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fix sample codes in collective.py (#26787)

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* fix sample codes, test=develop
revert-26856-strategy_example2
lilong12 5 years ago committed by GitHub
parent 435ab2aa8a
commit 030b298e82
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1 changed files with 92 additions and 87 deletions
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python/paddle/distributed/collective.py
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@ -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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