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0211a833
编写于
5月 23, 2022
作者:
Y
YuanRisheng
提交者:
GitHub
5月 23, 2022
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差异文件
Add double grad yaml for celu/sqrt/rsqrt/square op (#42895)
* add double grad yaml * fix bugs when compile infrt
上级
e5ebd347
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
105 addition
and
6 deletion
+105
-6
paddle/fluid/eager/auto_code_generator/final_state_generator/codegen_utils.py
...uto_code_generator/final_state_generator/codegen_utils.py
+2
-1
paddle/phi/kernels/activation_kernel.h
paddle/phi/kernels/activation_kernel.h
+1
-1
python/paddle/fluid/tests/unittests/test_activation_nn_grad.py
...n/paddle/fluid/tests/unittests/test_activation_nn_grad.py
+20
-0
python/paddle/fluid/tests/unittests/test_activation_op.py
python/paddle/fluid/tests/unittests/test_activation_op.py
+7
-1
python/paddle/nn/functional/activation.py
python/paddle/nn/functional/activation.py
+3
-1
python/paddle/tensor/layer_function_generator.py
python/paddle/tensor/layer_function_generator.py
+8
-2
python/paddle/utils/code_gen/api.yaml
python/paddle/utils/code_gen/api.yaml
+10
-0
python/paddle/utils/code_gen/backward.yaml
python/paddle/utils/code_gen/backward.yaml
+54
-0
未找到文件。
paddle/fluid/eager/auto_code_generator/final_state_generator/codegen_utils.py
浏览文件 @
0211a833
...
...
@@ -28,7 +28,8 @@ ops_to_fill_zero_for_empty_grads = set([
"multiply_triple_grad"
,
"conv2d_grad_grad"
,
"batch_norm_double_grad"
,
"tanh_double_grad"
,
"tanh_triple_grad"
,
"subtract_double_grad"
,
"divide_double_grad"
,
"log_double_grad"
,
"elu_double_grad"
,
"leaky_relu_double_grad"
"leaky_relu_double_grad"
,
"sqrt_double_grad"
,
"rsqrt_double_grad"
,
"square_double_grad"
,
"celu_double_grad"
])
# For API dispatch used at python-level
...
...
paddle/phi/kernels/activation_kernel.h
浏览文件 @
0211a833
...
...
@@ -78,7 +78,7 @@ DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(SoftShrink, lambda)
DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS
(
HardShrink
,
threshold
)
DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS
(
Elu
,
alpha
)
DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS
(
Swish
,
beta
)
DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS
(
c
elu
,
alpha
)
DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS
(
C
elu
,
alpha
)
DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS
(
BRelu
,
t_min
,
t_max
)
DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS
(
STanh
,
scale_a
,
scale_b
)
...
...
python/paddle/fluid/tests/unittests/test_activation_nn_grad.py
浏览文件 @
0211a833
...
...
@@ -253,6 +253,9 @@ class TestELUDoubleGradCheck(unittest.TestCase):
class
TestCELUDoubleGradCheck
(
unittest
.
TestCase
):
def
celu_wrapper
(
self
,
x
):
return
paddle
.
nn
.
functional
.
celu
(
x
[
0
],
alpha
=
0.2
)
@
prog_scope
()
def
func
(
self
,
place
):
shape
=
[
2
,
4
,
4
,
4
]
...
...
@@ -269,6 +272,8 @@ class TestCELUDoubleGradCheck(unittest.TestCase):
x_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
shape
).
astype
(
dtype
)
gradient_checker
.
double_grad_check
(
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
,
eps
=
eps
)
gradient_checker
.
double_grad_check_for_dygraph
(
self
.
celu_wrapper
,
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
)
def
test_grad
(
self
):
paddle
.
enable_static
()
...
...
@@ -280,6 +285,9 @@ class TestCELUDoubleGradCheck(unittest.TestCase):
class
TestSqrtDoubleGradCheck
(
unittest
.
TestCase
):
def
sqrt_wrapper
(
self
,
x
):
return
paddle
.
sqrt
(
x
[
0
])
@
prog_scope
()
def
func
(
self
,
place
):
shape
=
[
2
,
3
,
7
,
9
]
...
...
@@ -294,6 +302,8 @@ class TestSqrtDoubleGradCheck(unittest.TestCase):
gradient_checker
.
double_grad_check
(
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
,
eps
=
eps
)
gradient_checker
.
double_grad_check_for_dygraph
(
self
.
sqrt_wrapper
,
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
)
def
test_grad
(
self
):
paddle
.
enable_static
()
...
...
@@ -305,6 +315,9 @@ class TestSqrtDoubleGradCheck(unittest.TestCase):
class
TestRsqrtDoubleGradCheck
(
unittest
.
TestCase
):
def
rsqrt_wrapper
(
self
,
x
):
return
paddle
.
rsqrt
(
x
[
0
])
@
prog_scope
()
def
func
(
self
,
place
):
shape
=
[
2
,
3
,
7
,
9
]
...
...
@@ -319,6 +332,8 @@ class TestRsqrtDoubleGradCheck(unittest.TestCase):
gradient_checker
.
double_grad_check
(
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
,
eps
=
eps
)
gradient_checker
.
double_grad_check_for_dygraph
(
self
.
rsqrt_wrapper
,
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
)
def
test_grad
(
self
):
paddle
.
enable_static
()
...
...
@@ -330,6 +345,9 @@ class TestRsqrtDoubleGradCheck(unittest.TestCase):
class
TestSquareDoubleGradCheck
(
unittest
.
TestCase
):
def
square_wrapper
(
self
,
x
):
return
paddle
.
square
(
x
[
0
])
@
prog_scope
()
def
func
(
self
,
place
):
# the shape of input variable should be clearly specified, not inlcude -1.
...
...
@@ -344,6 +362,8 @@ class TestSquareDoubleGradCheck(unittest.TestCase):
gradient_checker
.
double_grad_check
(
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
,
eps
=
eps
)
gradient_checker
.
double_grad_check_for_dygraph
(
self
.
square_wrapper
,
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
)
def
test_grad
(
self
):
paddle
.
enable_static
()
...
...
python/paddle/fluid/tests/unittests/test_activation_op.py
浏览文件 @
0211a833
...
...
@@ -2003,6 +2003,7 @@ class TestCELU(TestActivation):
self
.
op_type
=
"celu"
self
.
init_dtype
()
self
.
python_api
=
paddle
.
nn
.
functional
.
celu
np
.
random
.
seed
(
1024
)
x
=
np
.
random
.
uniform
(
-
3
,
3
,
[
10
,
12
]).
astype
(
self
.
dtype
)
alpha
=
1.5
...
...
@@ -2014,7 +2015,7 @@ class TestCELU(TestActivation):
def
test_check_grad
(
self
):
if
self
.
dtype
==
np
.
float16
:
return
self
.
check_grad
([
'X'
],
'Out'
)
self
.
check_grad
([
'X'
],
'Out'
,
check_eager
=
True
)
class
TestCELUAPI
(
unittest
.
TestCase
):
...
...
@@ -2080,6 +2081,11 @@ class TestCELUAPI(unittest.TestCase):
name
=
'x_fp16'
,
shape
=
[
10
,
12
],
dtype
=
'float16'
)
self
.
celu
(
x_fp16
)
def
test_api_eager_dygraph
(
self
):
with
_test_eager_guard
():
self
.
test_dygraph_api
()
self
.
test_errors
()
class
TestReciprocal
(
TestActivation
):
def
setUp
(
self
):
...
...
python/paddle/nn/functional/activation.py
浏览文件 @
0211a833
...
...
@@ -63,8 +63,10 @@ def celu(x, alpha=1.0, name=None):
if
alpha
==
0
:
raise
ZeroDivisionError
(
"alpha cannot be 0 for celu"
)
if
in_dynamic_mode
():
if
_in_legacy_dygraph
():
return
_C_ops
.
celu
(
x
,
'alpha'
,
alpha
)
if
in_dygraph_mode
():
return
_C_ops
.
final_state_celu
(
x
,
alpha
)
check_variable_and_dtype
(
x
,
'x'
,
[
'float16'
,
'float32'
,
'float64'
],
'celu'
)
helper
=
LayerHelper
(
"celu"
,
**
locals
())
...
...
python/paddle/tensor/layer_function_generator.py
浏览文件 @
0211a833
...
...
@@ -21,7 +21,7 @@ import string
from
six.moves
import
cStringIO
from
..static
import
Variable
from
..fluid.proto
import
framework_pb2
from
..framework
import
OpProtoHolder
,
core
,
convert_np_dtype_to_dtype_
from
..framework
import
OpProtoHolder
,
core
,
convert_np_dtype_to_dtype_
,
_non_static_mode
,
in_dygraph_mode
from
..framework
import
LayerHelper
from
..fluid.data_feeder
import
check_variable_and_dtype
import
paddle
...
...
@@ -256,7 +256,13 @@ def generate_activation_fn(op_type):
op_proto
=
OpProtoHolder
.
instance
().
get_op_proto
(
op_type
)
def
func
(
x
,
name
=
None
):
if
paddle
.
in_dynamic_mode
():
final_state_op_type
=
"final_state_%s"
%
op_type
if
in_dygraph_mode
()
and
hasattr
(
_C_ops
,
final_state_op_type
):
op
=
getattr
(
_C_ops
,
final_state_op_type
)
return
op
(
x
)
# TODO(dev): Because some ops' yaml has not been migrated.
# Replace it with _in_legacy_dygraph while all yaml work is done.
if
_non_static_mode
():
op
=
getattr
(
_C_ops
,
op_type
)
return
op
(
x
)
...
...
python/paddle/utils/code_gen/api.yaml
浏览文件 @
0211a833
...
...
@@ -319,6 +319,16 @@
func
:
ceil
backward
:
ceil_grad
-
api
:
celu
args
:
(Tensor x, float alpha)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
celu
backward
:
celu_grad
# cholesky
-
api
:
cholesky
args
:
(Tensor x, bool upper)
...
...
python/paddle/utils/code_gen/backward.yaml
浏览文件 @
0211a833
...
...
@@ -232,6 +232,27 @@
kernel
:
func
:
ceil_grad
-
backward_api
:
celu_double_grad
forward
:
celu_grad(Tensor x, Tensor grad_out, float alpha) -> Tensor(grad_x)
args
:
(Tensor x, Tensor grad_out, Tensor grad_x_grad, float alpha)
output
:
Tensor(x_grad), Tensor(grad_out_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
x
]
kernel
:
func
:
celu_double_grad
-
backward_api
:
celu_grad
forward
:
celu(Tensor x, float alpha) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, float alpha)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
celu_grad
backward
:
celu_double_grad
-
backward_api
:
cholesky_grad
forward
:
cholesky (Tensor x, bool upper) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad, bool upper)
...
...
@@ -1544,6 +1565,16 @@
kernel
:
func
:
round_grad
-
backward_api
:
rsqrt_double_grad
forward
:
rsqrt_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x)
args
:
(Tensor out, Tensor grad_x, Tensor grad_x_grad)
output
:
Tensor(out_grad), Tensor(grad_out_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
out
,
out
]
kernel
:
func
:
rsqrt_double_grad
-
backward_api
:
rsqrt_grad
forward
:
rsqrt (Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
...
...
@@ -1553,6 +1584,7 @@
param
:
[
out
]
kernel
:
func
:
rsqrt_grad
backward
:
rsqrt_double_grad
-
backward_api
:
scale_double_grad
forward
:
scale_grad (Tensor grad_out, Scalar scale, float bias, bool bias_after_scale) -> Tensor(grad_x)
...
...
@@ -1731,6 +1763,16 @@
invoke
:
concat( out_grad, axis)
# TODO(zhangyunfei) The config of double grad and triple grad will be supported in the future.
-
backward_api
:
sqrt_double_grad
forward
:
sqrt_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x)
args
:
(Tensor out, Tensor grad_x, Tensor grad_x_grad)
output
:
Tensor(out_grad), Tensor(grad_out_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
out
,
out
]
kernel
:
func
:
sqrt_double_grad
-
backward_api
:
sqrt_grad
forward
:
sqrt (Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
...
...
@@ -1740,6 +1782,17 @@
param
:
[
out
]
kernel
:
func
:
sqrt_grad
backward
:
sqrt_double_grad
-
backward_api
:
square_double_grad
forward
:
square_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x)
args
:
(Tensor x, Tensor grad_out, Tensor grad_x_grad)
output
:
Tensor(x_grad), Tensor(grad_out_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
x
]
kernel
:
func
:
square_double_grad
-
backward_api
:
square_grad
forward
:
square (Tensor x) -> Tensor(out)
...
...
@@ -1750,6 +1803,7 @@
param
:
[
x
]
kernel
:
func
:
square_grad
backward
:
square_double_grad
-
backward_api
:
squeeze_grad
forward
:
squeeze(Tensor x, int[] axes) -> Tensor(out), Tensor(xshape)
...
...
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