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未验证 提交 8ce90254 编写于 作者: X xsrobin 提交者： GitHub
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fix unalign of some examples (#18943) 

* test=develop test=document_preview

* Update API.spec
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paddle/fluid/API.spec
浏览文件 @ 8ce90254
......@@ -79,18 +79,18 @@ paddle.fluid.initializer.ConstantInitializer ('paddle.fluid.initializer.Constant
paddle.fluid.initializer.ConstantInitializer.__init__ (ArgSpec(args=['self', 'value', 'force_cpu'], varargs=None, keywords=None, defaults=(0.0, False)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.initializer.UniformInitializer ('paddle.fluid.initializer.UniformInitializer', ('document', 'a8f1177e4ce29766853e801d5b0a3635'))
paddle.fluid.initializer.UniformInitializer.__init__ (ArgSpec(args=['self', 'low', 'high', 'seed'], varargs=None, keywords=None, defaults=(-1.0, 1.0, 0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.initializer.NormalInitializer ('paddle.fluid.initializer.NormalInitializer', ('document', '2171207fb07293603e0fd2ff01234b3e'))
paddle.fluid.initializer.NormalInitializer ('paddle.fluid.initializer.NormalInitializer', ('document', '279a0d89bf01138fbf4c4ba14f22099b'))
paddle.fluid.initializer.NormalInitializer.__init__ (ArgSpec(args=['self', 'loc', 'scale', 'seed'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.initializer.TruncatedNormalInitializer ('paddle.fluid.initializer.TruncatedNormalInitializer', ('document', 'b8e90aad6ee5687cb5f2b6fd404370d1'))
paddle.fluid.initializer.TruncatedNormalInitializer.__init__ (ArgSpec(args=['self', 'loc', 'scale', 'seed'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.initializer.XavierInitializer ('paddle.fluid.initializer.XavierInitializer', ('document', '3d5676f1a5414aa0c815d793a795ccb3'))
paddle.fluid.initializer.XavierInitializer.__init__ (ArgSpec(args=['self', 'uniform', 'fan_in', 'fan_out', 'seed'], varargs=None, keywords=None, defaults=(True, None, None, 0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.initializer.BilinearInitializer ('paddle.fluid.initializer.BilinearInitializer', ('document', '5646a5cd44f0c9111344d13f46d31169'))
paddle.fluid.initializer.BilinearInitializer ('paddle.fluid.initializer.BilinearInitializer', ('document', '8a40b54fe33c19c3edcf6624ffae5d03'))
paddle.fluid.initializer.BilinearInitializer.__init__ (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'd389912dc079cbef432335a00017cec0'))
paddle.fluid.initializer.MSRAInitializer ('paddle.fluid.initializer.MSRAInitializer', ('document', 'ecfadb28c52d01496d107835a69ec3f9'))
paddle.fluid.initializer.MSRAInitializer ('paddle.fluid.initializer.MSRAInitializer', ('document', 'b99e0ee95e2fd02640cb4b08a7ae80cc'))
paddle.fluid.initializer.MSRAInitializer.__init__ (ArgSpec(args=['self', 'uniform', 'fan_in', 'seed'], varargs=None, keywords=None, defaults=(True, None, 0)), ('document', '53c757bed9345f2ad3361902531e7cf5'))
paddle.fluid.initializer.force_init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '53c01b661feb8e60d0efa2066976c1a8'))
paddle.fluid.initializer.init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '68bebc3963526880a07c98a5d6226794'))
paddle.fluid.initializer.force_init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '5f55553caf939d270c7fe8dc418084b2'))
paddle.fluid.initializer.init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'eaa04fd68661a3af59abd0e19b3b6eda'))
paddle.fluid.initializer.NumpyArrayInitializer ('paddle.fluid.initializer.NumpyArrayInitializer', ('document', '064f134a27c16372967d450f499762ab'))
paddle.fluid.initializer.NumpyArrayInitializer.__init__ (ArgSpec(args=['self', 'value'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.layers.fc (ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, False, None)), ('document', '1c74f52549814235077ecc34856a95eb'))
......@@ -148,7 +148,7 @@ paddle.fluid.layers.warpctc (ArgSpec(args=['input', 'label', 'blank', 'norm_by_t
paddle.fluid.layers.sequence_reshape (ArgSpec(args=['input', 'new_dim'], varargs=None, keywords=None, defaults=None), ('document', 'f568714a876425004aca4ea2d4a27701'))
paddle.fluid.layers.transpose (ArgSpec(args=['x', 'perm', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '8e72db173d4c082e27cb11f31d8c9bfa'))
paddle.fluid.layers.im2sequence (ArgSpec(args=['input', 'filter_size', 'stride', 'padding', 'input_image_size', 'out_stride', 'name'], varargs=None, keywords=None, defaults=(1, 1, 0, None, 1, None)), ('document', '33134416fc27dd65a767e5f15116ee16'))
paddle.fluid.layers.nce (ArgSpec(args=['input', 'label', 'num_total_classes', 'sample_weight', 'param_attr', 'bias_attr', 'num_neg_samples', 'name', 'sampler', 'custom_dist', 'seed', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 'uniform', None, 0, False)), ('document', '11a544a6e3fd0482509712dd54377fa1'))
paddle.fluid.layers.nce (ArgSpec(args=['input', 'label', 'num_total_classes', 'sample_weight', 'param_attr', 'bias_attr', 'num_neg_samples', 'name', 'sampler', 'custom_dist', 'seed', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 'uniform', None, 0, False)), ('document', '83d4ca6dfb957912807f535756e76992'))
paddle.fluid.layers.sampled_softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'num_samples', 'num_true', 'remove_accidental_hits', 'use_customized_samples', 'customized_samples', 'customized_probabilities', 'seed'], varargs=None, keywords=None, defaults=(1, True, False, None, None, 0)), ('document', 'd4435a63d34203339831ee6a86ef9242'))
paddle.fluid.layers.hsigmoid (ArgSpec(args=['input', 'label', 'num_classes', 'param_attr', 'bias_attr', 'name', 'path_table', 'path_code', 'is_custom', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, False, False)), ('document', 'b83e7dfa81059b39bb137922dc914f50'))
paddle.fluid.layers.beam_search (ArgSpec(args=['pre_ids', 'pre_scores', 'ids', 'scores', 'beam_size', 'end_id', 'level', 'is_accumulated', 'name', 'return_parent_idx'], varargs=None, keywords=None, defaults=(0, True, None, False)), ('document', '1270395ce97a4e1b556104abbb14f096'))
......@@ -409,7 +409,7 @@ paddle.fluid.layers.inverse_time_decay (ArgSpec(args=['learning_rate', 'decay_st
paddle.fluid.layers.polynomial_decay (ArgSpec(args=['learning_rate', 'decay_steps', 'end_learning_rate', 'power', 'cycle'], varargs=None, keywords=None, defaults=(0.0001, 1.0, False)), ('document', 'a343254c36c2e89512cd8cd8a1960ead'))
paddle.fluid.layers.piecewise_decay (ArgSpec(args=['boundaries', 'values'], varargs=None, keywords=None, defaults=None), ('document', 'd9f654117542c6b702963dda107a247f'))
paddle.fluid.layers.noam_decay (ArgSpec(args=['d_model', 'warmup_steps'], varargs=None, keywords=None, defaults=None), ('document', 'fd57228fb76195e66bbcc8d8e42c494d'))
paddle.fluid.layers.cosine_decay (ArgSpec(args=['learning_rate', 'step_each_epoch', 'epochs'], varargs=None, keywords=None, defaults=None), ('document', 'f0d65d8c89d0fe78051ca689daa15e35'))
paddle.fluid.layers.cosine_decay (ArgSpec(args=['learning_rate', 'step_each_epoch', 'epochs'], varargs=None, keywords=None, defaults=None), ('document', '1062e487dd3b50a6e58b5703b4f594c9'))
paddle.fluid.layers.linear_lr_warmup (ArgSpec(args=['learning_rate', 'warmup_steps', 'start_lr', 'end_lr'], varargs=None, keywords=None, defaults=None), ('document', 'dc7292c456847ba41cfd318e9f7f4363'))
paddle.fluid.layers.Uniform ('paddle.fluid.layers.distributions.Uniform', ('document', 'af70e7003f437e7a8a9e28cded35c433'))
paddle.fluid.layers.Uniform.__init__ (ArgSpec(args=['self', 'low', 'high'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
......
python/paddle/fluid/initializer.py
浏览文件 @ 8ce90254
......@@ -42,10 +42,10 @@ def force_init_on_cpu():
.. code-block:: python
import paddle.fluid as fluid
if fluid.initializer.force_init_on_cpu():
step = fluid.layers.create_global_var(
shape=[2,3], value=1.0, dtype='float32')
import paddle.fluid as fluid
if fluid.initializer.force_init_on_cpu():
step = fluid.layers.create_global_var(
shape=[2,3], value=1.0, dtype='float32')
"""
return _force_init_on_cpu_
......@@ -59,10 +59,10 @@ def init_on_cpu():
Examples:
.. code-block:: python
import paddle.fluid as fluid
with fluid.initializer.init_on_cpu():
step = fluid.layers.create_global_var(
shape=[2,3], value=1.0, dtype='float32')
import paddle.fluid as fluid
with fluid.initializer.init_on_cpu():
step = fluid.layers.create_global_var(
shape=[2,3], value=1.0, dtype='float32')
"""
global _force_init_on_cpu_
......@@ -295,10 +295,10 @@ class NormalInitializer(Initializer):
Examples:
.. code-block:: python
import paddle.fluid as fluid
x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
fc = fluid.layers.fc(input=x, size=10,
param_attr=fluid.initializer.Normal(loc=0.0, scale=2.0))
import paddle.fluid as fluid
x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
fc = fluid.layers.fc(input=x, size=10,
param_attr=fluid.initializer.Normal(loc=0.0, scale=2.0))
"""
......@@ -611,11 +611,11 @@ class MSRAInitializer(Initializer):
Examples:
.. code-block:: python
import paddle.fluid as fluid
x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
fc = fluid.layers.fc(input=x, size=10,
param_attr=fluid.initializer.MSRA(uniform=False))
import paddle.fluid as fluid
x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
fc = fluid.layers.fc(input=x, size=10,
param_attr=fluid.initializer.MSRA(uniform=False))
"""
......@@ -715,25 +715,25 @@ class BilinearInitializer(Initializer):
.. code-block:: python
import paddle.fluid as fluid
factor = 2
C = 2
w_attr = fluid.param_attr.ParamAttr(
learning_rate=0.,
regularizer=fluid.regularizer.L2Decay(0.),
import paddle.fluid as fluid
factor = 2
C = 2
w_attr = fluid.param_attr.ParamAttr(
learning_rate=0.,
regularizer=fluid.regularizer.L2Decay(0.),
initializer=fluid.initializer.Bilinear())
x = fluid.layers.data(name="data", shape=[3, 32, 32],
dtype="float32")
conv_up = fluid.layers.conv2d_transpose(
input=x,
num_filters=C,
output_size=None,
filter_size=2 * factor - factor % 2,
padding=int(math.ceil((factor - 1) / 2.)),
stride=factor,
groups=C,
param_attr=w_attr,
bias_attr=False)
x = fluid.layers.data(name="data", shape=[3, 32, 32],
dtype="float32")
conv_up = fluid.layers.conv2d_transpose(
input=x,
num_filters=C,
output_size=None,
filter_size=2 * factor - factor % 2,
padding=int(math.ceil((factor - 1) / 2.)),
stride=factor,
groups=C,
param_attr=w_attr,
bias_attr=False)
Where, `num_filters=C` and `groups=C` means this is channel-wise transposed
convolution. The filter shape will be (C, 1, K, K) where K is `filer_size`,
......
python/paddle/fluid/layers/learning_rate_scheduler.py
浏览文件 @ 8ce90254
......@@ -405,23 +405,23 @@ def cosine_decay(learning_rate, step_each_epoch, epochs):
.. math::
decayed\_lr = learning\_rate * 0.5 * (math.cos * (epoch * \\frac{math.pi}{epochs} ) + 1)
decayed\_lr = learning\_rate * 0.5 * (math.cos * (epoch * \\frac{math.pi}{epochs} ) + 1)
Args:
learning_rate(Variable|float): The initial learning rate.
step_each_epoch(int): the number of steps in an epoch.
epochs(int): the number of epochs.
Returns:
Variable: The decayed learning rate.
Variable: The decayed learning rate.
Examples:
.. code-block:: python
.. code-block:: python
import paddle.fluid as fluid
base_lr = 0.1
lr = fluid.layers.cosine_decay(
learning_rate = base_lr, step_each_epoch=10000, epochs=120)
import paddle.fluid as fluid
base_lr = 0.1
lr = fluid.layers.cosine_decay(
learning_rate = base_lr, step_each_epoch=10000, epochs=120)
"""
with default_main_program()._lr_schedule_guard():
......
python/paddle/fluid/layers/nn.py
浏览文件 @ 8ce90254
......@@ -5811,40 +5811,40 @@ def nce(input,
.. code-block:: python
import paddle.fluid as fluid
import numpy as np
window_size = 5
words = []
for i in xrange(window_size):
words.append(fluid.layers.data(
name='word_{0}'.format(i), shape=[1], dtype='int64'))
dict_size = 10000
label_word = int(window_size / 2) + 1
embs = []
for i in xrange(window_size):
if i == label_word:
continue
emb = fluid.layers.embedding(input=words[i], size=[dict_size, 32],
param_attr='embed', is_sparse=True)
embs.append(emb)
embs = fluid.layers.concat(input=embs, axis=1)
loss = fluid.layers.nce(input=embs, label=words[label_word],
num_total_classes=dict_size, param_attr='nce.w_0',
bias_attr='nce.b_0')
#or use custom distribution
dist = np.array([0.05,0.5,0.1,0.3,0.05])
loss = fluid.layers.nce(input=embs, label=words[label_word],
num_total_classes=5, param_attr='nce.w_1',
bias_attr='nce.b_1',
num_neg_samples=3,
sampler="custom_dist",
custom_dist=dist)
import paddle.fluid as fluid
import numpy as np
window_size = 5
words = []
for i in xrange(window_size):
words.append(fluid.layers.data(
name='word_{0}'.format(i), shape=[1], dtype='int64'))
dict_size = 10000
label_word = int(window_size / 2) + 1
embs = []
for i in xrange(window_size):
if i == label_word:
continue
emb = fluid.layers.embedding(input=words[i], size=[dict_size, 32],
param_attr='embed', is_sparse=True)
embs.append(emb)
embs = fluid.layers.concat(input=embs, axis=1)
loss = fluid.layers.nce(input=embs, label=words[label_word],
num_total_classes=dict_size, param_attr='nce.w_0',
bias_attr='nce.b_0')
#or use custom distribution
dist = np.array([0.05,0.5,0.1,0.3,0.05])
loss = fluid.layers.nce(input=embs, label=words[label_word],
num_total_classes=5, param_attr='nce.w_1',
bias_attr='nce.b_1',
num_neg_samples=3,
sampler="custom_dist",
custom_dist=dist)
"""
helper = LayerHelper('nce', **locals())
assert isinstance(input, Variable)
......
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