mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-05 13:50:13 +06:00
c89bdfbe72
* Put models in subfolders * Styling * Fix imports in tests * More fixes in test imports * Sneaky hidden imports * Fix imports in doc files * More sneaky imports * Finish fixing tests * Fix examples * Fix path for copies * More fixes for examples * Fix dummy files * More fixes for example * More model import fixes * Is this why you're unhappy GitHub? * Fix imports in conver command
106 lines
4.2 KiB
Python
106 lines
4.2 KiB
Python
import os
|
|
import re
|
|
import shutil
|
|
import sys
|
|
import tempfile
|
|
import unittest
|
|
|
|
|
|
git_repo_path = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
|
|
sys.path.append(os.path.join(git_repo_path, "utils"))
|
|
|
|
import check_copies # noqa: E402
|
|
|
|
|
|
# This is the reference code that will be used in the tests.
|
|
# If BertLMPredictionHead is changed in modeling_bert.py, this code needs to be manually updated.
|
|
REFERENCE_CODE = """ def __init__(self, config):
|
|
super().__init__()
|
|
self.transform = BertPredictionHeadTransform(config)
|
|
|
|
# The output weights are the same as the input embeddings, but there is
|
|
# an output-only bias for each token.
|
|
self.decoder = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
|
|
|
|
self.bias = nn.Parameter(torch.zeros(config.vocab_size))
|
|
|
|
# Need a link between the two variables so that the bias is correctly resized with `resize_token_embeddings`
|
|
self.decoder.bias = self.bias
|
|
|
|
def forward(self, hidden_states):
|
|
hidden_states = self.transform(hidden_states)
|
|
hidden_states = self.decoder(hidden_states)
|
|
return hidden_states
|
|
"""
|
|
|
|
|
|
class CopyCheckTester(unittest.TestCase):
|
|
def setUp(self):
|
|
self.transformer_dir = tempfile.mkdtemp()
|
|
os.makedirs(os.path.join(self.transformer_dir, "models/bert/"))
|
|
check_copies.TRANSFORMER_PATH = self.transformer_dir
|
|
shutil.copy(
|
|
os.path.join(git_repo_path, "src/transformers/models/bert/modeling_bert.py"),
|
|
os.path.join(self.transformer_dir, "models/bert/modeling_bert.py"),
|
|
)
|
|
|
|
def tearDown(self):
|
|
check_copies.TRANSFORMER_PATH = "src/transformers"
|
|
shutil.rmtree(self.transformer_dir)
|
|
|
|
def check_copy_consistency(self, comment, class_name, class_code, overwrite_result=None):
|
|
code = comment + f"\nclass {class_name}(nn.Module):\n" + class_code
|
|
if overwrite_result is not None:
|
|
expected = comment + f"\nclass {class_name}(nn.Module):\n" + overwrite_result
|
|
fname = os.path.join(self.transformer_dir, "new_code.py")
|
|
with open(fname, "w") as f:
|
|
f.write(code)
|
|
if overwrite_result is None:
|
|
self.assertTrue(len(check_copies.is_copy_consistent(fname)) == 0)
|
|
else:
|
|
check_copies.is_copy_consistent(f.name, overwrite=True)
|
|
with open(fname, "r") as f:
|
|
self.assertTrue(f.read(), expected)
|
|
|
|
def test_find_code_in_transformers(self):
|
|
code = check_copies.find_code_in_transformers("models.bert.modeling_bert.BertLMPredictionHead")
|
|
self.assertEqual(code, REFERENCE_CODE)
|
|
|
|
def test_is_copy_consistent(self):
|
|
# Base copy consistency
|
|
self.check_copy_consistency(
|
|
"# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead",
|
|
"BertLMPredictionHead",
|
|
REFERENCE_CODE + "\n",
|
|
)
|
|
|
|
# With no empty line at the end
|
|
self.check_copy_consistency(
|
|
"# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead",
|
|
"BertLMPredictionHead",
|
|
REFERENCE_CODE,
|
|
)
|
|
|
|
# Copy consistency with rename
|
|
self.check_copy_consistency(
|
|
"# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead with Bert->TestModel",
|
|
"TestModelLMPredictionHead",
|
|
re.sub("Bert", "TestModel", REFERENCE_CODE),
|
|
)
|
|
|
|
# Copy consistency with a really long name
|
|
long_class_name = "TestModelWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReasonIReallyDontUnderstand"
|
|
self.check_copy_consistency(
|
|
f"# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead with Bert->{long_class_name}",
|
|
f"{long_class_name}LMPredictionHead",
|
|
re.sub("Bert", long_class_name, REFERENCE_CODE),
|
|
)
|
|
|
|
# Copy consistency with overwrite
|
|
self.check_copy_consistency(
|
|
"# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead with Bert->TestModel",
|
|
"TestModelLMPredictionHead",
|
|
REFERENCE_CODE,
|
|
overwrite_result=re.sub("Bert", "TestModel", REFERENCE_CODE),
|
|
)
|