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体验新版 GitCode,发现更多精彩内容 >>
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613a3ffe
编写于
2月 22, 2023
作者:
H
houj04
提交者:
GitHub
2月 22, 2023
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差异文件
[XPU] add fp16 support for assign. update xccl to 1.0.9. (#50702)
上级
d8845735
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
72 addition
and
66 deletion
+72
-66
cmake/external/xpu.cmake
cmake/external/xpu.cmake
+1
-1
paddle/phi/backends/xpu/xpu2_op_list.cc
paddle/phi/backends/xpu/xpu2_op_list.cc
+1
-0
paddle/phi/kernels/assign_kernel.cc
paddle/phi/kernels/assign_kernel.cc
+2
-1
python/paddle/fluid/tests/unittests/xpu/test_assign_op_xpu.py
...on/paddle/fluid/tests/unittests/xpu/test_assign_op_xpu.py
+68
-64
未找到文件。
cmake/external/xpu.cmake
浏览文件 @
613a3ffe
...
...
@@ -8,7 +8,7 @@ set(XPU_API_LIB_NAME "libxpuapi.so")
set
(
XPU_RT_LIB_NAME
"libxpurt.so"
)
set
(
XPU_BASE_DATE
"20230220"
)
set
(
XPU_XCCL_BASE_VERSION
"1.0.
8
"
)
set
(
XPU_XCCL_BASE_VERSION
"1.0.
9
"
)
if
(
NOT DEFINED XPU_BASE_URL
)
set
(
XPU_BASE_URL_WITHOUT_DATE
...
...
paddle/phi/backends/xpu/xpu2_op_list.cc
浏览文件 @
613a3ffe
...
...
@@ -46,6 +46,7 @@ XPUOpMap& get_kl2_ops() {
XPUKernelSet
({
phi
::
DataType
::
FLOAT32
,
phi
::
DataType
::
FLOAT64
,
phi
::
DataType
::
INT32
,
phi
::
DataType
::
FLOAT16
,
phi
::
DataType
::
INT64
,
phi
::
DataType
::
BOOL
})},
{
"assign_value"
,
XPUKernelSet
({
phi
::
DataType
::
FLOAT32
})},
...
...
paddle/phi/kernels/assign_kernel.cc
浏览文件 @
613a3ffe
...
...
@@ -179,5 +179,6 @@ PD_REGISTER_KERNEL(assign_value,
bool
,
int
,
float
,
int64_t
)
{}
int64_t
,
phi
::
dtype
::
float16
)
{}
#endif
python/paddle/fluid/tests/unittests/xpu/test_assign_op_xpu.py
浏览文件 @
613a3ffe
# Copyright (c) 20
18
PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 20
23
PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
...
...
@@ -13,72 +13,76 @@
# limitations under the License.
import
sys
import
unittest
import
numpy
as
np
sys
.
path
.
append
(
".."
)
import
unittest
from
op_test_xpu
import
XPUOpTest
from
xpu.get_test_cover_info
import
(
XPUOpTestWrapper
,
create_test_class
,
get_xpu_op_support_types
,
)
import
paddle
'''
class TestAssignOp(op_test.OpTest):
def setUp(self):
self.op_type = "assign"
x = np.random.random(size=(100, 10)).astype('float32')
self.inputs = {'X': x}
self.outputs = {'Out': x}
def test_forward(self):
if paddle.is_compiled_with_xpu():
place = paddle.XPUPlace(0)
self.check_output_with_place(place)
def test_backward(self):
if paddle.is_compiled_with_xpu():
place = paddle.XPUPlace(0)
self.check_grad_with_place(place, ['X'], 'Out')
class TestAssignOpWithLoDTensorArray(unittest.TestCase):
def test_assign_LoDTensorArray(self):
main_program = Program()
startup_program = Program()
with program_guard(main_program):
x = fluid.data(name='x', shape=[100, 10], dtype='float32')
x.stop_gradient = False
y = fluid.layers.fill_constant(
shape=[100, 10], dtype='float32', value=1)
z = paddle.add(x=x, y=y)
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
init_array = paddle.tensor.array_write(x=z, i=i)
array = fluid.layers.assign(init_array)
sums = paddle.tensor.array_read(array=init_array, i=i)
mean = paddle.mean(sums)
append_backward(mean)
place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
) else fluid.CPUPlace()
exe = fluid.Executor(place)
feed_x = np.random.random(size=(100, 10)).astype('float32')
ones = np.ones((100, 10)).astype('float32')
feed_add = feed_x + ones
res = exe.run(main_program,
feed={'x': feed_x},
fetch_list=[sums.name, x.grad_name])
np.testing.assert_allclose(res[0], feed_add)
np.testing.assert_allclose(res[1], ones / 1000.0)
class TestAssignOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
# The type of input must be Variable or numpy.ndarray.
x1 = fluid.create_lod_tensor(
np.array([[-1]]), [[1]], fluid.XPUPlace(0))
self.assertRaises(TypeError, fluid.layers.assign, x1)
x2 = np.array([[2.5, 2.5]], dtype='uint8')
self.assertRaises(TypeError, fluid.layers.assign, x2)
'''
if
__name__
==
'__main__'
:
paddle
.
enable_static
()
paddle
.
enable_static
()
class
XPUTestAssignOP
(
XPUOpTestWrapper
):
def
__init__
(
self
):
self
.
op_name
=
'assign'
self
.
use_dynamic_create_class
=
False
class
TestAssignOPBase
(
XPUOpTest
):
def
setUp
(
self
):
self
.
place
=
paddle
.
XPUPlace
(
0
)
self
.
init_dtype
()
self
.
set_case
()
def
set_case
(
self
):
self
.
op_type
=
'assign'
self
.
init_config
()
x
=
np
.
random
.
random
(
size
=
self
.
input_shape
).
astype
(
self
.
dtype
)
self
.
inputs
=
{
'X'
:
x
}
self
.
attrs
=
{}
self
.
outputs
=
{
'Out'
:
x
}
def
init_dtype
(
self
):
self
.
dtype
=
self
.
in_type
def
test_check_output
(
self
):
self
.
check_output_with_place
(
self
.
place
)
def
test_check_grad
(
self
):
self
.
check_grad_with_place
(
self
.
place
,
[
'X'
],
'Out'
)
def
init_config
(
self
):
self
.
input_shape
=
(
2
,
5
)
class
XPUTestAssign1
(
TestAssignOPBase
):
def
init_config
(
self
):
self
.
input_shape
=
[
2
,
768
]
class
XPUTestAssign2
(
TestAssignOPBase
):
def
init_config
(
self
):
self
.
input_shape
=
[
3
,
8
,
4096
]
class
XPUTestAssign3
(
TestAssignOPBase
):
def
init_config
(
self
):
self
.
input_shape
=
[
1024
]
class
XPUTestAssign4
(
TestAssignOPBase
):
def
init_config
(
self
):
self
.
input_shape
=
[
2
,
2
,
255
]
support_types
=
get_xpu_op_support_types
(
'assign'
)
for
stype
in
support_types
:
create_test_class
(
globals
(),
XPUTestAssignOP
,
stype
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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