提交 3c84d219 编写于 作者: Y Yibing Liu

Code format

上级 75fa71ca
...@@ -115,7 +115,7 @@ class BertModel(object): ...@@ -115,7 +115,7 @@ class BertModel(object):
self_attn_mask = fluid.layers.matmul( self_attn_mask = fluid.layers.matmul(
x=input_mask, y=input_mask, transpose_y=True) x=input_mask, y=input_mask, transpose_y=True)
self_attn_mask = fluid.layers.scale( self_attn_mask = fluid.layers.scale(
x=self_attn_mask, scale=1000.0, bias=-1.0, bias_after_scale=False) x=self_attn_mask, scale=10000.0, bias=-1.0, bias_after_scale=False)
n_head_self_attn_mask = fluid.layers.stack( n_head_self_attn_mask = fluid.layers.stack(
x=[self_attn_mask] * self._n_head, axis=1) x=[self_attn_mask] * self._n_head, axis=1)
n_head_self_attn_mask.stop_gradient = True n_head_self_attn_mask.stop_gradient = True
......
...@@ -156,17 +156,19 @@ def chunk_eval(np_labels, np_infers, np_lens, tag_num, dev_count=1): ...@@ -156,17 +156,19 @@ def chunk_eval(np_labels, np_infers, np_lens, tag_num, dev_count=1):
infer_index = 0 infer_index = 0
label_index = 0 label_index = 0
while label_index < len(label_chunks) and infer_index < len( while label_index < len(label_chunks) \
infer_chunks): and infer_index < len(infer_chunks):
if infer_chunks[infer_index]["st"] < label_chunks[label_index][ if infer_chunks[infer_index]["st"] \
"st"]: < label_chunks[label_index]["st"]:
infer_index += 1 infer_index += 1
elif infer_chunks[infer_index]["st"] > label_chunks[ elif infer_chunks[infer_index]["st"] \
label_index]["st"]: > label_chunks[label_index]["st"]:
label_index += 1 label_index += 1
else: else:
if infer_chunks[infer_index]["en"] == label_chunks[label_index]["en"] and \ if infer_chunks[infer_index]["en"] \
infer_chunks[infer_index]["type"] == label_chunks[label_index]["type"]: == label_chunks[label_index]["en"] \
and infer_chunks[infer_index]["type"] \
== label_chunks[label_index]["type"]:
num_correct += 1 num_correct += 1
infer_index += 1 infer_index += 1
......
...@@ -115,7 +115,7 @@ class ErnieModel(object): ...@@ -115,7 +115,7 @@ class ErnieModel(object):
x=input_mask, y=input_mask, transpose_y=True) x=input_mask, y=input_mask, transpose_y=True)
self_attn_mask = fluid.layers.scale( self_attn_mask = fluid.layers.scale(
x=self_attn_mask, scale=1000.0, bias=-1.0, bias_after_scale=False) x=self_attn_mask, scale=10000.0, bias=-1.0, bias_after_scale=False)
n_head_self_attn_mask = fluid.layers.stack( n_head_self_attn_mask = fluid.layers.stack(
x=[self_attn_mask] * self._n_head, axis=1) x=[self_attn_mask] * self._n_head, axis=1)
n_head_self_attn_mask.stop_gradient = True n_head_self_attn_mask.stop_gradient = True
......
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