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b0eca104
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体验新版 GitCode,发现更多精彩内容 >>
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b0eca104
编写于
5月 15, 2018
作者:
W
Wu Yi
提交者:
GitHub
5月 15, 2018
浏览文件
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电子邮件补丁
差异文件
remove unused vars (#10618)
上级
6cbe597a
变更
8
显示空白变更内容
内联
并排
Showing
8 changed file
with
8 addition
and
8 deletion
+8
-8
python/paddle/fluid/tests/book/notest_understand_sentiment.py
...on/paddle/fluid/tests/book/notest_understand_sentiment.py
+1
-1
python/paddle/fluid/tests/book/test_fit_a_line.py
python/paddle/fluid/tests/book/test_fit_a_line.py
+1
-1
python/paddle/fluid/tests/book/test_image_classification.py
python/paddle/fluid/tests/book/test_image_classification.py
+1
-1
python/paddle/fluid/tests/book/test_label_semantic_roles.py
python/paddle/fluid/tests/book/test_label_semantic_roles.py
+1
-1
python/paddle/fluid/tests/book/test_machine_translation.py
python/paddle/fluid/tests/book/test_machine_translation.py
+1
-1
python/paddle/fluid/tests/book/test_recognize_digits.py
python/paddle/fluid/tests/book/test_recognize_digits.py
+1
-1
python/paddle/fluid/tests/book/test_recommender_system.py
python/paddle/fluid/tests/book/test_recommender_system.py
+1
-1
python/paddle/fluid/tests/book/test_word2vec.py
python/paddle/fluid/tests/book/test_word2vec.py
+1
-1
未找到文件。
python/paddle/fluid/tests/book/notest_understand_sentiment.py
浏览文件 @
b0eca104
...
@@ -170,7 +170,7 @@ def train(word_dict,
...
@@ -170,7 +170,7 @@ def train(word_dict,
assert
save_dirname
is
None
assert
save_dirname
is
None
adagrad
=
fluid
.
optimizer
.
Adagrad
(
learning_rate
=
0.002
)
adagrad
=
fluid
.
optimizer
.
Adagrad
(
learning_rate
=
0.002
)
optimize_ops
,
params_grads
=
adagrad
.
minimize
(
cost
)
adagrad
.
minimize
(
cost
)
train_data
=
paddle
.
batch
(
train_data
=
paddle
.
batch
(
paddle
.
reader
.
shuffle
(
paddle
.
reader
.
shuffle
(
...
...
python/paddle/fluid/tests/book/test_fit_a_line.py
浏览文件 @
b0eca104
...
@@ -33,7 +33,7 @@ def train(use_cuda, save_dirname, is_local):
...
@@ -33,7 +33,7 @@ def train(use_cuda, save_dirname, is_local):
avg_cost
=
fluid
.
layers
.
mean
(
cost
)
avg_cost
=
fluid
.
layers
.
mean
(
cost
)
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
optimize_ops
,
params_grads
=
sgd_optimizer
.
minimize
(
avg_cost
)
sgd_optimizer
.
minimize
(
avg_cost
)
BATCH_SIZE
=
20
BATCH_SIZE
=
20
...
...
python/paddle/fluid/tests/book/test_image_classification.py
浏览文件 @
b0eca104
...
@@ -125,7 +125,7 @@ def train(net_type, use_cuda, save_dirname, is_local):
...
@@ -125,7 +125,7 @@ def train(net_type, use_cuda, save_dirname, is_local):
test_program
=
fluid
.
default_main_program
().
clone
(
for_test
=
True
)
test_program
=
fluid
.
default_main_program
().
clone
(
for_test
=
True
)
optimizer
=
fluid
.
optimizer
.
Adam
(
learning_rate
=
0.001
)
optimizer
=
fluid
.
optimizer
.
Adam
(
learning_rate
=
0.001
)
optimize
_ops
,
params_grads
=
optimize
r
.
minimize
(
avg_cost
)
optimizer
.
minimize
(
avg_cost
)
BATCH_SIZE
=
128
BATCH_SIZE
=
128
PASS_NUM
=
1
PASS_NUM
=
1
...
...
python/paddle/fluid/tests/book/test_label_semantic_roles.py
浏览文件 @
b0eca104
...
@@ -175,7 +175,7 @@ def train(use_cuda, save_dirname=None, is_local=True):
...
@@ -175,7 +175,7 @@ def train(use_cuda, save_dirname=None, is_local=True):
decay_steps
=
100000
,
decay_steps
=
100000
,
decay_rate
=
0.5
,
decay_rate
=
0.5
,
staircase
=
True
))
staircase
=
True
))
optimize_ops
,
params_grads
=
sgd_optimizer
.
minimize
(
avg_cost
)
sgd_optimizer
.
minimize
(
avg_cost
)
# TODO(qiao)
# TODO(qiao)
# add dependency track and move this config before optimizer
# add dependency track and move this config before optimizer
...
...
python/paddle/fluid/tests/book/test_machine_translation.py
浏览文件 @
b0eca104
...
@@ -185,7 +185,7 @@ def train_main(use_cuda, is_sparse, is_local=True):
...
@@ -185,7 +185,7 @@ def train_main(use_cuda, is_sparse, is_local=True):
learning_rate
=
1e-4
,
learning_rate
=
1e-4
,
regularization
=
fluid
.
regularizer
.
L2DecayRegularizer
(
regularization
=
fluid
.
regularizer
.
L2DecayRegularizer
(
regularization_coeff
=
0.1
))
regularization_coeff
=
0.1
))
optimize
_ops
,
params_grads
=
optimize
r
.
minimize
(
avg_cost
)
optimizer
.
minimize
(
avg_cost
)
train_data
=
paddle
.
batch
(
train_data
=
paddle
.
batch
(
paddle
.
reader
.
shuffle
(
paddle
.
reader
.
shuffle
(
...
...
python/paddle/fluid/tests/book/test_recognize_digits.py
浏览文件 @
b0eca104
...
@@ -95,7 +95,7 @@ def train(nn_type,
...
@@ -95,7 +95,7 @@ def train(nn_type,
test_program
=
fluid
.
default_main_program
().
clone
(
for_test
=
True
)
test_program
=
fluid
.
default_main_program
().
clone
(
for_test
=
True
)
optimizer
=
fluid
.
optimizer
.
Adam
(
learning_rate
=
0.001
)
optimizer
=
fluid
.
optimizer
.
Adam
(
learning_rate
=
0.001
)
optimize
_ops
,
params_grads
=
optimize
r
.
minimize
(
avg_loss
)
optimizer
.
minimize
(
avg_loss
)
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
...
...
python/paddle/fluid/tests/book/test_recommender_system.py
浏览文件 @
b0eca104
...
@@ -160,7 +160,7 @@ def train(use_cuda, save_dirname, is_local=True):
...
@@ -160,7 +160,7 @@ def train(use_cuda, save_dirname, is_local=True):
test_program
=
fluid
.
default_main_program
().
clone
(
for_test
=
True
)
test_program
=
fluid
.
default_main_program
().
clone
(
for_test
=
True
)
sgd_optimizer
=
SGDOptimizer
(
learning_rate
=
0.2
)
sgd_optimizer
=
SGDOptimizer
(
learning_rate
=
0.2
)
optimize_ops
,
params_grads
=
sgd_optimizer
.
minimize
(
avg_cost
)
sgd_optimizer
.
minimize
(
avg_cost
)
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
...
...
python/paddle/fluid/tests/book/test_word2vec.py
浏览文件 @
b0eca104
...
@@ -101,7 +101,7 @@ def train(use_cuda, is_sparse, is_parallel, save_dirname, is_local=True):
...
@@ -101,7 +101,7 @@ def train(use_cuda, is_sparse, is_parallel, save_dirname, is_local=True):
avg_cost
=
fluid
.
layers
.
mean
(
pd
())
avg_cost
=
fluid
.
layers
.
mean
(
pd
())
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
optimize_ops
,
params_grads
=
sgd_optimizer
.
minimize
(
avg_cost
)
sgd_optimizer
.
minimize
(
avg_cost
)
train_reader
=
paddle
.
batch
(
train_reader
=
paddle
.
batch
(
paddle
.
dataset
.
imikolov
.
train
(
word_dict
,
N
),
BATCH_SIZE
)
paddle
.
dataset
.
imikolov
.
train
(
word_dict
,
N
),
BATCH_SIZE
)
...
...
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