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Author SHA1 Message Date
Sylvain Gugger
bc21aaca78 Patch release v4.22.2
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2022-09-27 09:58:15 -04:00
Sylvain Gugger
38d0ee2ff2 More tests for regression in cached non existence (#19216)
* More tests for regression in cached non existence

* Style
2022-09-27 09:57:40 -04:00
Sylvain Gugger
791dbf9af4 Fix cached_file in offline mode for cached non-existing files (#19206)
* Fix cached_file in offline mode for cached non-existing files

* Add tests

* Test with offline mode
2022-09-27 09:57:35 -04:00
Sylvain Gugger
56c2c58519 Don't warn of move if cache is empty (#19109) 2022-09-27 09:57:13 -04:00
Sylvain Gugger
35807511ee Fix TrainingArguments documentation (#19162)
* Fix TrainingArguments documentation

* Fix TFTrainingArguments documentation
2022-09-22 14:43:09 -04:00
9 changed files with 155 additions and 56 deletions

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@@ -400,7 +400,7 @@ install_requires = [
setup(
name="transformers",
version="4.22.1", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
version="4.22.2", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
author="The Hugging Face team (past and future) with the help of all our contributors (https://github.com/huggingface/transformers/graphs/contributors)",
author_email="transformers@huggingface.co",
description="State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow",

View File

@@ -22,7 +22,7 @@
# to defer the actual importing for when the objects are requested. This way `import transformers` provides the names
# in the namespace without actually importing anything (and especially none of the backends).
__version__ = "4.22.1"
__version__ = "4.22.2"
from typing import TYPE_CHECKING

View File

@@ -119,7 +119,6 @@ class OptimizerNames(ExplicitEnum):
@dataclass
class TrainingArguments:
framework = "pt"
"""
TrainingArguments is the subset of the arguments we use in our example scripts **which relate to the training loop
itself**.
@@ -500,6 +499,7 @@ class TrainingArguments:
Whether to use Apple Silicon chip based `mps` device.
"""
framework = "pt"
output_dir: str = field(
metadata={"help": "The output directory where the model predictions and checkpoints will be written."},
)

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@@ -28,7 +28,6 @@ if is_tf_available():
@dataclass
class TFTrainingArguments(TrainingArguments):
framework = "tf"
"""
TrainingArguments is the subset of the arguments we use in our example scripts **which relate to the training loop
itself**.
@@ -162,6 +161,7 @@ class TFTrainingArguments(TrainingArguments):
Whether to activate the XLA compilation or not.
"""
framework = "tf"
tpu_name: Optional[str] = field(
default=None,
metadata={"help": "Name of TPU"},

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@@ -435,7 +435,7 @@ def cached_file(
except LocalEntryNotFoundError:
# We try to see if we have a cached version (not up to date):
resolved_file = try_to_load_from_cache(path_or_repo_id, full_filename, cache_dir=cache_dir, revision=revision)
if resolved_file is not None:
if resolved_file is not None and resolved_file != _CACHED_NO_EXIST:
return resolved_file
if not _raise_exceptions_for_missing_entries or not _raise_exceptions_for_connection_errors:
return None
@@ -457,7 +457,7 @@ def cached_file(
except HTTPError as err:
# First we try to see if we have a cached version (not up to date):
resolved_file = try_to_load_from_cache(path_or_repo_id, full_filename, cache_dir=cache_dir, revision=revision)
if resolved_file is not None:
if resolved_file is not None and resolved_file != _CACHED_NO_EXIST:
return resolved_file
if not _raise_exceptions_for_connection_errors:
return None
@@ -1104,8 +1104,9 @@ else:
with open(cache_version_file) as f:
cache_version = int(f.read())
cache_is_not_empty = os.path.isdir(TRANSFORMERS_CACHE) and len(os.listdir(TRANSFORMERS_CACHE)) > 0
if cache_version < 1:
if cache_version < 1 and cache_is_not_empty:
if is_offline_mode():
logger.warn(
"You are offline and the cache for model files in Transformers v4.22.0 has been updated while your local "

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@@ -40,6 +40,7 @@ from transformers import (
AutoTokenizer,
BertTokenizer,
BertTokenizerFast,
GPT2TokenizerFast,
PreTrainedTokenizer,
PreTrainedTokenizerBase,
PreTrainedTokenizerFast,
@@ -3881,12 +3882,30 @@ class TokenizerUtilTester(unittest.TestCase):
# Download this model to make sure it's in the cache.
_ = BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert")
# Under the mock environment we get a 500 error when trying to reach the model.
# Under the mock environment we get a 500 error when trying to reach the tokenizer.
with mock.patch("requests.request", return_value=response_mock) as mock_head:
_ = BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert")
# This check we did call the fake head request
mock_head.assert_called()
@require_tokenizers
def test_cached_files_are_used_when_internet_is_down_missing_files(self):
# A mock response for an HTTP head request to emulate server down
response_mock = mock.Mock()
response_mock.status_code = 500
response_mock.headers = {}
response_mock.raise_for_status.side_effect = HTTPError
response_mock.json.return_value = {}
# Download this model to make sure it's in the cache.
_ = GPT2TokenizerFast.from_pretrained("gpt2")
# Under the mock environment we get a 500 error when trying to reach the tokenizer.
with mock.patch("requests.request", return_value=response_mock) as mock_head:
_ = GPT2TokenizerFast.from_pretrained("gpt2")
# This check we did call the fake head request
mock_head.assert_called()
def test_legacy_load_from_one_file(self):
# This test is for deprecated behavior and can be removed in v5
try:

View File

@@ -15,28 +15,14 @@
import contextlib
import importlib
import io
import json
import tempfile
import unittest
from pathlib import Path
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER
from transformers.utils import (
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
WEIGHTS_NAME,
ContextManagers,
find_labels,
get_file_from_repo,
has_file,
is_flax_available,
is_tf_available,
is_torch_available,
)
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available
MODEL_ID = DUMMY_UNKNOWN_IDENTIFIER
@@ -77,38 +63,6 @@ class TestImportMechanisms(unittest.TestCase):
assert importlib.util.find_spec("transformers") is not None
class GetFromCacheTests(unittest.TestCase):
def test_has_file(self):
self.assertTrue(has_file("hf-internal-testing/tiny-bert-pt-only", WEIGHTS_NAME))
self.assertFalse(has_file("hf-internal-testing/tiny-bert-pt-only", TF2_WEIGHTS_NAME))
self.assertFalse(has_file("hf-internal-testing/tiny-bert-pt-only", FLAX_WEIGHTS_NAME))
def test_get_file_from_repo_distant(self):
# `get_file_from_repo` returns None if the file does not exist
self.assertIsNone(get_file_from_repo("bert-base-cased", "ahah.txt"))
# The function raises if the repository does not exist.
with self.assertRaisesRegex(EnvironmentError, "is not a valid model identifier"):
get_file_from_repo("bert-base-case", "config.json")
# The function raises if the revision does not exist.
with self.assertRaisesRegex(EnvironmentError, "is not a valid git identifier"):
get_file_from_repo("bert-base-cased", "config.json", revision="ahaha")
resolved_file = get_file_from_repo("bert-base-cased", "config.json")
# The name is the cached name which is not very easy to test, so instead we load the content.
config = json.loads(open(resolved_file, "r").read())
self.assertEqual(config["hidden_size"], 768)
def test_get_file_from_repo_local(self):
with tempfile.TemporaryDirectory() as tmp_dir:
filename = Path(tmp_dir) / "a.txt"
filename.touch()
self.assertEqual(get_file_from_repo(tmp_dir, "a.txt"), str(filename))
self.assertIsNone(get_file_from_repo(tmp_dir, "b.txt"))
class GenericUtilTests(unittest.TestCase):
@unittest.mock.patch("sys.stdout", new_callable=io.StringIO)
def test_context_managers_no_context(self, mock_stdout):

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@@ -0,0 +1,125 @@
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
cached_file,
get_file_from_repo,
has_file,
)
RANDOM_BERT = "hf-internal-testing/tiny-random-bert"
CACHE_DIR = os.path.join(TRANSFORMERS_CACHE, "models--hf-internal-testing--tiny-random-bert")
FULL_COMMIT_HASH = "9b8c223d42b2188cb49d29af482996f9d0f3e5a6"
class GetFromCacheTests(unittest.TestCase):
def test_cached_file(self):
archive_file = cached_file(RANDOM_BERT, CONFIG_NAME)
# Should have downloaded the file in here
self.assertTrue(os.path.isdir(CACHE_DIR))
# Cache should contain at least those three subfolders:
for subfolder in ["blobs", "refs", "snapshots"]:
self.assertTrue(os.path.isdir(os.path.join(CACHE_DIR, subfolder)))
with open(os.path.join(CACHE_DIR, "refs", "main")) as f:
main_commit = f.read()
self.assertEqual(archive_file, os.path.join(CACHE_DIR, "snapshots", main_commit, CONFIG_NAME))
self.assertTrue(os.path.isfile(archive_file))
# File is cached at the same place the second time.
new_archive_file = cached_file(RANDOM_BERT, CONFIG_NAME)
self.assertEqual(archive_file, new_archive_file)
# Using a specific revision to test the full commit hash.
archive_file = cached_file(RANDOM_BERT, CONFIG_NAME, revision="9b8c223")
self.assertEqual(archive_file, os.path.join(CACHE_DIR, "snapshots", FULL_COMMIT_HASH, CONFIG_NAME))
def test_cached_file_errors(self):
with self.assertRaisesRegex(EnvironmentError, "is not a valid model identifier"):
_ = cached_file("tiny-random-bert", CONFIG_NAME)
with self.assertRaisesRegex(EnvironmentError, "is not a valid git identifier"):
_ = cached_file(RANDOM_BERT, CONFIG_NAME, revision="aaaa")
with self.assertRaisesRegex(EnvironmentError, "does not appear to have a file named"):
_ = cached_file(RANDOM_BERT, "conf")
def test_non_existence_is_cached(self):
with self.assertRaisesRegex(EnvironmentError, "does not appear to have a file named"):
_ = cached_file(RANDOM_BERT, "conf")
with open(os.path.join(CACHE_DIR, "refs", "main")) as f:
main_commit = f.read()
self.assertTrue(os.path.isfile(os.path.join(CACHE_DIR, ".no_exist", main_commit, "conf")))
path = cached_file(RANDOM_BERT, "conf", _raise_exceptions_for_missing_entries=False)
self.assertIsNone(path)
path = cached_file(RANDOM_BERT, "conf", local_files_only=True, _raise_exceptions_for_missing_entries=False)
self.assertIsNone(path)
response_mock = mock.Mock()
response_mock.status_code = 500
response_mock.headers = {}
response_mock.raise_for_status.side_effect = HTTPError
response_mock.json.return_value = {}
# Under the mock environment we get a 500 error when trying to reach the tokenizer.
with mock.patch("requests.request", return_value=response_mock) as mock_head:
path = cached_file(RANDOM_BERT, "conf", _raise_exceptions_for_connection_errors=False)
self.assertIsNone(path)
# This check we did call the fake head request
mock_head.assert_called()
def test_has_file(self):
self.assertTrue(has_file("hf-internal-testing/tiny-bert-pt-only", WEIGHTS_NAME))
self.assertFalse(has_file("hf-internal-testing/tiny-bert-pt-only", TF2_WEIGHTS_NAME))
self.assertFalse(has_file("hf-internal-testing/tiny-bert-pt-only", FLAX_WEIGHTS_NAME))
def test_get_file_from_repo_distant(self):
# `get_file_from_repo` returns None if the file does not exist
self.assertIsNone(get_file_from_repo("bert-base-cased", "ahah.txt"))
# The function raises if the repository does not exist.
with self.assertRaisesRegex(EnvironmentError, "is not a valid model identifier"):
get_file_from_repo("bert-base-case", CONFIG_NAME)
# The function raises if the revision does not exist.
with self.assertRaisesRegex(EnvironmentError, "is not a valid git identifier"):
get_file_from_repo("bert-base-cased", CONFIG_NAME, revision="ahaha")
resolved_file = get_file_from_repo("bert-base-cased", CONFIG_NAME)
# The name is the cached name which is not very easy to test, so instead we load the content.
config = json.loads(open(resolved_file, "r").read())
self.assertEqual(config["hidden_size"], 768)
def test_get_file_from_repo_local(self):
with tempfile.TemporaryDirectory() as tmp_dir:
filename = Path(tmp_dir) / "a.txt"
filename.touch()
self.assertEqual(get_file_from_repo(tmp_dir, "a.txt"), str(filename))
self.assertIsNone(get_file_from_repo(tmp_dir, "b.txt"))

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@@ -354,7 +354,7 @@ SPECIAL_MODULE_TO_TEST_MAP = {
"feature_extraction_utils.py": "test_feature_extraction_common.py",
"file_utils.py": ["utils/test_file_utils.py", "utils/test_model_output.py"],
"utils/generic.py": ["utils/test_file_utils.py", "utils/test_model_output.py", "utils/test_generic.py"],
"utils/hub.py": "utils/test_file_utils.py",
"utils/hub.py": "utils/test_hub_utils.py",
"modelcard.py": "utils/test_model_card.py",
"modeling_flax_utils.py": "test_modeling_flax_common.py",
"modeling_tf_utils.py": ["test_modeling_tf_common.py", "utils/test_modeling_tf_core.py"],