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9322d340
编写于
12月 26, 2018
作者:
S
shippingwang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Fix, test=develop
上级
5631fc08
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
17 addition
and
23 deletion
+17
-23
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-1
paddle/fluid/operators/shuffle_channel_op.cc
paddle/fluid/operators/shuffle_channel_op.cc
+14
-19
paddle/fluid/operators/shuffle_channel_op.h
paddle/fluid/operators/shuffle_channel_op.h
+0
-1
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+2
-2
未找到文件。
paddle/fluid/API.spec
浏览文件 @
9322d340
...
...
@@ -208,7 +208,7 @@ paddle.fluid.layers.bilinear_tensor_product ArgSpec(args=['x', 'y', 'size', 'act
paddle.fluid.layers.merge_selected_rows ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.get_tensor_from_selected_rows ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.lstm ArgSpec(args=['input', 'init_h', 'init_c', 'max_len', 'hidden_size', 'num_layers', 'dropout_prob', 'is_bidirec', 'is_test', 'name', 'default_initializer', 'seed'], varargs=None, keywords=None, defaults=(0.0, False, False, None, None, -1))
paddle.fluid.layers.shuffle_channel ArgSpec(args=['x', 'group', 'name'], varargs=None, keywords=None, defaults=(
1, None
))
paddle.fluid.layers.shuffle_channel ArgSpec(args=['x', 'group', 'name'], varargs=None, keywords=None, defaults=(
None,
))
paddle.fluid.layers.py_func ArgSpec(args=['func', 'x', 'out', 'backward_func', 'skip_vars_in_backward_input'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.psroi_pool ArgSpec(args=['input', 'rois', 'output_channels', 'spatial_scale', 'pooled_height', 'pooled_width', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.huber_loss ArgSpec(args=['input', 'label', 'delta'], varargs=None, keywords=None, defaults=None)
...
...
paddle/fluid/operators/shuffle_channel_op.cc
浏览文件 @
9322d340
...
...
@@ -29,15 +29,13 @@ class ShuffleChannelOp : public framework::OperatorWithKernel {
ctx
->
SetOutputDim
(
"Out"
,
input_dims
);
}
/*
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
return framework::OpKernelType(
framework::ToDataType(ctx.Input<framework::Tensor>("X")->type()),
ctx.device_context());
}
*/
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
ctx
.
Input
<
framework
::
Tensor
>
(
"X"
)
->
type
(),
ctx
.
device_context
());
}
};
class
ShuffleChannelOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -89,16 +87,13 @@ class ShuffleChannelGradOp : public framework::OperatorWithKernel {
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
input_dims
);
}
/*
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
return framework::OpKernelType(
framework::ToDataType(
framework::ToDataType(ctx.Input<framework::Tensor>("X")->type()),
ctx.device_context());
}
*/
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
ctx
.
Input
<
framework
::
Tensor
>
(
"X"
)
->
type
(),
ctx
.
device_context
());
}
};
}
// namespace operators
...
...
paddle/fluid/operators/shuffle_channel_op.h
浏览文件 @
9322d340
...
...
@@ -50,7 +50,6 @@ class ShuffleChannelOpKernel : public framework::OpKernel<T> {
}
}
}
return
;
}
};
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
9322d340
...
...
@@ -9335,13 +9335,13 @@ def get_tensor_from_selected_rows(x, name=None):
return
out
def
shuffle_channel
(
x
,
group
=
1
,
name
=
None
):
def
shuffle_channel
(
x
,
group
,
name
=
None
):
"""
**Shuffle Channel Operator**
This operator obtains the group convolutional layer with channels shuffled.
First, divide the input channels in each group into several subgroups,
then, feed each group in the next layer with different subgroups.
Shuffle channel
operation makes it possible to build more powerful structures
Channel shuffling
operation makes it possible to build more powerful structures
with multiple group convolutional layers.
Args:
...
...
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