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030b298e
编写于
9月 02, 2020
作者:
L
lilong12
提交者:
GitHub
9月 02, 2020
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差异文件
fix sample codes in collective.py (#26787)
* fix sample codes, test=develop
上级
435ab2aa
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1
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1 changed file
with
92 addition
and
87 deletion
+92
-87
python/paddle/distributed/collective.py
python/paddle/distributed/collective.py
+92
-87
未找到文件。
python/paddle/distributed/collective.py
浏览文件 @
030b298e
...
...
@@ -73,20 +73,21 @@ def broadcast(tensor, src, group=0):
Examples:
.. code-block:: python
import paddle
import paddle.prepare_context as prepare_context
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.ParallelEnv().dev_id)
prepare_context()
if paddle.ParallelEnv().local_rank == 0:
np_data = np.array([[4, 5, 6], [4, 5, 6]])
else:
np_data = np.array([[1, 2, 3], [1, 2, 3]])
data = paddle.to_tensor(np_data)
paddle.distributed.broadcast(data, 1)
out = data.numpy()
# [[1, 2, 3], [1, 2, 3]]
import numpy as np
import paddle
from paddle.distributed import init_parallel_env
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.distributed.ParallelEnv().dev_id)
init_parallel_env()
if paddle.distributed.ParallelEnv().local_rank == 0:
np_data = np.array([[4, 5, 6], [4, 5, 6]])
else:
np_data = np.array([[1, 2, 3], [1, 2, 3]])
data = paddle.to_tensor(np_data)
paddle.distributed.broadcast(data, 1)
out = data.numpy()
# [[1, 2, 3], [1, 2, 3]]
"""
if
in_dygraph_mode
():
return
core
.
ops
.
c_broadcast
(
tensor
,
tensor
,
'root'
,
src
,
...
...
@@ -129,21 +130,22 @@ def all_reduce(tensor, op=ReduceOp.SUM, group=0):
Examples:
.. code-block:: python
import paddle
from paddle.distributed import ReduceOp
import paddle.prepare_context as prepare_context
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.ParallelEnv().dev_id)
prepare_context()
if paddle.ParallelEnv().local_rank == 0:
np_data = np.array([[4, 5, 6], [4, 5, 6]])
else:
np_data = np.array([[1, 2, 3], [1, 2, 3]])
data = paddle.to_tensor(np_data)
paddle.distributed.all_reduce(data)
out = data.numpy()
# [[5, 7, 9], [5, 7, 9]]
import numpy as np
import paddle
from paddle.distributed import ReduceOp
from paddle.distributed import init_parallel_env
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.distributed.ParallelEnv().dev_id)
init_parallel_env()
if paddle.distributed.ParallelEnv().local_rank == 0:
np_data = np.array([[4, 5, 6], [4, 5, 6]])
else:
np_data = np.array([[1, 2, 3], [1, 2, 3]])
data = paddle.to_tensor(np_data)
paddle.distributed.all_reduce(data)
out = data.numpy()
# [[5, 7, 9], [5, 7, 9]]
"""
if
in_dygraph_mode
():
if
op
==
ReduceOp
.
SUM
:
...
...
@@ -204,20 +206,21 @@ def reduce(tensor, dst, op=ReduceOp.SUM, group=0):
Examples:
.. code-block:: python
import paddle
import paddle.prepare_context as prepare_context
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.ParallelEnv().dev_id)
prepare_context()
if paddle.ParallelEnv().local_rank == 0:
np_data = np.array([[4, 5, 6], [4, 5, 6]])
else:
np_data = np.array([[1, 2, 3], [1, 2, 3]])
data = paddle.to_tensor(np_data)
paddle.distributed.reduce(data, 0)
out = data.numpy()
# [[5, 7, 9], [5, 7, 9]]
import numpy as np
import paddle
from paddle.distributed import init_parallel_env
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.distributed.ParallelEnv().dev_id)
init_parallel_env()
if paddle.distributed.ParallelEnv().local_rank == 0:
np_data = np.array([[4, 5, 6], [4, 5, 6]])
else:
np_data = np.array([[1, 2, 3], [1, 2, 3]])
data = paddle.to_tensor(np_data)
paddle.distributed.reduce(data, 0)
out = data.numpy()
# [[5, 7, 9], [5, 7, 9]]
"""
if
in_dygraph_mode
():
if
op
==
ReduceOp
.
SUM
:
...
...
@@ -286,25 +289,26 @@ def all_gather(tensor_list, tensor, group=0):
Examples:
.. code-block:: python
import paddle
import paddle.prepare_context as prepare_context
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.ParallelEnv().dev_id)
prepare_context()
tensor_list = []
if paddle.ParallelEnv().local_rank == 0:
np_data1 = np.array([[4, 5, 6], [4, 5, 6]])
np_data2 = np.array([[4, 5, 6], [4, 5, 6]])
data1 = paddle.to_tensor(np_data1)
data2 = paddle.to_tensor(np_data2)
paddle.distributed.all_gather(tensor_list, data1)
else:
np_data1 = np.array([[1, 2, 3], [1, 2, 3]])
np_data2 = np.array([[1, 2, 3], [1, 2, 3]])
data1 = paddle.to_tensor(np_data1)
data2 = paddle.to_tensor(np_data2)
out = paddle.distributed.all_gather(tensor_list, data2)
import numpy as np
import paddle
from paddle.distributed import init_parallel_env
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.distributed.ParallelEnv().dev_id)
init_parallel_env()
tensor_list = []
if paddle.distributed.ParallelEnv().local_rank == 0:
np_data1 = np.array([[4, 5, 6], [4, 5, 6]])
np_data2 = np.array([[4, 5, 6], [4, 5, 6]])
data1 = paddle.to_tensor(np_data1)
data2 = paddle.to_tensor(np_data2)
paddle.distributed.all_gather(tensor_list, data1)
else:
np_data1 = np.array([[1, 2, 3], [1, 2, 3]])
np_data2 = np.array([[1, 2, 3], [1, 2, 3]])
data1 = paddle.to_tensor(np_data1)
data2 = paddle.to_tensor(np_data2)
paddle.distributed.all_gather(tensor_list, data2)
"""
op_type
=
'c_allgather'
helper
=
LayerHelper
(
op_type
,
**
locals
())
...
...
@@ -359,25 +363,26 @@ def scatter(tensor, tensor_list=None, src=0, group=0):
Examples:
.. code-block:: python
import paddle
import paddle.prepare_context as prepare_context
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.ParallelEnv().dev_id)
prepare_context()
if paddle.ParallelEnv().local_rank == 0:
np_data1 = np.array([7, 8, 9])
np_data2 = np.array([10, 11, 12])
else:
np_data1 = np.array([1, 2, 3])
np_data2 = np.array([4, 5, 6])
data1 = paddle.to_tensor(np_data1)
data2 = paddle.to_tensor(np_data2)
if paddle.ParallelEnv().local_rank == 0:
paddle.distributed.scatter(data1, src=1)
else:
paddle.distributed.scatter(data1, tensor_list=[data1, data2], src=1)
out = data1.numpy()
import numpy as np
import paddle
from paddle.distributed import init_parallel_env
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.distributed.ParallelEnv().dev_id)
init_parallel_env()
if paddle.distributed.ParallelEnv().local_rank == 0:
np_data1 = np.array([7, 8, 9])
np_data2 = np.array([10, 11, 12])
else:
np_data1 = np.array([1, 2, 3])
np_data2 = np.array([4, 5, 6])
data1 = paddle.to_tensor(np_data1)
data2 = paddle.to_tensor(np_data2)
if paddle.distributed.ParallelEnv().local_rank == 0:
paddle.distributed.scatter(data1, src=1)
else:
paddle.distributed.scatter(data1, tensor_list=[data1, data2], src=1)
out = data1.numpy()
"""
op_type
=
'c_scatter'
global
_default_group
...
...
@@ -425,13 +430,13 @@ def barrier(group=0):
Examples:
.. code-block:: python
import paddle
import paddle.prepare_context as prepare_context
import paddle
from paddle.distributed import init_parallel_env
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle
.ParallelEnv().dev_id)
prepare_context
()
paddle.distributed.barrier()
paddle.disable_static()
paddle.set_device('gpu:%d'%paddle.distributed
.ParallelEnv().dev_id)
init_parallel_env
()
paddle.distributed.barrier()
"""
op_type
=
'barrier'
temp
=
paddle
.
fill_constant
([
1
],
dtype
=
"int32"
,
value
=
"1"
)
...
...
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