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体验新版 GitCode,发现更多精彩内容 >>
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提交
77cf305f
编写于
4月 04, 2022
作者:
H
hong
提交者:
GitHub
4月 04, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Add batch norm yaml (#41386)
* update * fix bug
上级
19cb0d18
变更
13
隐藏空白更改
内联
并排
Showing
13 changed file
with
269 addition
and
51 deletion
+269
-51
paddle/fluid/operators/inplace_abn_op.cc
paddle/fluid/operators/inplace_abn_op.cc
+2
-2
paddle/fluid/operators/inplace_abn_op.cu
paddle/fluid/operators/inplace_abn_op.cu
+4
-4
paddle/phi/api/lib/api_custom_impl.cc
paddle/phi/api/lib/api_custom_impl.cc
+129
-0
paddle/phi/api/lib/api_custom_impl.h
paddle/phi/api/lib/api_custom_impl.h
+14
-0
paddle/phi/kernels/batch_norm_grad_kernel.h
paddle/phi/kernels/batch_norm_grad_kernel.h
+6
-6
paddle/phi/kernels/cpu/batch_norm_grad_kernel.cc
paddle/phi/kernels/cpu/batch_norm_grad_kernel.cc
+15
-11
paddle/phi/kernels/gpu/batch_norm_grad_kernel.cu
paddle/phi/kernels/gpu/batch_norm_grad_kernel.cu
+9
-9
paddle/phi/ops/compat/batch_norm_sig.cc
paddle/phi/ops/compat/batch_norm_sig.cc
+11
-9
python/paddle/fluid/dygraph/nn.py
python/paddle/fluid/dygraph/nn.py
+16
-9
python/paddle/fluid/tests/unittests/test_batch_norm_op_v2.py
python/paddle/fluid/tests/unittests/test_batch_norm_op_v2.py
+34
-0
python/paddle/nn/functional/norm.py
python/paddle/nn/functional/norm.py
+10
-1
python/paddle/utils/code_gen/api.yaml
python/paddle/utils/code_gen/api.yaml
+7
-0
python/paddle/utils/code_gen/backward.yaml
python/paddle/utils/code_gen/backward.yaml
+12
-0
未找到文件。
paddle/fluid/operators/inplace_abn_op.cc
浏览文件 @
77cf305f
...
...
@@ -312,8 +312,8 @@ class InplaceABNGradKernel : public framework::OpKernel<T> {
phi
::
BatchNormGradRawKernel
<
T
>
(
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
dev_ctx
),
*
d_y
,
*
y
,
*
scale
,
*
bias
,
*
saved_mean
,
*
saved_variance
,
space_opt
,
mean_opt
,
variance_opt
,
momentum
,
epsilon
,
data_layout
,
is_test
,
*
y
,
*
scale
,
*
bias
,
mean_opt
,
variance_opt
,
*
saved_mean
,
*
saved_variance
,
space_opt
,
*
d_y
,
momentum
,
epsilon
,
data_layout
,
is_test
,
use_global_stats
,
trainable_statistics
,
fuse_with_relu
,
true
,
d_x
,
scale_grad
,
bias_grad
);
}
...
...
paddle/fluid/operators/inplace_abn_op.cu
浏览文件 @
77cf305f
...
...
@@ -140,10 +140,10 @@ class InplaceABNGradKernel
phi
::
BatchNormGradRawKernel
<
T
>
(
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
dev_ctx
),
*
d_y
,
*
y
,
*
scale
,
*
bias
,
*
saved_mean
,
*
saved_variance
,
space_opt
,
mean_opt
,
variance_opt
,
momentum
,
epsilon
,
data_layout
,
is_tes
t
,
use_global_stats
,
trainable_statistics
,
fuse_with_relu
,
true
,
d_x
,
scale_grad
,
bias_grad
);
*
y
,
*
scale
,
*
bias
,
mean_opt
,
variance_opt
,
*
saved_mean
,
*
saved_variance
,
space_opt
,
*
d_y
,
momentum
,
epsilon
,
data_layou
t
,
is_test
,
use_global_stats
,
trainable_statistics
,
fuse_with_relu
,
true
,
d_x
,
scale_grad
,
bias_grad
);
}
}
};
...
...
paddle/phi/api/lib/api_custom_impl.cc
浏览文件 @
77cf305f
...
...
@@ -167,6 +167,135 @@ std::vector<Tensor> split_impl(const Tensor& x,
return
out
;
}
std
::
tuple
<
Tensor
,
Tensor
,
Tensor
,
Tensor
,
Tensor
,
Tensor
>
batch_norm_impl
(
const
Tensor
&
x
,
const
Tensor
&
scale
,
const
Tensor
&
bias
,
const
Tensor
&
mean
,
const
Tensor
&
variance
,
float
momentum
,
float
epsilon
,
const
std
::
string
&
data_layout
,
bool
is_test
,
bool
use_global_stats
,
bool
trainable_statistics
,
bool
fuse_with_relu
)
{
Backend
kernel_backend
=
Backend
::
UNDEFINED
;
DataLayout
kernel_layout
=
DataLayout
::
UNDEFINED
;
DataType
kernel_data_type
=
DataType
::
UNDEFINED
;
kernel_data_type
=
ParseDataType
(
x
);
if
(
kernel_backend
==
Backend
::
UNDEFINED
||
kernel_layout
==
DataLayout
::
UNDEFINED
||
kernel_data_type
==
DataType
::
UNDEFINED
)
{
auto
kernel_key_set
=
ParseKernelKeyByInputArgs
(
x
);
auto
kernel_key
=
kernel_key_set
.
GetHighestPriorityKernelKey
();
if
(
kernel_backend
==
Backend
::
UNDEFINED
)
{
kernel_backend
=
kernel_key
.
backend
();
}
if
(
kernel_layout
==
DataLayout
::
UNDEFINED
)
{
kernel_layout
=
kernel_key
.
layout
();
}
if
(
kernel_data_type
==
DataType
::
UNDEFINED
)
{
kernel_data_type
=
kernel_key
.
dtype
();
}
}
const
auto
&
kernel
=
phi
::
KernelFactory
::
Instance
().
SelectKernelOrThrowError
(
"batch_norm"
,
{
kernel_backend
,
kernel_layout
,
kernel_data_type
});
VLOG
(
6
)
<<
"batch_norm API kernel key: ["
<<
kernel_backend
<<
", "
<<
kernel_layout
<<
", "
<<
kernel_data_type
<<
"]"
;
VLOG
(
6
)
<<
"batch_norm API kernel: "
<<
kernel
;
auto
*
dev_ctx
=
GetDeviceContextByBackend
(
kernel_backend
);
auto
input_x
=
PrepareData
(
x
,
kernel
.
InputAt
(
0
),
{});
auto
input_scale
=
PrepareData
(
scale
,
kernel
.
InputAt
(
1
),
{});
auto
input_bias
=
PrepareData
(
bias
,
kernel
.
InputAt
(
2
),
{});
auto
input_mean
=
PrepareData
(
mean
,
kernel
.
InputAt
(
3
),
{});
auto
input_variance
=
PrepareData
(
variance
,
kernel
.
InputAt
(
4
),
{});
std
::
tuple
<
Tensor
,
Tensor
,
Tensor
,
Tensor
,
Tensor
,
Tensor
>
api_output
;
auto
kernel_out_0
=
SetKernelOutput
(
kernel_backend
,
&
std
::
get
<
0
>
(
api_output
));
std
::
get
<
1
>
(
api_output
).
set_impl
(
mean
.
impl
());
std
::
get
<
2
>
(
api_output
).
set_impl
(
variance
.
impl
());
auto
kernel_out_1
=
SetKernelOutput
(
kernel_backend
,
&
std
::
get
<
1
>
(
api_output
));
auto
kernel_out_2
=
SetKernelOutput
(
kernel_backend
,
&
std
::
get
<
2
>
(
api_output
));
auto
kernel_out_3
=
SetKernelOutput
(
kernel_backend
,
&
std
::
get
<
3
>
(
api_output
));
auto
kernel_out_4
=
SetKernelOutput
(
kernel_backend
,
&
std
::
get
<
4
>
(
api_output
));
auto
kernel_out_5
=
SetKernelOutput
(
kernel_backend
,
&
std
::
get
<
5
>
(
api_output
));
phi
::
MetaTensor
meta_out_0
(
kernel_out_0
);
phi
::
MetaTensor
meta_out_1
(
kernel_out_1
);
phi
::
MetaTensor
meta_out_2
(
kernel_out_2
);
phi
::
MetaTensor
meta_out_3
(
kernel_out_3
);
phi
::
MetaTensor
meta_out_4
(
kernel_out_4
);
phi
::
MetaTensor
meta_out_5
(
kernel_out_5
);
phi
::
BatchNormInferMeta
(
MakeMetaTensor
(
*
input_x
),
MakeMetaTensor
(
*
input_scale
),
MakeMetaTensor
(
*
input_bias
),
MakeMetaTensor
(
*
input_mean
),
MakeMetaTensor
(
*
input_variance
),
momentum
,
epsilon
,
data_layout
,
is_test
,
use_global_stats
,
trainable_statistics
,
fuse_with_relu
,
&
meta_out_0
,
&
meta_out_1
,
&
meta_out_2
,
&
meta_out_3
,
&
meta_out_4
,
&
meta_out_5
);
using
kernel_signature
=
void
(
*
)(
const
platform
::
DeviceContext
&
,
const
phi
::
DenseTensor
&
,
const
phi
::
DenseTensor
&
,
const
phi
::
DenseTensor
&
,
const
phi
::
DenseTensor
&
,
const
phi
::
DenseTensor
&
,
float
,
float
,
const
std
::
string
&
,
bool
,
bool
,
bool
,
bool
,
phi
::
DenseTensor
*
,
phi
::
DenseTensor
*
,
phi
::
DenseTensor
*
,
phi
::
DenseTensor
*
,
phi
::
DenseTensor
*
,
phi
::
DenseTensor
*
);
auto
*
kernel_fn
=
kernel
.
GetVariadicKernelFn
<
kernel_signature
>
();
{
(
*
kernel_fn
)(
*
dev_ctx
,
*
input_x
,
*
input_scale
,
*
input_bias
,
*
input_mean
,
*
input_variance
,
momentum
,
epsilon
,
data_layout
,
is_test
,
use_global_stats
,
trainable_statistics
,
fuse_with_relu
,
kernel_out_0
,
kernel_out_1
,
kernel_out_2
,
kernel_out_3
,
kernel_out_4
,
kernel_out_5
);
}
return
api_output
;
}
std
::
vector
<
Tensor
>
concat_grad_impl
(
const
std
::
vector
<
Tensor
>&
x
,
const
Tensor
&
out_grad
,
const
Scalar
&
axis
)
{
...
...
paddle/phi/api/lib/api_custom_impl.h
浏览文件 @
77cf305f
...
...
@@ -31,6 +31,20 @@ std::vector<Tensor> split_impl(const Tensor& x,
const
IntArray
&
num_or_sections
,
const
Scalar
&
axis
);
std
::
tuple
<
Tensor
,
Tensor
,
Tensor
,
Tensor
,
Tensor
,
Tensor
>
batch_norm_impl
(
const
Tensor
&
x
,
const
Tensor
&
scale
,
const
Tensor
&
bias
,
const
Tensor
&
mean
,
const
Tensor
&
variance
,
float
momentum
,
float
epsilon
,
const
std
::
string
&
data_layout
,
bool
is_test
,
bool
use_global_stats
,
bool
trainable_statistics
,
bool
fuse_with_relu
);
std
::
vector
<
Tensor
>
concat_grad_impl
(
const
std
::
vector
<
Tensor
>&
x
,
const
Tensor
&
out_grad
,
const
Scalar
&
axis
);
...
...
paddle/phi/kernels/batch_norm_grad_kernel.h
浏览文件 @
77cf305f
...
...
@@ -21,15 +21,15 @@ namespace phi {
template
<
typename
T
,
typename
Context
>
void
BatchNormGradRawKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
y_grad
,
const
DenseTensor
&
x
,
const
DenseTensor
&
scale
,
const
DenseTensor
&
bias
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
saved_mean
,
const
DenseTensor
&
saved_variance
,
paddle
::
optional
<
const
DenseTensor
&>
reserve_space
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
y_grad
,
float
momentum
,
float
epsilon
,
const
std
::
string
&
data_layout
,
...
...
@@ -44,15 +44,15 @@ void BatchNormGradRawKernel(const Context& dev_ctx,
template
<
typename
T
,
typename
Context
>
void
BatchNormGradKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
y_grad
,
const
DenseTensor
&
x
,
const
DenseTensor
&
scale
,
const
DenseTensor
&
bias
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
saved_mean
,
const
DenseTensor
&
saved_variance
,
paddle
::
optional
<
const
DenseTensor
&>
reserve_space
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
y_grad
,
float
momentum
,
float
epsilon
,
const
std
::
string
&
data_layout
,
...
...
paddle/phi/kernels/cpu/batch_norm_grad_kernel.cc
浏览文件 @
77cf305f
...
...
@@ -37,15 +37,16 @@ using ConstEigenVectorArrayMap =
template
<
typename
T
,
typename
Context
>
void
BatchNormGradRawKernel
(
const
Context
&
ctx
,
const
DenseTensor
&
y_grad
,
const
DenseTensor
&
x
,
const
DenseTensor
&
scale
,
const
DenseTensor
&
bias
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
saved_mean
,
const
DenseTensor
&
saved_variance
,
paddle
::
optional
<
const
DenseTensor
&>
reserve_space
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
y_grad
,
float
momentum
,
float
epsilon
,
const
std
::
string
&
data_layout_str
,
...
...
@@ -122,8 +123,8 @@ void BatchNormGradRawKernel(const Context& ctx,
ctx
.
template
Alloc
<
T
>(
d_x
);
}
const
T
*
mean_data
=
saved_mean
.
data
<
T
>
()
;
const
T
*
inv_var_data
=
saved_variance
.
data
<
T
>
()
;
const
T
*
mean_data
=
nullptr
;
const
T
*
inv_var_data
=
nullptr
;
DenseTensor
inv_var_tensor
;
if
(
use_global_stats
)
{
const
auto
*
running_mean
=
mean
.
get_ptr
();
...
...
@@ -136,6 +137,9 @@ void BatchNormGradRawKernel(const Context& ctx,
inv_var_tmp
=
(
var_arr
+
epsilon
).
sqrt
().
inverse
();
inv_var_data
=
running_inv_var_data
;
}
else
{
mean_data
=
saved_mean
.
data
<
T
>
();
inv_var_data
=
saved_variance
.
data
<
T
>
();
}
ConstEigenVectorArrayMap
<
T
>
scale_arr
(
scale
.
data
<
T
>
(),
C
);
...
...
@@ -293,15 +297,15 @@ void BatchNormGradRawKernel(const Context& ctx,
template
<
typename
T
,
typename
Context
>
void
BatchNormGradKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
y_grad
,
const
DenseTensor
&
x
,
const
DenseTensor
&
scale
,
const
DenseTensor
&
bias
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
saved_mean
,
const
DenseTensor
&
saved_variance
,
paddle
::
optional
<
const
DenseTensor
&>
reserve_space
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
y_grad
,
float
momentum
,
float
epsilon
,
const
std
::
string
&
data_layout
,
...
...
@@ -313,15 +317,15 @@ void BatchNormGradKernel(const Context& dev_ctx,
DenseTensor
*
scale_grad
,
DenseTensor
*
bias_grad
)
{
BatchNormGradRawKernel
<
T
,
Context
>
(
dev_ctx
,
y_grad
,
x
,
scale
,
bias
,
mean
,
variance
,
saved_mean
,
saved_variance
,
reserve_space
,
mean
,
variance
,
y_grad
,
momentum
,
epsilon
,
data_layout
,
...
...
paddle/phi/kernels/gpu/batch_norm_grad_kernel.cu
浏览文件 @
77cf305f
...
...
@@ -306,15 +306,15 @@ static __global__ LAUNCH_BOUNDS(BlockDim) void BNBackwardData(
template
<
typename
T
,
typename
Context
>
void
BatchNormGradRawKernel
(
const
Context
&
ctx
,
const
DenseTensor
&
y_grad
,
const
DenseTensor
&
x
,
const
DenseTensor
&
scale
,
const
DenseTensor
&
bias
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
saved_mean
,
const
DenseTensor
&
saved_variance
,
paddle
::
optional
<
const
DenseTensor
&>
reserve_space
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
y_grad
,
float
momentum
,
float
epsilon_f
,
const
std
::
string
&
data_layout_str
,
...
...
@@ -863,15 +863,15 @@ void BatchNormGradRawKernel(const Context &ctx,
template
<
typename
T
,
typename
Context
>
void
BatchNormGradKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
y_grad
,
const
DenseTensor
&
x
,
const
DenseTensor
&
scale
,
const
DenseTensor
&
bias
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
saved_mean
,
const
DenseTensor
&
saved_variance
,
paddle
::
optional
<
const
DenseTensor
&>
reserve_space
,
paddle
::
optional
<
const
DenseTensor
&>
mean
,
paddle
::
optional
<
const
DenseTensor
&>
variance
,
const
DenseTensor
&
y_grad
,
float
momentum
,
float
epsilon
,
const
std
::
string
&
data_layout
,
...
...
@@ -883,15 +883,15 @@ void BatchNormGradKernel(const Context &dev_ctx,
DenseTensor
*
scale_grad
,
DenseTensor
*
bias_grad
)
{
BatchNormGradRawKernel
<
T
,
Context
>
(
dev_ctx
,
y_grad
,
x
,
scale
,
bias
,
mean
,
variance
,
saved_mean
,
saved_variance
,
reserve_space
,
mean
,
variance
,
y_grad
,
momentum
,
epsilon
,
data_layout
,
...
...
paddle/phi/ops/compat/batch_norm_sig.cc
浏览文件 @
77cf305f
...
...
@@ -59,15 +59,17 @@ KernelSignature BatchNormGradOpArgumentMapping(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"batch_norm_grad"
,
{
GradVarName
(
"Y"
),
"X"
,
"Scale"
,
"Bias"
,
"SavedMean"
,
"SavedVariance"
,
"ReserveSpace"
,
"Mean"
,
"Variance"
},
{
"X"
,
"Scale"
,
"Bias"
,
"Mean"
,
"Variance"
,
"SavedMean"
,
"SavedVariance"
,
"ReserveSpace"
,
GradVarName
(
"Y"
),
},
{
"momentum"
,
"epsilon"
,
"data_layout"
,
...
...
python/paddle/fluid/dygraph/nn.py
浏览文件 @
77cf305f
...
...
@@ -1339,15 +1339,22 @@ class BatchNorm(layers.Layer):
variance_out
=
self
.
_variance
if
_non_static_mode
():
attrs
=
(
"momentum"
,
self
.
_momentum
,
"epsilon"
,
self
.
_epsilon
,
"is_test"
,
not
self
.
training
,
"data_layout"
,
self
.
_data_layout
,
"use_mkldnn"
,
self
.
_use_mkldnn
,
"fuse_with_relu"
,
self
.
_fuse_with_relu
,
"use_global_stats"
,
self
.
_use_global_stats
,
'trainable_statistics'
,
self
.
_trainable_statistics
)
batch_norm_out
,
_
,
_
,
_
,
_
,
_
=
_C_ops
.
batch_norm
(
input
,
self
.
weight
,
self
.
bias
,
self
.
_mean
,
self
.
_variance
,
mean_out
,
variance_out
,
*
attrs
)
if
in_dygraph_mode
():
batch_norm_out
,
t1
,
t2
,
t3
,
t4
,
_
=
_C_ops
.
final_state_batch_norm
(
input
,
self
.
weight
,
self
.
bias
,
self
.
_mean
,
self
.
_variance
,
self
.
_momentum
,
self
.
_epsilon
,
self
.
_data_layout
,
not
self
.
training
,
self
.
_use_global_stats
,
self
.
_trainable_statistics
,
False
)
else
:
attrs
=
(
"momentum"
,
self
.
_momentum
,
"epsilon"
,
self
.
_epsilon
,
"is_test"
,
not
self
.
training
,
"data_layout"
,
self
.
_data_layout
,
"use_mkldnn"
,
self
.
_use_mkldnn
,
"fuse_with_relu"
,
self
.
_fuse_with_relu
,
"use_global_stats"
,
self
.
_use_global_stats
,
'trainable_statistics'
,
self
.
_trainable_statistics
)
batch_norm_out
,
_
,
_
,
_
,
_
,
_
=
_C_ops
.
batch_norm
(
input
,
self
.
weight
,
self
.
bias
,
self
.
_mean
,
self
.
_variance
,
mean_out
,
variance_out
,
*
attrs
)
return
dygraph_utils
.
_append_activation_in_dygraph
(
batch_norm_out
,
act
=
self
.
_act
,
use_mkldnn
=
self
.
_use_mkldnn
)
...
...
python/paddle/fluid/tests/unittests/test_batch_norm_op_v2.py
浏览文件 @
77cf305f
...
...
@@ -81,6 +81,40 @@ class TestBatchNorm(unittest.TestCase):
self
.
assertRaises
(
ValueError
,
error2d_dataformat
)
self
.
assertRaises
(
ValueError
,
error3d_dataformat
)
def
test_eager_api
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
fluid
.
CUDAPlace
(
0
))
for
p
in
places
:
shape
=
[
4
,
10
,
4
,
4
]
def
compute_v1
(
x
):
with
fluid
.
dygraph
.
guard
(
p
):
bn
=
fluid
.
dygraph
.
BatchNorm
(
shape
[
1
])
#bn = paddle.nn.BatchNorm2D(shape[1])
x1
=
paddle
.
to_tensor
(
x
)
x1
.
stop_gradient
=
False
y
=
bn
(
x1
)
y
.
backward
()
return
y
.
numpy
(),
x1
.
gradient
()
def
compute_v2
(
x
):
with
fluid
.
dygraph
.
guard
(
p
):
with
_test_eager_guard
():
print
(
"v2"
)
bn
=
paddle
.
nn
.
BatchNorm2D
(
shape
[
1
])
x1
=
paddle
.
to_tensor
(
x
)
x1
.
stop_gradient
=
False
y
=
bn
(
x1
)
y
.
backward
()
return
y
.
numpy
(),
x1
.
gradient
()
x
=
np
.
random
.
randn
(
*
shape
).
astype
(
"float32"
)
y1
,
g1
=
compute_v1
(
x
)
y2
,
g2
=
compute_v2
(
x
)
self
.
assertTrue
(
np
.
allclose
(
g1
,
g2
))
self
.
assertTrue
(
np
.
allclose
(
y1
,
y2
))
def
test_dygraph
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
...
...
python/paddle/nn/functional/norm.py
浏览文件 @
77cf305f
...
...
@@ -186,15 +186,24 @@ def batch_norm(x,
else
:
trainable_statistics
=
not
use_global_stats
if
in_dynamic_mode
():
if
in_dygraph_mode
():
batch_norm_out
,
_
,
_
,
_
,
_
,
_
=
_C_ops
.
final_state_batch_norm
(
x
,
weight
,
bias
,
running_mean
,
running_var
,
momentum
,
epsilon
,
data_format
,
not
training
,
use_global_stats
,
trainable_statistics
,
False
)
return
batch_norm_out
if
_in_legacy_dygraph
():
# for dygraph need tuple
attrs
=
(
"momentum"
,
momentum
,
"epsilon"
,
epsilon
,
"is_test"
,
not
training
,
"data_layout"
,
data_format
,
"use_mkldnn"
,
False
,
"fuse_with_relu"
,
False
,
"use_global_stats"
,
use_global_stats
,
"trainable_statistics"
,
trainable_statistics
)
batch_norm_out
,
_
,
_
,
_
,
_
,
_
=
_C_ops
.
batch_norm
(
x
,
weight
,
bias
,
running_mean
,
running_var
,
mean_out
,
variance_out
,
*
attrs
)
return
dygraph_utils
.
_append_activation_in_dygraph
(
batch_norm_out
,
act
=
None
)
...
...
python/paddle/utils/code_gen/api.yaml
浏览文件 @
77cf305f
...
...
@@ -207,6 +207,13 @@
kernel
:
func
:
auc
# batch_norm
-
api
:
batch_norm
args
:
(Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
output
:
Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
invoke
:
batch_norm_impl(x, scale, bias, mean, variance, momentum, epsilon, data_layout, is_test, use_global_stats, trainable_statistics, fuse_with_relu)
backward
:
batch_norm_grad
-
api
:
bce_loss
args
:
(Tensor input, Tensor label)
output
:
Tensor
...
...
python/paddle/utils/code_gen/backward.yaml
浏览文件 @
77cf305f
...
...
@@ -118,6 +118,18 @@
kernel
:
func
:
atanh_grad
-
backward_api
:
batch_norm_grad
forward
:
batch_norm (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
args
:
(Tensor x, Tensor scale, Tensor bias, Tensor mean_out, Tensor variance_out, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
output
:
Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
infer_meta
:
func
:
GeneralTernaryGradInferMeta
param
:
[
x
,
scale
,
bias
]
kernel
:
func
:
batch_norm_grad
data_type
:
out_grad
optional
:
mean_out, variance_out, reserve_space
-
backward_api
:
bce_loss_grad
forward
:
bce_loss (Tensor input, Tensor label) -> Tensor(out)
args
:
(Tensor input, Tensor label, Tensor out_grad)
...
...
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