add tab format.

local_add_cudnn_lstm
ZhenWang 6 years ago
parent 5e0bc13008
commit 9aa65bb166

@ -6843,8 +6843,8 @@ def elu(x, alpha=1.0, name=None):
.. code-block:: python
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.elu(x, alpha=0.2)
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.elu(x, alpha=0.2)
"""
helper = LayerHelper('elu', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
@ -6873,8 +6873,8 @@ def relu6(x, threshold=6.0, name=None):
.. code-block:: python
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.relu6(x, threshold=6.0)
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.relu6(x, threshold=6.0)
"""
helper = LayerHelper('relu6', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
@ -6903,8 +6903,8 @@ def pow(x, factor=1.0, name=None):
.. code-block:: python
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.pow(x, factor=2.0)
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.pow(x, factor=2.0)
"""
helper = LayerHelper('pow', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
@ -6934,8 +6934,8 @@ def stanh(x, scale_a=2.0 / 3.0, scale_b=1.7159, name=None):
.. code-block:: python
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.stanh(x, scale_a=0.6667, scale_b=1.7159)
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.stanh(x, scale_a=0.6667, scale_b=1.7159)
"""
helper = LayerHelper('stanh', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
@ -6966,8 +6966,8 @@ def hard_sigmoid(x, slope=0.2, offset=0.5, name=None):
.. code-block:: python
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.hard_sigmoid(x, slope=0.3, offset=0.8)
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.hard_sigmoid(x, slope=0.3, offset=0.8)
"""
helper = LayerHelper('hard_sigmoid', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
@ -6997,8 +6997,8 @@ def swish(x, beta=1.0, name=None):
.. code-block:: python
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.swish(x, beta=2.0)
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32")
y = fluid.layers.swish(x, beta=2.0)
"""
helper = LayerHelper('swish', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
@ -7034,9 +7034,9 @@ def prelu(x, mode, param_attr=None, name=None):
.. code-block:: python
x = fluid.layers.data(name="x", shape=[10,10], dtype="float32")
mode = 'channel'
output = fluid.layers.prelu(x,mode)
x = fluid.layers.data(name="x", shape=[10,10], dtype="float32")
mode = 'channel'
output = fluid.layers.prelu(x,mode)
"""
helper = LayerHelper('prelu', **locals())
if mode not in ['all', 'channel', 'element']:

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