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提交 6133728a 编写于 作者: K Kexin Zhao
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fix error

上级 69e0af56
隐藏空白更改
内联 并排
Showing with 16 addition and 16 deletion
python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py
浏览文件 @ 6133728a
...@@ -215,21 +215,21 @@ def infer(use_cuda, inference_program, save_path): ...@@ -215,21 +215,21 @@ def infer(use_cuda, inference_program, save_path):
lod = [[3, 4, 2]] lod = [[3, 4, 2]]
base_shape = [1] base_shape = [1]
# The range of random integers is [low, high] # The range of random integers is [low, high]
word = fluid.create_random_lodtensor( word = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1) lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
pred = fluid.create_random_lodtensor( pred = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=PRED_DICT_LEN - 1) lod, base_shape, place, low=0, high=PRED_DICT_LEN - 1)
ctx_n2 = fluid.create_random_lodtensor( ctx_n2 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1) lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
ctx_n1 = fluid.create_random_lodtensor( ctx_n1 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1) lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
ctx_0 = fluid.create_random_lodtensor( ctx_0 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1) lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
ctx_p1 = fluid.create_random_lodtensor( ctx_p1 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1) lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
ctx_p2 = fluid.create_random_lodtensor( ctx_p2 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1) lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
mark = fluid.create_random_lodtensor( mark = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=MARK_DICT_LEN - 1) lod, base_shape, place, low=0, high=MARK_DICT_LEN - 1)
results = inferencer.infer( results = inferencer.infer(
......
python/paddle/fluid/tests/book/test_label_semantic_roles.py
浏览文件 @ 6133728a
...@@ -261,21 +261,21 @@ def infer(use_cuda, save_dirname=None): ...@@ -261,21 +261,21 @@ def infer(use_cuda, save_dirname=None):
lod = [[3, 4, 2]] lod = [[3, 4, 2]]
base_shape = [1] base_shape = [1]
# The range of random integers is [low, high] # The range of random integers is [low, high]
word = fluid.create_random_lodtensor( word = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=word_dict_len - 1) lod, base_shape, place, low=0, high=word_dict_len - 1)
pred = fluid.create_random_lodtensor( pred = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=pred_dict_len - 1) lod, base_shape, place, low=0, high=pred_dict_len - 1)
ctx_n2 = fluid.create_random_lodtensor( ctx_n2 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=word_dict_len - 1) lod, base_shape, place, low=0, high=word_dict_len - 1)
ctx_n1 = fluid.create_random_lodtensor( ctx_n1 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=word_dict_len - 1) lod, base_shape, place, low=0, high=word_dict_len - 1)
ctx_0 = fluid.create_random_lodtensor( ctx_0 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=word_dict_len - 1) lod, base_shape, place, low=0, high=word_dict_len - 1)
ctx_p1 = fluid.create_random_lodtensor( ctx_p1 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=word_dict_len - 1) lod, base_shape, place, low=0, high=word_dict_len - 1)
ctx_p2 = fluid.create_random_lodtensor( ctx_p2 = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=word_dict_len - 1) lod, base_shape, place, low=0, high=word_dict_len - 1)
mark = fluid.create_random_lodtensor( mark = fluid.create_random_int_lodtensor(
lod, base_shape, place, low=0, high=mark_dict_len - 1) lod, base_shape, place, low=0, high=mark_dict_len - 1)
# Construct feed as a dictionary of {feed_target_name: feed_target_data} # Construct feed as a dictionary of {feed_target_name: feed_target_data}
......
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