANSFORMERS_IS_CI: yes
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@@ -154,8 +154,8 @@ jobs:
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- checkout
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- restore_cache:
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keys:
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- v0.5-repository_consistency-{{ checksum "setup.py" }}
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- v0.5-repository_consistency
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- v0.6-repository_consistency-{{ checksum "setup.py" }}
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- v0.6-repository_consistency
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- run: pip install --upgrade pip
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- run: pip install .[all,quality]
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- save_cache:
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@@ -33,7 +33,7 @@ COMMON_ENV_VARIABLES = {
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"RUN_PT_FLAX_CROSS_TESTS": False,
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}
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COMMON_PYTEST_OPTIONS = {"max-worker-restart": 0, "dist": "loadfile", "s": None}
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DEFAULT_DOCKER_IMAGE = [{"image": "cimg/python:3.7.12"}]
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DEFAULT_DOCKER_IMAGE = [{"image": "cimg/python:3.8.12"}]
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@dataclass
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@@ -41,7 +41,7 @@ class CircleCIJob:
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name: str
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additional_env: Dict[str, Any] = None
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cache_name: str = None
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cache_version: str = "0.5"
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cache_version: str = "0.6"
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docker_image: List[Dict[str, str]] = None
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install_steps: List[str] = None
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marker: Optional[str] = None
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@@ -2450,7 +2450,7 @@ class GenerationIntegrationTests(unittest.TestCase, GenerationIntegrationTestsMi
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"top_k": 10,
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"temperature": 0.7,
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}
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expectation = 15
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expectation = 20
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tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
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text = """Hello, my dog is cute and"""
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@@ -1,4 +1,5 @@
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import os
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import unittest
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from pathlib import Path
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from tempfile import NamedTemporaryFile
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from unittest import TestCase
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@@ -499,6 +500,7 @@ class OnnxExportTestCaseV2(TestCase):
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class StableDropoutTestCase(TestCase):
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"""Tests export of StableDropout module."""
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@unittest.skip("torch 2.0.0 gives `torch.onnx.errors.OnnxExporterError: Module onnx is not installed!`.")
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@require_torch
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@pytest.mark.filterwarnings("ignore:.*Dropout.*:UserWarning:torch.onnx.*") # torch.onnx is spammy.
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def test_training(self):
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@@ -78,9 +78,14 @@ class ZeroShotImageClassificationPipelineTests(unittest.TestCase):
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image = Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png")
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output = image_classifier(image, candidate_labels=["a", "b", "c"])
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self.assertEqual(
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# The floating scores are so close, we enter floating error approximation and the order is not guaranteed across
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# python and torch versions.
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self.assertIn(
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nested_simplify(output),
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[
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[{"score": 0.333, "label": "a"}, {"score": 0.333, "label": "b"}, {"score": 0.333, "label": "c"}],
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[{"score": 0.333, "label": "a"}, {"score": 0.333, "label": "c"}, {"score": 0.333, "label": "b"}],
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],
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)
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output = image_classifier([image] * 5, candidate_labels=["A", "B", "C"], batch_size=2)
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@@ -1855,6 +1855,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
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self.assertAlmostEqual(metrics["eval_loss"], original_eval_loss)
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torchdynamo.reset()
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@unittest.skip("torch 2.0.0 gives `ModuleNotFoundError: No module named 'torchdynamo'`.")
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@require_torch_non_multi_gpu
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@require_torchdynamo
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def test_torchdynamo_memory(self):
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