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Unverified Commit df6eee92 authored by Yih-Dar's avatar Yih-Dar Committed by GitHub
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Follow up for #31973 (#32025) 



* fix

* [test_all] trigger full CI

---------
Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
parent de231889
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Showing with 825 additions and 690 deletions
tests/generation/test_configuration_utils.py
View file @ df6eee92
......@@ -18,10 +18,10 @@ import os
import tempfile
import unittest
import warnings
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.generation import GenerationMode
......@@ -228,72 +228,88 @@ class ConfigPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-generation-config")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="valid_org/test-generation-config-org")
except HTTPError:
pass
def test_push_to_hub(self):
config = GenerationConfig(
do_sample=True,
temperature=0.7,
length_penalty=1.0,
)
config.push_to_hub("test-generation-config", token=self._token)
new_config = GenerationConfig.from_pretrained(f"{USER}/test-generation-config")
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
@staticmethod
def _try_delete_repo(repo_id, token):
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-generation-config")
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
# Push to hub via save_pretrained
def test_push_to_hub(self):
with tempfile.TemporaryDirectory() as tmp_dir:
config.save_pretrained(tmp_dir, repo_id="test-generation-config", push_to_hub=True, token=self._token)
new_config = GenerationConfig.from_pretrained(f"{USER}/test-generation-config")
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
try:
tmp_repo = f"{USER}/test-generation-config-{Path(tmp_dir).name}"
config = GenerationConfig(
do_sample=True,
temperature=0.7,
length_penalty=1.0,
)
config.push_to_hub(tmp_repo, token=self._token)
new_config = GenerationConfig.from_pretrained(tmp_repo)
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-generation-config-{Path(tmp_dir).name}"
config = GenerationConfig(
do_sample=True,
temperature=0.7,
length_penalty=1.0,
)
# Push to hub via save_pretrained
config.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_config = GenerationConfig.from_pretrained(tmp_repo)
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization(self):
config = GenerationConfig(
do_sample=True,
temperature=0.7,
length_penalty=1.0,
)
config.push_to_hub("valid_org/test-generation-config-org", token=self._token)
new_config = GenerationConfig.from_pretrained("valid_org/test-generation-config-org")
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-generation-config-org")
except: # noqa E722
pass
# Push to hub via save_pretrained
with tempfile.TemporaryDirectory() as tmp_dir:
config.save_pretrained(
tmp_dir, repo_id="valid_org/test-generation-config-org", push_to_hub=True, token=self._token
)
new_config = GenerationConfig.from_pretrained("valid_org/test-generation-config-org")
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
try:
tmp_repo = f"valid_org/test-generation-config-org-{Path(tmp_dir).name}"
config = GenerationConfig(
do_sample=True,
temperature=0.7,
length_penalty=1.0,
)
config.push_to_hub(tmp_repo, token=self._token)
new_config = GenerationConfig.from_pretrained(tmp_repo)
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"valid_org/test-generation-config-org-{Path(tmp_dir).name}"
config = GenerationConfig(
do_sample=True,
temperature=0.7,
length_penalty=1.0,
)
# Push to hub via save_pretrained
config.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_config = GenerationConfig.from_pretrained(tmp_repo)
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
tests/models/auto/test_processor_auto.py
View file @ df6eee92
......@@ -20,10 +20,8 @@ import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from uuid import uuid4
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
......@@ -374,69 +372,73 @@ class ProcessorPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-processor")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="valid_org/test-processor-org")
except HTTPError:
pass
@staticmethod
def _try_delete_repo(repo_id, token):
try:
delete_repo(token=cls._token, repo_id="test-dynamic-processor")
except HTTPError:
# Reset repo
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
def test_push_to_hub(self):
processor = Wav2Vec2Processor.from_pretrained(SAMPLE_PROCESSOR_CONFIG_DIR)
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
processor.save_pretrained(os.path.join(tmp_dir, "test-processor"), push_to_hub=True, token=self._token)
new_processor = Wav2Vec2Processor.from_pretrained(f"{USER}/test-processor")
for k, v in processor.feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_processor.feature_extractor, k))
self.assertDictEqual(new_processor.tokenizer.get_vocab(), processor.tokenizer.get_vocab())
def test_push_to_hub_in_organization(self):
processor = Wav2Vec2Processor.from_pretrained(SAMPLE_PROCESSOR_CONFIG_DIR)
try:
tmp_repo = f"{USER}/test-processor-{Path(tmp_dir).name}"
processor = Wav2Vec2Processor.from_pretrained(SAMPLE_PROCESSOR_CONFIG_DIR)
# Push to hub via save_pretrained
processor.save_pretrained(tmp_repo, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_processor = Wav2Vec2Processor.from_pretrained(tmp_repo)
for k, v in processor.feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_processor.feature_extractor, k))
self.assertDictEqual(new_processor.tokenizer.get_vocab(), processor.tokenizer.get_vocab())
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
processor.save_pretrained(
os.path.join(tmp_dir, "test-processor-org"),
push_to_hub=True,
token=self._token,
organization="valid_org",
)
try:
tmp_repo = f"valid_org/test-processor-org-{Path(tmp_dir).name}"
processor = Wav2Vec2Processor.from_pretrained(SAMPLE_PROCESSOR_CONFIG_DIR)
# Push to hub via save_pretrained
processor.save_pretrained(
tmp_dir,
repo_id=tmp_repo,
push_to_hub=True,
token=self._token,
)
new_processor = Wav2Vec2Processor.from_pretrained("valid_org/test-processor-org")
for k, v in processor.feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_processor.feature_extractor, k))
self.assertDictEqual(new_processor.tokenizer.get_vocab(), processor.tokenizer.get_vocab())
new_processor = Wav2Vec2Processor.from_pretrained(tmp_repo)
for k, v in processor.feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_processor.feature_extractor, k))
self.assertDictEqual(new_processor.tokenizer.get_vocab(), processor.tokenizer.get_vocab())
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_dynamic_processor(self):
CustomFeatureExtractor.register_for_auto_class()
CustomTokenizer.register_for_auto_class()
CustomProcessor.register_for_auto_class()
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-dynamic-processor-{Path(tmp_dir).name}"
feature_extractor = CustomFeatureExtractor.from_pretrained(SAMPLE_PROCESSOR_CONFIG_DIR)
CustomFeatureExtractor.register_for_auto_class()
CustomTokenizer.register_for_auto_class()
CustomProcessor.register_for_auto_class()
with tempfile.TemporaryDirectory() as tmp_dir:
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = CustomTokenizer(vocab_file)
feature_extractor = CustomFeatureExtractor.from_pretrained(SAMPLE_PROCESSOR_CONFIG_DIR)
processor = CustomProcessor(feature_extractor, tokenizer)
with tempfile.TemporaryDirectory() as tmp_dir:
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = CustomTokenizer(vocab_file)
random_repo_id = f"{USER}/test-dynamic-processor-{uuid4()}"
try:
with tempfile.TemporaryDirectory() as tmp_dir:
create_repo(random_repo_id, token=self._token)
repo = Repository(tmp_dir, clone_from=random_repo_id, token=self._token)
processor = CustomProcessor(feature_extractor, tokenizer)
create_repo(tmp_repo, token=self._token)
repo = Repository(tmp_dir, clone_from=tmp_repo, token=self._token)
processor.save_pretrained(tmp_dir)
# This has added the proper auto_map field to the feature extractor config
......@@ -466,8 +468,10 @@ class ProcessorPushToHubTester(unittest.TestCase):
repo.push_to_hub()
new_processor = AutoProcessor.from_pretrained(random_repo_id, trust_remote_code=True)
# Can't make an isinstance check because the new_processor is from the CustomProcessor class of a dynamic module
self.assertEqual(new_processor.__class__.__name__, "CustomProcessor")
finally:
delete_repo(repo_id=random_repo_id)
new_processor = AutoProcessor.from_pretrained(tmp_repo, trust_remote_code=True)
# Can't make an isinstance check because the new_processor is from the CustomProcessor class of a dynamic module
self.assertEqual(new_processor.__class__.__name__, "CustomProcessor")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
tests/utils/test_configuration_utils.py
View file @ df6eee92
......@@ -98,88 +98,106 @@ class ConfigPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-config")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="valid_org/test-config-org")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="test-dynamic-config")
except HTTPError:
pass
def test_push_to_hub(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
config.push_to_hub("test-config", token=self._token)
new_config = BertConfig.from_pretrained(f"{USER}/test-config")
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
@staticmethod
def _try_delete_repo(repo_id, token):
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-config")
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
# Push to hub via save_pretrained
def test_push_to_hub(self):
with tempfile.TemporaryDirectory() as tmp_dir:
config.save_pretrained(tmp_dir, repo_id="test-config", push_to_hub=True, token=self._token)
new_config = BertConfig.from_pretrained(f"{USER}/test-config")
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
try:
tmp_repo = f"{USER}/test-config-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
config.push_to_hub(tmp_repo, token=self._token)
new_config = BertConfig.from_pretrained(tmp_repo)
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-config-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
# Push to hub via save_pretrained
config.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_config = BertConfig.from_pretrained(tmp_repo)
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
config.push_to_hub("valid_org/test-config-org", token=self._token)
new_config = BertConfig.from_pretrained("valid_org/test-config-org")
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-config-org")
except: # noqa E722
pass
# Push to hub via save_pretrained
with tempfile.TemporaryDirectory() as tmp_dir:
config.save_pretrained(tmp_dir, repo_id="valid_org/test-config-org", push_to_hub=True, token=self._token)
new_config = BertConfig.from_pretrained("valid_org/test-config-org")
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
try:
tmp_repo = f"valid_org/test-config-org-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
config.push_to_hub(tmp_repo, token=self._token)
new_config = BertConfig.from_pretrained(tmp_repo)
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"valid_org/test-config-org-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
# Push to hub via save_pretrained
config.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_config = BertConfig.from_pretrained(tmp_repo)
for k, v in config.to_dict().items():
if k != "transformers_version":
self.assertEqual(v, getattr(new_config, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_dynamic_config(self):
CustomConfig.register_for_auto_class()
config = CustomConfig(attribute=42)
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-dynamic-config-{Path(tmp_dir).name}"
CustomConfig.register_for_auto_class()
config = CustomConfig(attribute=42)
config.push_to_hub("test-dynamic-config", token=self._token)
config.push_to_hub(tmp_repo, token=self._token)
# This has added the proper auto_map field to the config
self.assertDictEqual(config.auto_map, {"AutoConfig": "custom_configuration.CustomConfig"})
# This has added the proper auto_map field to the config
self.assertDictEqual(config.auto_map, {"AutoConfig": "custom_configuration.CustomConfig"})
new_config = AutoConfig.from_pretrained(f"{USER}/test-dynamic-config", trust_remote_code=True)
# Can't make an isinstance check because the new_config is from the FakeConfig class of a dynamic module
self.assertEqual(new_config.__class__.__name__, "CustomConfig")
self.assertEqual(new_config.attribute, 42)
new_config = AutoConfig.from_pretrained(tmp_repo, trust_remote_code=True)
# Can't make an isinstance check because the new_config is from the FakeConfig class of a dynamic module
self.assertEqual(new_config.__class__.__name__, "CustomConfig")
self.assertEqual(new_config.attribute, 42)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
class ConfigTestUtils(unittest.TestCase):
......
tests/utils/test_feature_extraction_utils.py
View file @ df6eee92
......@@ -60,85 +60,91 @@ class FeatureExtractorPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-feature-extractor")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="valid_org/test-feature-extractor-org")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="test-dynamic-feature-extractor")
except HTTPError:
pass
def test_push_to_hub(self):
feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
feature_extractor.push_to_hub("test-feature-extractor", token=self._token)
new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(f"{USER}/test-feature-extractor")
for k, v in feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_feature_extractor, k))
@staticmethod
def _try_delete_repo(repo_id, token):
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-feature-extractor")
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
# Push to hub via save_pretrained
def test_push_to_hub(self):
with tempfile.TemporaryDirectory() as tmp_dir:
feature_extractor.save_pretrained(
tmp_dir, repo_id="test-feature-extractor", push_to_hub=True, token=self._token
)
new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(f"{USER}/test-feature-extractor")
for k, v in feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_feature_extractor, k))
def test_push_to_hub_in_organization(self):
feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
feature_extractor.push_to_hub("valid_org/test-feature-extractor", token=self._token)
try:
tmp_repo = f"{USER}/test-feature-extractor-{Path(tmp_dir).name}"
new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("valid_org/test-feature-extractor")
for k, v in feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_feature_extractor, k))
feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
feature_extractor.push_to_hub(tmp_repo, token=self._token)
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-feature-extractor")
except: # noqa E722
pass
new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(tmp_repo)
for k, v in feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_feature_extractor, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
# Push to hub via save_pretrained
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
feature_extractor.save_pretrained(
tmp_dir, repo_id="valid_org/test-feature-extractor-org", push_to_hub=True, token=self._token
)
try:
tmp_repo = f"{USER}/test-feature-extractor-{Path(tmp_dir).name}"
feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
# Push to hub via save_pretrained
feature_extractor.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(tmp_repo)
for k, v in feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_feature_extractor, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("valid_org/test-feature-extractor-org")
for k, v in feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_feature_extractor, k))
def test_push_to_hub_in_organization(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"valid_org/test-feature-extractor-{Path(tmp_dir).name}"
feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
feature_extractor.push_to_hub(tmp_repo, token=self._token)
new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(tmp_repo)
for k, v in feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_feature_extractor, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"valid_org/test-feature-extractor-{Path(tmp_dir).name}"
feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
# Push to hub via save_pretrained
feature_extractor.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(tmp_repo)
for k, v in feature_extractor.__dict__.items():
self.assertEqual(v, getattr(new_feature_extractor, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_dynamic_feature_extractor(self):
CustomFeatureExtractor.register_for_auto_class()
feature_extractor = CustomFeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
feature_extractor.push_to_hub("test-dynamic-feature-extractor", token=self._token)
# This has added the proper auto_map field to the config
self.assertDictEqual(
feature_extractor.auto_map,
{"AutoFeatureExtractor": "custom_feature_extraction.CustomFeatureExtractor"},
)
new_feature_extractor = AutoFeatureExtractor.from_pretrained(
f"{USER}/test-dynamic-feature-extractor", trust_remote_code=True
)
# Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
self.assertEqual(new_feature_extractor.__class__.__name__, "CustomFeatureExtractor")
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-dynamic-feature-extractor-{Path(tmp_dir).name}"
CustomFeatureExtractor.register_for_auto_class()
feature_extractor = CustomFeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
feature_extractor.push_to_hub(tmp_repo, token=self._token)
# This has added the proper auto_map field to the config
self.assertDictEqual(
feature_extractor.auto_map,
{"AutoFeatureExtractor": "custom_feature_extraction.CustomFeatureExtractor"},
)
new_feature_extractor = AutoFeatureExtractor.from_pretrained(tmp_repo, trust_remote_code=True)
# Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
self.assertEqual(new_feature_extractor.__class__.__name__, "CustomFeatureExtractor")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
tests/utils/test_image_processing_utils.py
View file @ df6eee92
......@@ -71,88 +71,93 @@ class ImageProcessorPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-image-processor")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="valid_org/test-image-processor-org")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="test-dynamic-image-processor")
except HTTPError:
pass
def test_push_to_hub(self):
image_processor = ViTImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub("test-image-processor", token=self._token)
new_image_processor = ViTImageProcessor.from_pretrained(f"{USER}/test-image-processor")
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
@staticmethod
def _try_delete_repo(repo_id, token):
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-image-processor")
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
# Push to hub via save_pretrained
def test_push_to_hub(self):
with tempfile.TemporaryDirectory() as tmp_dir:
image_processor.save_pretrained(
tmp_dir, repo_id="test-image-processor", push_to_hub=True, token=self._token
)
new_image_processor = ViTImageProcessor.from_pretrained(f"{USER}/test-image-processor")
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
try:
tmp_repo = f"{USER}/test-image-processor-{Path(tmp_dir).name}"
image_processor = ViTImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub(tmp_repo, token=self._token)
new_image_processor = ViTImageProcessor.from_pretrained(tmp_repo)
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-image-processor-{Path(tmp_dir).name}"
image_processor = ViTImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
# Push to hub via save_pretrained
image_processor.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_image_processor = ViTImageProcessor.from_pretrained(tmp_repo)
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization(self):
image_processor = ViTImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub("valid_org/test-image-processor", token=self._token)
new_image_processor = ViTImageProcessor.from_pretrained("valid_org/test-image-processor")
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-image-processor")
except: # noqa E722
pass
# Push to hub via save_pretrained
with tempfile.TemporaryDirectory() as tmp_dir:
image_processor.save_pretrained(
tmp_dir, repo_id="valid_org/test-image-processor-org", push_to_hub=True, token=self._token
)
new_image_processor = ViTImageProcessor.from_pretrained("valid_org/test-image-processor-org")
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
try:
tmp_repo = f"valid_org/test-image-processor-{Path(tmp_dir).name}"
image_processor = ViTImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub(tmp_repo, token=self._token)
new_image_processor = ViTImageProcessor.from_pretrained(tmp_repo)
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"valid_org/test-image-processor-{Path(tmp_dir).name}"
image_processor = ViTImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
# Push to hub via save_pretrained
image_processor.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_image_processor = ViTImageProcessor.from_pretrained(tmp_repo)
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_dynamic_image_processor(self):
CustomImageProcessor.register_for_auto_class()
image_processor = CustomImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub("test-dynamic-image-processor", token=self._token)
# This has added the proper auto_map field to the config
self.assertDictEqual(
image_processor.auto_map,
{"AutoImageProcessor": "custom_image_processing.CustomImageProcessor"},
)
new_image_processor = AutoImageProcessor.from_pretrained(
f"{USER}/test-dynamic-image-processor", trust_remote_code=True
)
# Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
self.assertEqual(new_image_processor.__class__.__name__, "CustomImageProcessor")
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-dynamic-image-processor-{Path(tmp_dir).name}"
CustomImageProcessor.register_for_auto_class()
image_processor = CustomImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub(tmp_repo, token=self._token)
# This has added the proper auto_map field to the config
self.assertDictEqual(
image_processor.auto_map,
{"AutoImageProcessor": "custom_image_processing.CustomImageProcessor"},
)
new_image_processor = AutoImageProcessor.from_pretrained(tmp_repo, trust_remote_code=True)
# Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
self.assertEqual(new_image_processor.__class__.__name__, "CustomImageProcessor")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
class ImageProcessingUtilsTester(unittest.TestCase):
......
tests/utils/test_modeling_flax_utils.py
View file @ df6eee92
......@@ -14,10 +14,10 @@
import tempfile
import unittest
from pathlib import Path
import numpy as np
from huggingface_hub import HfFolder, delete_repo, snapshot_download
from requests.exceptions import HTTPError
from transformers import BertConfig, BertModel, is_flax_available, is_torch_available
from transformers.testing_utils import (
......@@ -55,89 +55,103 @@ class FlaxModelPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-model-flax")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="valid_org/test-model-flax-org")
except HTTPError:
pass
def test_push_to_hub(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = FlaxBertModel(config)
model.push_to_hub("test-model-flax", token=self._token)
new_model = FlaxBertModel.from_pretrained(f"{USER}/test-model-flax")
base_params = flatten_dict(unfreeze(model.params))
new_params = flatten_dict(unfreeze(new_model.params))
for key in base_params.keys():
max_diff = (base_params[key] - new_params[key]).sum().item()
self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
@staticmethod
def _try_delete_repo(repo_id, token):
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-model-flax")
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
# Push to hub via save_pretrained
def test_push_to_hub(self):
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(tmp_dir, repo_id="test-model-flax", push_to_hub=True, token=self._token)
new_model = FlaxBertModel.from_pretrained(f"{USER}/test-model-flax")
base_params = flatten_dict(unfreeze(model.params))
new_params = flatten_dict(unfreeze(new_model.params))
for key in base_params.keys():
max_diff = (base_params[key] - new_params[key]).sum().item()
self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
try:
tmp_repo = f"{USER}/test-model-flax-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = FlaxBertModel(config)
model.push_to_hub(tmp_repo, token=self._token)
new_model = FlaxBertModel.from_pretrained(tmp_repo)
base_params = flatten_dict(unfreeze(model.params))
new_params = flatten_dict(unfreeze(new_model.params))
for key in base_params.keys():
max_diff = (base_params[key] - new_params[key]).sum().item()
self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-model-flax-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = FlaxBertModel(config)
# Push to hub via save_pretrained
model.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_model = FlaxBertModel.from_pretrained(tmp_repo)
base_params = flatten_dict(unfreeze(model.params))
new_params = flatten_dict(unfreeze(new_model.params))
for key in base_params.keys():
max_diff = (base_params[key] - new_params[key]).sum().item()
self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = FlaxBertModel(config)
model.push_to_hub("valid_org/test-model-flax-org", token=self._token)
new_model = FlaxBertModel.from_pretrained("valid_org/test-model-flax-org")
base_params = flatten_dict(unfreeze(model.params))
new_params = flatten_dict(unfreeze(new_model.params))
for key in base_params.keys():
max_diff = (base_params[key] - new_params[key]).sum().item()
self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-model-flax-org")
except: # noqa E722
pass
# Push to hub via save_pretrained
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(
tmp_dir, repo_id="valid_org/test-model-flax-org", push_to_hub=True, token=self._token
)
new_model = FlaxBertModel.from_pretrained("valid_org/test-model-flax-org")
base_params = flatten_dict(unfreeze(model.params))
new_params = flatten_dict(unfreeze(new_model.params))
for key in base_params.keys():
max_diff = (base_params[key] - new_params[key]).sum().item()
self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
try:
tmp_repo = f"valid_org/test-model-flax-org-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = FlaxBertModel(config)
model.push_to_hub(tmp_repo, token=self._token)
new_model = FlaxBertModel.from_pretrained(tmp_repo)
base_params = flatten_dict(unfreeze(model.params))
new_params = flatten_dict(unfreeze(new_model.params))
for key in base_params.keys():
max_diff = (base_params[key] - new_params[key]).sum().item()
self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"valid_org/test-model-flax-org-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = FlaxBertModel(config)
# Push to hub via save_pretrained
model.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_model = FlaxBertModel.from_pretrained(tmp_repo)
base_params = flatten_dict(unfreeze(model.params))
new_params = flatten_dict(unfreeze(new_model.params))
for key in base_params.keys():
max_diff = (base_params[key] - new_params[key]).sum().item()
self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def check_models_equal(model1, model2):
......
tests/utils/test_modeling_tf_utils.py
View file @ df6eee92
......@@ -23,6 +23,7 @@ import random
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, Repository, delete_repo, snapshot_download
from requests.exceptions import HTTPError
......@@ -682,127 +683,149 @@ class TFModelPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-model-tf")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="test-model-tf-callback")
except HTTPError:
pass
@staticmethod
def _try_delete_repo(repo_id, token):
try:
delete_repo(token=cls._token, repo_id="valid_org/test-model-tf-org")
except HTTPError:
# Reset repo
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
def test_push_to_hub(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = TFBertModel(config)
# Make sure model is properly initialized
model.build_in_name_scope()
logging.set_verbosity_info()
logger = logging.get_logger("transformers.utils.hub")
with CaptureLogger(logger) as cl:
model.push_to_hub("test-model-tf", token=self._token)
logging.set_verbosity_warning()
# Check the model card was created and uploaded.
self.assertIn("Uploading the following files to __DUMMY_TRANSFORMERS_USER__/test-model-tf", cl.out)
new_model = TFBertModel.from_pretrained(f"{USER}/test-model-tf")
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-model-tf-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = TFBertModel(config)
# Make sure model is properly initialized
model.build_in_name_scope()
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-model-tf")
except: # noqa E722
pass
logging.set_verbosity_info()
logger = logging.get_logger("transformers.utils.hub")
with CaptureLogger(logger) as cl:
model.push_to_hub(tmp_repo, token=self._token)
logging.set_verbosity_warning()
# Check the model card was created and uploaded.
self.assertIn("Uploading the following files to __DUMMY_TRANSFORMERS_USER__/test-model-tf", cl.out)
# Push to hub via save_pretrained
new_model = TFBertModel.from_pretrained(tmp_repo)
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(tmp_dir, repo_id="test-model-tf", push_to_hub=True, token=self._token)
try:
tmp_repo = f"{USER}/test-model-tf-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = TFBertModel(config)
# Make sure model is properly initialized
model.build_in_name_scope()
new_model = TFBertModel.from_pretrained(f"{USER}/test-model-tf")
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
# Push to hub via save_pretrained
model.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_model = TFBertModel.from_pretrained(tmp_repo)
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
@is_pt_tf_cross_test
def test_push_to_hub_callback(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = TFBertForMaskedLM(config)
model.compile()
with tempfile.TemporaryDirectory() as tmp_dir:
push_to_hub_callback = PushToHubCallback(
output_dir=tmp_dir,
hub_model_id="test-model-tf-callback",
hub_token=self._token,
)
model.fit(model.dummy_inputs, model.dummy_inputs, epochs=1, callbacks=[push_to_hub_callback])
try:
tmp_repo = f"{USER}/test-model-tf-callback-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = TFBertForMaskedLM(config)
model.compile()
new_model = TFBertForMaskedLM.from_pretrained(f"{USER}/test-model-tf-callback")
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
push_to_hub_callback = PushToHubCallback(
output_dir=tmp_dir,
hub_model_id=tmp_repo,
hub_token=self._token,
)
model.fit(model.dummy_inputs, model.dummy_inputs, epochs=1, callbacks=[push_to_hub_callback])
tf_push_to_hub_params = dict(inspect.signature(TFPreTrainedModel.push_to_hub).parameters)
tf_push_to_hub_params.pop("base_model_card_args")
pt_push_to_hub_params = dict(inspect.signature(PreTrainedModel.push_to_hub).parameters)
pt_push_to_hub_params.pop("deprecated_kwargs")
self.assertDictEaual(tf_push_to_hub_params, pt_push_to_hub_params)
new_model = TFBertForMaskedLM.from_pretrained(tmp_repo)
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
tf_push_to_hub_params = dict(inspect.signature(TFPreTrainedModel.push_to_hub).parameters)
tf_push_to_hub_params.pop("base_model_card_args")
pt_push_to_hub_params = dict(inspect.signature(PreTrainedModel.push_to_hub).parameters)
pt_push_to_hub_params.pop("deprecated_kwargs")
self.assertDictEaual(tf_push_to_hub_params, pt_push_to_hub_params)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = TFBertModel(config)
# Make sure model is properly initialized
model.build_in_name_scope()
model.push_to_hub("valid_org/test-model-tf-org", token=self._token)
new_model = TFBertModel.from_pretrained("valid_org/test-model-tf-org")
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"valid_org/test-model-tf-org-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = TFBertModel(config)
# Make sure model is properly initialized
model.build_in_name_scope()
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-model-tf-org")
except: # noqa E722
pass
model.push_to_hub(tmp_repo, token=self._token)
# Push to hub via save_pretrained
new_model = TFBertModel.from_pretrained(tmp_repo)
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(tmp_dir, push_to_hub=True, token=self._token, repo_id="valid_org/test-model-tf-org")
try:
tmp_repo = f"valid_org/test-model-tf-org-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = TFBertModel(config)
# Make sure model is properly initialized
model.build_in_name_scope()
new_model = TFBertModel.from_pretrained("valid_org/test-model-tf-org")
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
# Push to hub via save_pretrained
model.save_pretrained(tmp_dir, push_to_hub=True, token=self._token, repo_id=tmp_repo)
new_model = TFBertModel.from_pretrained(tmp_repo)
models_equal = True
for p1, p2 in zip(model.weights, new_model.weights):
if not tf.math.reduce_all(p1 == p2):
models_equal = False
break
self.assertTrue(models_equal)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
tests/utils/test_modeling_utils.py
View file @ df6eee92
......@@ -1876,142 +1876,168 @@ class ModelPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-model")
except HTTPError:
pass
@staticmethod
def _try_delete_repo(repo_id, token):
try:
delete_repo(token=cls._token, repo_id="valid_org/test-model-org")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="test-dynamic-model")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="test-dynamic-model-with-tags")
except HTTPError:
# Reset repo
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
@unittest.skip(reason="This test is flaky")
def test_push_to_hub(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = BertModel(config)
model.push_to_hub("test-model", token=self._token)
new_model = BertModel.from_pretrained(f"{USER}/test-model")
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-model-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = BertModel(config)
model.push_to_hub(tmp_repo, token=self._token)
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-model")
except: # noqa E722
pass
new_model = BertModel.from_pretrained(tmp_repo)
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
# Push to hub via save_pretrained
@unittest.skip(reason="This test is flaky")
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(tmp_dir, repo_id="test-model", push_to_hub=True, token=self._token)
try:
tmp_repo = f"{USER}/test-model-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = BertModel(config)
# Push to hub via save_pretrained
model.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_model = BertModel.from_pretrained(f"{USER}/test-model")
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
new_model = BertModel.from_pretrained(tmp_repo)
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_with_description(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = BertModel(config)
COMMIT_DESCRIPTION = """
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-model-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = BertModel(config)
COMMIT_DESCRIPTION = """
The commit description supports markdown synthax see:
```python
>>> form transformers import AutoConfig
>>> config = AutoConfig.from_pretrained("google-bert/bert-base-uncased")
```
"""
commit_details = model.push_to_hub(
"test-model", use_auth_token=self._token, create_pr=True, commit_description=COMMIT_DESCRIPTION
)
self.assertEqual(commit_details.commit_description, COMMIT_DESCRIPTION)
commit_details = model.push_to_hub(
tmp_repo, use_auth_token=self._token, create_pr=True, commit_description=COMMIT_DESCRIPTION
)
self.assertEqual(commit_details.commit_description, COMMIT_DESCRIPTION)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
@unittest.skip(reason="This test is flaky")
def test_push_to_hub_in_organization(self):
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = BertModel(config)
model.push_to_hub("valid_org/test-model-org", token=self._token)
new_model = BertModel.from_pretrained("valid_org/test-model-org")
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"valid_org/test-model-org-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = BertModel(config)
model.push_to_hub(tmp_repo, token=self._token)
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-model-org")
except: # noqa E722
pass
new_model = BertModel.from_pretrained(tmp_repo)
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
# Push to hub via save_pretrained
@unittest.skip(reason="This test is flaky")
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(tmp_dir, push_to_hub=True, token=self._token, repo_id="valid_org/test-model-org")
try:
tmp_repo = f"valid_org/test-model-org-{Path(tmp_dir).name}"
config = BertConfig(
vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
)
model = BertModel(config)
# Push to hub via save_pretrained
model.save_pretrained(tmp_dir, push_to_hub=True, token=self._token, repo_id=tmp_repo)
new_model = BertModel.from_pretrained("valid_org/test-model-org")
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
new_model = BertModel.from_pretrained(tmp_repo)
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_dynamic_model(self):
CustomConfig.register_for_auto_class()
CustomModel.register_for_auto_class()
config = CustomConfig(hidden_size=32)
model = CustomModel(config)
model.push_to_hub("test-dynamic-model", token=self._token)
# checks
self.assertDictEqual(
config.auto_map,
{"AutoConfig": "custom_configuration.CustomConfig", "AutoModel": "custom_modeling.CustomModel"},
)
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-dynamic-model-{Path(tmp_dir).name}"
CustomConfig.register_for_auto_class()
CustomModel.register_for_auto_class()
config = CustomConfig(hidden_size=32)
model = CustomModel(config)
model.push_to_hub(tmp_repo, token=self._token)
# checks
self.assertDictEqual(
config.auto_map,
{"AutoConfig": "custom_configuration.CustomConfig", "AutoModel": "custom_modeling.CustomModel"},
)
new_model = AutoModel.from_pretrained(f"{USER}/test-dynamic-model", trust_remote_code=True)
# Can't make an isinstance check because the new_model is from the CustomModel class of a dynamic module
self.assertEqual(new_model.__class__.__name__, "CustomModel")
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
new_model = AutoModel.from_pretrained(tmp_repo, trust_remote_code=True)
# Can't make an isinstance check because the new_model is from the CustomModel class of a dynamic module
self.assertEqual(new_model.__class__.__name__, "CustomModel")
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))
config = AutoConfig.from_pretrained(f"{USER}/test-dynamic-model", trust_remote_code=True)
new_model = AutoModel.from_config(config, trust_remote_code=True)
self.assertEqual(new_model.__class__.__name__, "CustomModel")
config = AutoConfig.from_pretrained(tmp_repo, trust_remote_code=True)
new_model = AutoModel.from_config(config, trust_remote_code=True)
self.assertEqual(new_model.__class__.__name__, "CustomModel")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_with_tags(self):
from huggingface_hub import ModelCard
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-dynamic-model-with-tags-{Path(tmp_dir).name}"
from huggingface_hub import ModelCard
new_tags = ["tag-1", "tag-2"]
new_tags = ["tag-1", "tag-2"]
CustomConfig.register_for_auto_class()
CustomModel.register_for_auto_class()
CustomConfig.register_for_auto_class()
CustomModel.register_for_auto_class()
config = CustomConfig(hidden_size=32)
model = CustomModel(config)
config = CustomConfig(hidden_size=32)
model = CustomModel(config)
self.assertTrue(model.model_tags is None)
self.assertTrue(model.model_tags is None)
model.add_model_tags(new_tags)
model.add_model_tags(new_tags)
self.assertTrue(model.model_tags == new_tags)
self.assertTrue(model.model_tags == new_tags)
model.push_to_hub("test-dynamic-model-with-tags", token=self._token)
model.push_to_hub(tmp_repo, token=self._token)
loaded_model_card = ModelCard.load(f"{USER}/test-dynamic-model-with-tags")
self.assertEqual(loaded_model_card.data.tags, new_tags)
loaded_model_card = ModelCard.load(tmp_repo)
self.assertEqual(loaded_model_card.data.tags, new_tags)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
@require_torch
......
tests/utils/test_tokenization_utils.py
View file @ df6eee92
......@@ -118,110 +118,133 @@ class TokenizerPushToHubTester(unittest.TestCase):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-tokenizer")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="valid_org/test-tokenizer-org")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="test-dynamic-tokenizer")
except HTTPError:
pass
def test_push_to_hub(self):
with tempfile.TemporaryDirectory() as tmp_dir:
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = BertTokenizer(vocab_file)
tokenizer.push_to_hub("test-tokenizer", token=self._token)
new_tokenizer = BertTokenizer.from_pretrained(f"{USER}/test-tokenizer")
self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab)
@staticmethod
def _try_delete_repo(repo_id, token):
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-tokenizer")
delete_repo(repo_id=repo_id, token=token)
except: # noqa E722
pass
# Push to hub via save_pretrained
def test_push_to_hub(self):
with tempfile.TemporaryDirectory() as tmp_dir:
tokenizer.save_pretrained(tmp_dir, repo_id="test-tokenizer", push_to_hub=True, token=self._token)
new_tokenizer = BertTokenizer.from_pretrained(f"{USER}/test-tokenizer")
self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab)
try:
tmp_repo = f"{USER}/test-tokenizer-{Path(tmp_dir).name}"
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = BertTokenizer(vocab_file)
tokenizer.push_to_hub(tmp_repo, token=self._token)
new_tokenizer = BertTokenizer.from_pretrained(tmp_repo)
self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
try:
tmp_repo = f"{USER}/test-tokenizer-{Path(tmp_dir).name}"
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = BertTokenizer(vocab_file)
# Push to hub via save_pretrained
tokenizer.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_tokenizer = BertTokenizer.from_pretrained(tmp_repo)
self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization(self):
with tempfile.TemporaryDirectory() as tmp_dir:
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = BertTokenizer(vocab_file)
tokenizer.push_to_hub("valid_org/test-tokenizer-org", token=self._token)
new_tokenizer = BertTokenizer.from_pretrained("valid_org/test-tokenizer-org")
self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab)
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-tokenizer-org")
except: # noqa E722
pass
# Push to hub via save_pretrained
try:
tmp_repo = f"valid_org/test-tokenizer-{Path(tmp_dir).name}"
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = BertTokenizer(vocab_file)
tokenizer.push_to_hub(tmp_repo, token=self._token)
new_tokenizer = BertTokenizer.from_pretrained(tmp_repo)
self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
def test_push_to_hub_in_organization_via_save_pretrained(self):
with tempfile.TemporaryDirectory() as tmp_dir:
tokenizer.save_pretrained(
tmp_dir, repo_id="valid_org/test-tokenizer-org", push_to_hub=True, token=self._token
)
new_tokenizer = BertTokenizer.from_pretrained("valid_org/test-tokenizer-org")
self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab)
try:
tmp_repo = f"valid_org/test-tokenizer-{Path(tmp_dir).name}"
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = BertTokenizer(vocab_file)
# Push to hub via save_pretrained
tokenizer.save_pretrained(tmp_dir, repo_id=tmp_repo, push_to_hub=True, token=self._token)
new_tokenizer = BertTokenizer.from_pretrained(tmp_repo)
self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab)
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
@require_tokenizers
def test_push_to_hub_dynamic_tokenizer(self):
CustomTokenizer.register_for_auto_class()
with tempfile.TemporaryDirectory() as tmp_dir:
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = CustomTokenizer(vocab_file)
try:
tmp_repo = f"{USER}/test-dynamic-tokenizer-{Path(tmp_dir).name}"
CustomTokenizer.register_for_auto_class()
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
tokenizer = CustomTokenizer(vocab_file)
# No fast custom tokenizer
tokenizer.push_to_hub("test-dynamic-tokenizer", token=self._token)
# No fast custom tokenizer
tokenizer.push_to_hub(tmp_repo, token=self._token)
tokenizer = AutoTokenizer.from_pretrained(f"{USER}/test-dynamic-tokenizer", trust_remote_code=True)
# Can't make an isinstance check because the new_model.config is from the CustomTokenizer class of a dynamic module
self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizer")
tokenizer = AutoTokenizer.from_pretrained(tmp_repo, trust_remote_code=True)
# Can't make an isinstance check because the new_model.config is from the CustomTokenizer class of a dynamic module
self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizer")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
# Fast and slow custom tokenizer
CustomTokenizerFast.register_for_auto_class()
@require_tokenizers
def test_push_to_hub_dynamic_tokenizer_with_both_slow_and_fast_classes(self):
with tempfile.TemporaryDirectory() as tmp_dir:
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
bert_tokenizer = BertTokenizerFast.from_pretrained(tmp_dir)
bert_tokenizer.save_pretrained(tmp_dir)
tokenizer = CustomTokenizerFast.from_pretrained(tmp_dir)
tokenizer.push_to_hub("test-dynamic-tokenizer", token=self._token)
tokenizer = AutoTokenizer.from_pretrained(f"{USER}/test-dynamic-tokenizer", trust_remote_code=True)
# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizerFast")
tokenizer = AutoTokenizer.from_pretrained(
f"{USER}/test-dynamic-tokenizer", use_fast=False, trust_remote_code=True
)
# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizer")
try:
tmp_repo = f"{USER}/test-dynamic-tokenizer-{Path(tmp_dir).name}"
CustomTokenizer.register_for_auto_class()
# Fast and slow custom tokenizer
CustomTokenizerFast.register_for_auto_class()
vocab_file = os.path.join(tmp_dir, "vocab.txt")
with open(vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]))
bert_tokenizer = BertTokenizerFast.from_pretrained(tmp_dir)
bert_tokenizer.save_pretrained(tmp_dir)
tokenizer = CustomTokenizerFast.from_pretrained(tmp_dir)
tokenizer.push_to_hub(tmp_repo, token=self._token)
tokenizer = AutoTokenizer.from_pretrained(tmp_repo, trust_remote_code=True)
# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizerFast")
tokenizer = AutoTokenizer.from_pretrained(tmp_repo, use_fast=False, trust_remote_code=True)
# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizer")
finally:
# Always (try to) delete the repo.
self._try_delete_repo(repo_id=tmp_repo, token=self._token)
class TrieTest(unittest.TestCase):
......
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