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Fix E714 flake8 warning (x8).

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This commit is contained in:
Aymeric Augustin
2019-12-21 18:07:03 +01:00
parent 5eab3cf6bc
commit fd2f17a7a1
8 changed files with 8 additions and 8 deletions
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2
examples/summarization/modeling_bertabs.py
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@@ -519,7 +519,7 @@ class MultiHeadedAttention(nn.Module):
attn = self.softmax(scores)
if not predefined_graph_1 is None:
if predefined_graph_1 is not None:
attn_masked = attn[:, -1] * predefined_graph_1
attn_masked = attn_masked / (torch.sum(attn_masked, 2).unsqueeze(2) + 1e-9)

2
templates/adding_a_new_model/modeling_tf_xxx.py
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@@ -152,7 +152,7 @@ class TFXxxMainLayer(tf.keras.layers.Layer):
# attention_probs has shape bsz x n_heads x N x N
# input head_mask has shape [num_heads] or [num_hidden_layers x num_heads]
# and head_mask is converted to shape [num_hidden_layers x batch x num_heads x seq_length x seq_length]
if not head_mask is None:
if head_mask is not None:
raise NotImplementedError
else:
head_mask = [None] * self.num_hidden_layers

2
transformers/modeling_tf_albert.py
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@@ -686,7 +686,7 @@ class TFAlbertModel(TFAlbertPreTrainedModel):
# attention_probs has shape bsz x n_heads x N x N
# input head_mask has shape [num_heads] or [num_hidden_layers x num_heads]
# and head_mask is converted to shape [num_hidden_layers x batch x num_heads x seq_length x seq_length]
if not head_mask is None:
if head_mask is not None:
raise NotImplementedError
else:
head_mask = [None] * self.num_hidden_layers

2
transformers/modeling_tf_bert.py
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@@ -562,7 +562,7 @@ class TFBertMainLayer(tf.keras.layers.Layer):
# attention_probs has shape bsz x n_heads x N x N
# input head_mask has shape [num_heads] or [num_hidden_layers x num_heads]
# and head_mask is converted to shape [num_hidden_layers x batch x num_heads x seq_length x seq_length]
if not head_mask is None:
if head_mask is not None:
raise NotImplementedError
else:
head_mask = [None] * self.num_hidden_layers

2
transformers/modeling_tf_gpt2.py
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@@ -311,7 +311,7 @@ class TFGPT2MainLayer(tf.keras.layers.Layer):
# attention_probs has shape bsz x n_heads x N x N
# input head_mask has shape [num_heads] or [num_hidden_layers x num_heads]
# and head_mask is converted to shape [num_hidden_layers x batch x num_heads x seq_length x seq_length]
if not head_mask is None:
if head_mask is not None:
raise NotImplementedError
else:
head_mask = [None] * self.num_hidden_layers

2
transformers/modeling_tf_openai.py
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@@ -303,7 +303,7 @@ class TFOpenAIGPTMainLayer(tf.keras.layers.Layer):
# attention_probs has shape bsz x n_heads x N x N
# input head_mask has shape [num_heads] or [num_hidden_layers x num_heads]
# and head_mask is converted to shape [num_hidden_layers x batch x num_heads x seq_length x seq_length]
if not head_mask is None:
if head_mask is not None:
raise NotImplementedError
else:
head_mask = [None] * self.num_hidden_layers

2
transformers/modeling_tf_t5.py
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@@ -456,7 +456,7 @@ class TFT5MainLayer(tf.keras.layers.Layer):
# attention_probs has shape bsz x n_heads x N x N
# input head_mask has shape [num_heads] or [num_hidden_layers x num_heads]
# and head_mask is converted to shape [num_hidden_layers x batch x num_heads x seq_length x seq_length]
if not head_mask is None:
if head_mask is not None:
raise NotImplementedError
else:
head_mask = [None] * self.num_hidden_layers

2
transformers/modeling_tf_transfo_xl.py
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@@ -554,7 +554,7 @@ class TFTransfoXLMainLayer(tf.keras.layers.Layer):
# attention_probs has shape bsz x n_heads x N x N
# input head_mask has shape [num_heads] or [num_hidden_layers x num_heads] (a head_mask for each layer)
# and head_mask is converted to shape [num_hidden_layers x qlen x klen x bsz x n_head]
if not head_mask is None:
if head_mask is not None:
raise NotImplementedError
else:
head_mask = [None] * self.n_layer