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Fix E741 flake8 warning (x14).

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This commit is contained in:
Aymeric Augustin
2019-12-21 18:25:59 +01:00
parent ea89bec185
commit b0f7db73cd
8 changed files with 60 additions and 60 deletions
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6
examples/contrib/run_swag.py
View File

@@ -76,7 +76,7 @@ class SwagExample(object):
return self.__repr__()
def __repr__(self):
l = [
attributes = [
"swag_id: {}".format(self.swag_id),
"context_sentence: {}".format(self.context_sentence),
"start_ending: {}".format(self.start_ending),
@@ -87,9 +87,9 @@ class SwagExample(object):
]
if self.label is not None:
l.append("label: {}".format(self.label))
attributes.append("label: {}".format(self.label))
return ", ".join(l)
return ", ".join(attributes)
class InputFeatures(object):

18
templates/adding_a_new_model/modeling_xxx.py
View File

@@ -89,25 +89,25 @@ def load_tf_weights_in_xxx(model, config, tf_checkpoint_path):
pointer = model
for m_name in name:
if re.fullmatch(r"[A-Za-z]+_\d+", m_name):
l = re.split(r"_(\d+)", m_name)
scope_names = re.split(r"_(\d+)", m_name)
else:
l = [m_name]
if l[0] == "kernel" or l[0] == "gamma":
scope_names = [m_name]
if scope_names[0] == "kernel" or scope_names[0] == "gamma":
pointer = getattr(pointer, "weight")
elif l[0] == "output_bias" or l[0] == "beta":
elif scope_names[0] == "output_bias" or scope_names[0] == "beta":
pointer = getattr(pointer, "bias")
elif l[0] == "output_weights":
elif scope_names[0] == "output_weights":
pointer = getattr(pointer, "weight")
elif l[0] == "squad":
elif scope_names[0] == "squad":
pointer = getattr(pointer, "classifier")
else:
try:
pointer = getattr(pointer, l[0])
pointer = getattr(pointer, scope_names[0])
except AttributeError:
logger.info("Skipping {}".format("/".join(name)))
continue
if len(l) >= 2:
num = int(l[1])
if len(scope_names) >= 2:
num = int(scope_names[1])
pointer = pointer[num]
if m_name[-11:] == "_embeddings":
pointer = getattr(pointer, "weight")

18
transformers/modeling_albert.py
View File

@@ -124,26 +124,26 @@ def load_tf_weights_in_albert(model, config, tf_checkpoint_path):
pointer = model
for m_name in name:
if re.fullmatch(r"[A-Za-z]+_\d+", m_name):
l = re.split(r"_(\d+)", m_name)
scope_names = re.split(r"_(\d+)", m_name)
else:
l = [m_name]
scope_names = [m_name]
if l[0] == "kernel" or l[0] == "gamma":
if scope_names[0] == "kernel" or scope_names[0] == "gamma":
pointer = getattr(pointer, "weight")
elif l[0] == "output_bias" or l[0] == "beta":
elif scope_names[0] == "output_bias" or scope_names[0] == "beta":
pointer = getattr(pointer, "bias")
elif l[0] == "output_weights":
elif scope_names[0] == "output_weights":
pointer = getattr(pointer, "weight")
elif l[0] == "squad":
elif scope_names[0] == "squad":
pointer = getattr(pointer, "classifier")
else:
try:
pointer = getattr(pointer, l[0])
pointer = getattr(pointer, scope_names[0])
except AttributeError:
logger.info("Skipping {}".format("/".join(name)))
continue
if len(l) >= 2:
num = int(l[1])
if len(scope_names) >= 2:
num = int(scope_names[1])
pointer = pointer[num]
if m_name[-11:] == "_embeddings":

18
transformers/modeling_bert.py
View File

@@ -93,25 +93,25 @@ def load_tf_weights_in_bert(model, config, tf_checkpoint_path):
pointer = model
for m_name in name:
if re.fullmatch(r"[A-Za-z]+_\d+", m_name):
l = re.split(r"_(\d+)", m_name)
scope_names = re.split(r"_(\d+)", m_name)
else:
l = [m_name]
if l[0] == "kernel" or l[0] == "gamma":
scope_names = [m_name]
if scope_names[0] == "kernel" or scope_names[0] == "gamma":
pointer = getattr(pointer, "weight")
elif l[0] == "output_bias" or l[0] == "beta":
elif scope_names[0] == "output_bias" or scope_names[0] == "beta":
pointer = getattr(pointer, "bias")
elif l[0] == "output_weights":
elif scope_names[0] == "output_weights":
pointer = getattr(pointer, "weight")
elif l[0] == "squad":
elif scope_names[0] == "squad":
pointer = getattr(pointer, "classifier")
else:
try:
pointer = getattr(pointer, l[0])
pointer = getattr(pointer, scope_names[0])
except AttributeError:
logger.info("Skipping {}".format("/".join(name)))
continue
if len(l) >= 2:
num = int(l[1])
if len(scope_names) >= 2:
num = int(scope_names[1])
pointer = pointer[num]
if m_name[-11:] == "_embeddings":
pointer = getattr(pointer, "weight")

18
transformers/modeling_gpt2.py
View File

@@ -77,20 +77,20 @@ def load_tf_weights_in_gpt2(model, config, gpt2_checkpoint_path):
pointer = model
for m_name in name:
if re.fullmatch(r"[A-Za-z]+\d+", m_name):
l = re.split(r"(\d+)", m_name)
scope_names = re.split(r"(\d+)", m_name)
else:
l = [m_name]
if l[0] == "w" or l[0] == "g":
scope_names = [m_name]
if scope_names[0] == "w" or scope_names[0] == "g":
pointer = getattr(pointer, "weight")
elif l[0] == "b":
elif scope_names[0] == "b":
pointer = getattr(pointer, "bias")
elif l[0] == "wpe" or l[0] == "wte":
pointer = getattr(pointer, l[0])
elif scope_names[0] == "wpe" or scope_names[0] == "wte":
pointer = getattr(pointer, scope_names[0])
pointer = getattr(pointer, "weight")
else:
pointer = getattr(pointer, l[0])
if len(l) >= 2:
num = int(l[1])
pointer = getattr(pointer, scope_names[0])
if len(scope_names) >= 2:
num = int(scope_names[1])
pointer = pointer[num]
try:
assert pointer.shape == array.shape

16
transformers/modeling_openai.py
View File

@@ -90,19 +90,19 @@ def load_tf_weights_in_openai_gpt(model, config, openai_checkpoint_folder_path):
pointer = model
for m_name in name:
if re.fullmatch(r"[A-Za-z]+\d+", m_name):
l = re.split(r"(\d+)", m_name)
scope_names = re.split(r"(\d+)", m_name)
else:
l = [m_name]
if l[0] == "g":
scope_names = [m_name]
if scope_names[0] == "g":
pointer = getattr(pointer, "weight")
elif l[0] == "b":
elif scope_names[0] == "b":
pointer = getattr(pointer, "bias")
elif l[0] == "w":
elif scope_names[0] == "w":
pointer = getattr(pointer, "weight")
else:
pointer = getattr(pointer, l[0])
if len(l) >= 2:
num = int(l[1])
pointer = getattr(pointer, scope_names[0])
if len(scope_names) >= 2:
num = int(scope_names[1])
pointer = pointer[num]
try:
assert pointer.shape == array.shape

22
transformers/modeling_t5.py
View File

@@ -95,29 +95,29 @@ def load_tf_weights_in_t5(model, config, tf_checkpoint_path):
array = tf_weights[txt_name]
for m_name in name:
if re.fullmatch(r"[A-Za-z]+_\d+", m_name):
l = re.split(r"_(\d+)", m_name)
scope_names = re.split(r"_(\d+)", m_name)
else:
l = [m_name]
if l[0] in ["kernel", "scale", "embedding"]:
scope_names = [m_name]
if scope_names[0] in ["kernel", "scale", "embedding"]:
pointer = getattr(pointer, "weight")
# elif l[0] == 'scale':
# elif scope_names[0] == 'scale':
# pointer = getattr(pointer, 'weight')
# elif l[0] == 'output_bias' or l[0] == 'beta':
# elif scope_names[0] == 'output_bias' or scope_names[0] == 'beta':
# pointer = getattr(pointer, 'bias')
# elif l[0] == 'squad':
# elif scope_names[0] == 'squad':
# pointer = getattr(pointer, 'classifier')
else:
try:
pointer = getattr(pointer, l[0])
pointer = getattr(pointer, scope_names[0])
except AttributeError:
logger.info("Skipping {}".format("/".join(name)))
continue
if len(l) >= 2:
num = int(l[1])
if len(scope_names) >= 2:
num = int(scope_names[1])
pointer = pointer[num]
if l[0] not in ["kernel", "scale", "embedding"]:
if scope_names[0] not in ["kernel", "scale", "embedding"]:
pointer = getattr(pointer, "weight")
if l[0] != "embedding":
if scope_names[0] != "embedding":
logger.info("Transposing numpy weight of shape {} for {}".format(array.shape, name))
array = np.transpose(array)
try:

4
transformers/tokenization_t5.py
View File

@@ -160,8 +160,8 @@ class T5Tokenizer(PreTrainedTokenizer):
def _convert_token_to_id(self, token):
""" Converts a token (str/unicode) in an id using the vocab. """
if token.startswith("<extra_id_"):
l = re.match(r"<extra_id_(\d+)>", token)
num = int(l.group(1))
match = re.match(r"<extra_id_(\d+)>", token)
num = int(match.group(1))
return self.vocab_size - num - 1
return self.sp_model.piece_to_id(token)