Support for version spec in requires & arbitrary mismatching depths across folders (#37854)
* Support for version spec in requires & arbitrary mismatching depths * Quality * Testing
This commit is contained in:
Lysandre Debut
@@ -1,11 +1,19 @@
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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 typing import Callable
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from transformers.utils.import_utils import define_import_structure, spread_import_structure
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import pytest
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from transformers.utils.import_utils import (
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Backend,
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VersionComparison,
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define_import_structure,
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spread_import_structure,
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)
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import_structures = Path("import_structures")
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import_structures = Path(__file__).parent / "import_structures"
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def fetch__all__(file_content):
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@@ -36,26 +44,39 @@ class TestImportStructures(unittest.TestCase):
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models_path = base_transformers_path / "src" / "transformers" / "models"
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models_import_structure = spread_import_structure(define_import_structure(models_path))
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# TODO: Lysandre
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# See https://app.circleci.com/pipelines/github/huggingface/transformers/104762/workflows/7ba9c6f7-a3b2-44e6-8eaf-749c7b7261f7/jobs/1393260/tests
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@unittest.skip(reason="failing")
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def test_definition(self):
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import_structure = define_import_structure(import_structures)
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import_structure_definition = {
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frozenset(()): {
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"import_structure_raw_register": {"A0", "a0", "A4"},
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valid_frozensets: dict[frozenset | frozenset[str], dict[str, set[str]]] = {
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frozenset(): {
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"import_structure_raw_register": {"A0", "A4", "a0"},
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"import_structure_register_with_comments": {"B0", "b0"},
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},
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frozenset(("tf", "torch")): {
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"import_structure_raw_register": {"A1", "a1", "A2", "a2", "A3", "a3"},
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"import_structure_register_with_comments": {"B1", "b1", "B2", "b2", "B3", "b3"},
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frozenset({"random_item_that_should_not_exist"}): {"failing_export": {"A0"}},
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frozenset({"torch"}): {
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"import_structure_register_with_duplicates": {"C0", "C1", "C2", "C3", "c0", "c1", "c2", "c3"}
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},
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frozenset(("torch",)): {
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"import_structure_register_with_duplicates": {"C0", "c0", "C1", "c1", "C2", "c2", "C3", "c3"},
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frozenset({"tf", "torch"}): {
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"import_structure_raw_register": {"A1", "A2", "A3", "a1", "a2", "a3"},
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"import_structure_register_with_comments": {"B1", "B2", "B3", "b1", "b2", "b3"},
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},
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frozenset({"torch>=2.5"}): {"import_structure_raw_register_with_versions": {"D0", "d0"}},
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frozenset({"torch>2.5"}): {"import_structure_raw_register_with_versions": {"D1", "d1"}},
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frozenset({"torch<=2.5"}): {"import_structure_raw_register_with_versions": {"D2", "d2"}},
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frozenset({"torch<2.5"}): {"import_structure_raw_register_with_versions": {"D3", "d3"}},
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frozenset({"torch==2.5"}): {"import_structure_raw_register_with_versions": {"D4", "d4"}},
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frozenset({"torch!=2.5"}): {"import_structure_raw_register_with_versions": {"D5", "d5"}},
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frozenset({"torch>=2.5", "accelerate<0.20"}): {
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"import_structure_raw_register_with_versions": {"D6", "d6"}
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},
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}
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self.assertDictEqual(import_structure, import_structure_definition)
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self.assertEqual(len(import_structure.keys()), len(valid_frozensets.keys()))
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for _frozenset in valid_frozensets.keys():
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self.assertTrue(_frozenset in import_structure)
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self.assertListEqual(list(import_structure[_frozenset].keys()), list(valid_frozensets[_frozenset].keys()))
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for module, objects in valid_frozensets[_frozenset].items():
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self.assertTrue(module in import_structure[_frozenset])
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self.assertSetEqual(objects, import_structure[_frozenset][module])
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def test_transformers_specific_model_import(self):
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"""
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@@ -96,9 +117,92 @@ class TestImportStructures(unittest.TestCase):
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)
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self.assertListEqual(sorted(objects), sorted(_all), msg=error_message)
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# TODO: Lysandre
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# See https://app.circleci.com/pipelines/github/huggingface/transformers/104762/workflows/7ba9c6f7-a3b2-44e6-8eaf-749c7b7261f7/jobs/1393260/tests
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@unittest.skip(reason="failing")
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def test_export_backend_should_be_defined(self):
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with self.assertRaisesRegex(ValueError, "Backend should be defined in the BACKENDS_MAPPING"):
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pass
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def test_import_spread(self):
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"""
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This test is specifically designed to test that varying levels of depth across import structures are
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respected.
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In this instance, frozensets are at respective depths of 1, 2 and 3, for example:
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- models.{frozensets}
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- models.albert.{frozensets}
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- models.deprecated.transfo_xl.{frozensets}
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"""
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initial_import_structure = {
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frozenset(): {"dummy_non_model": {"DummyObject"}},
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"models": {
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frozenset(): {"dummy_config": {"DummyConfig"}},
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"albert": {
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frozenset(): {"configuration_albert": {"AlbertConfig", "AlbertOnnxConfig"}},
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frozenset({"torch"}): {
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"modeling_albert": {
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"AlbertForMaskedLM",
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}
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},
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},
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"llama": {
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frozenset(): {"configuration_llama": {"LlamaConfig"}},
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frozenset({"torch"}): {
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"modeling_llama": {
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"LlamaForCausalLM",
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}
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},
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},
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"deprecated": {
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"transfo_xl": {
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frozenset({"torch"}): {
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"modeling_transfo_xl": {
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"TransfoXLModel",
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}
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},
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frozenset(): {
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"configuration_transfo_xl": {"TransfoXLConfig"},
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"tokenization_transfo_xl": {"TransfoXLCorpus", "TransfoXLTokenizer"},
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},
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},
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"deta": {
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frozenset({"torch"}): {
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"modeling_deta": {"DetaForObjectDetection", "DetaModel", "DetaPreTrainedModel"}
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},
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frozenset(): {"configuration_deta": {"DetaConfig"}},
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frozenset({"vision"}): {"image_processing_deta": {"DetaImageProcessor"}},
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},
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},
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},
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}
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ground_truth_spread_import_structure = {
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frozenset(): {
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"dummy_non_model": {"DummyObject"},
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"models.dummy_config": {"DummyConfig"},
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"models.albert.configuration_albert": {"AlbertConfig", "AlbertOnnxConfig"},
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"models.llama.configuration_llama": {"LlamaConfig"},
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"models.deprecated.transfo_xl.configuration_transfo_xl": {"TransfoXLConfig"},
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"models.deprecated.transfo_xl.tokenization_transfo_xl": {"TransfoXLCorpus", "TransfoXLTokenizer"},
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"models.deprecated.deta.configuration_deta": {"DetaConfig"},
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},
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frozenset({"torch"}): {
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"models.albert.modeling_albert": {"AlbertForMaskedLM"},
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"models.llama.modeling_llama": {"LlamaForCausalLM"},
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"models.deprecated.transfo_xl.modeling_transfo_xl": {"TransfoXLModel"},
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"models.deprecated.deta.modeling_deta": {"DetaForObjectDetection", "DetaModel", "DetaPreTrainedModel"},
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},
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frozenset({"vision"}): {"models.deprecated.deta.image_processing_deta": {"DetaImageProcessor"}},
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}
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newly_spread_import_structure = spread_import_structure(initial_import_structure)
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self.assertEqual(ground_truth_spread_import_structure, newly_spread_import_structure)
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@pytest.mark.parametrize(
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"backend,package_name,version_comparison,version",
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[
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pytest.param(Backend("torch>=2.5 "), "torch", VersionComparison.GREATER_THAN_OR_EQUAL.value, "2.5"),
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pytest.param(Backend("tf<=1"), "tf", VersionComparison.LESS_THAN_OR_EQUAL.value, "1"),
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pytest.param(Backend("torchvision==0.19.1"), "torchvision", VersionComparison.EQUAL.value, "0.19.1"),
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],
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)
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def test_backend_specification(backend: Backend, package_name: str, version_comparison: Callable, version: str):
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assert backend.package_name == package_name
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assert VersionComparison.from_string(backend.version_comparison) == version_comparison
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assert backend.version == version
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