Follow up for #31973 (#32025)

* fix

* [test_all] trigger full CI

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2024-07-25 16:12:23 +02:00
committed by GitHub
parent de2318894e
commit df6eee9201
9 changed files with 808 additions and 673 deletions

View File

@@ -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):
@staticmethod
def _try_delete_repo(repo_id, token):
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
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)
try:
# Reset repo
delete_repo(token=self._token, repo_id="test-model-tf")
except: # noqa E722
pass
# Push to hub via save_pretrained
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)
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)
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:
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()
# 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)
try:
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-model-tf-org")
except: # noqa E722
pass
# Push to hub via save_pretrained
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)
model.push_to_hub(tmp_repo, 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)
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-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()
# 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)