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未验证 提交 f9c51e8c 编写于 作者: I iLeGend 提交者： GitHub
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[xdoctest][task 213,215-217] reformat example code with google style in... 

[xdoctest][task 213,215-217] reformat example code with google style in `python/paddle/distributed/fleet/base` (#56651)

* [xdoctest][task 213,215-217] reformat example code with google style in python/paddle/distributed/fleet/base

* fix output as comments
上级 c7727885
隐藏空白更改
内联 并排
Showing with 138 addition and 133 deletion
python/paddle/distributed/fleet/base/orthogonal_strategy.py
浏览文件 @ f9c51e8c
......@@ -36,14 +36,14 @@ class OrthogonalStrategy:
Examples:
.. code-block:: python
# required: distributed
import paddle
import paddle.distributed as dist
from paddle.distributed.fleet.base.strategy_group import DPGroup, MPGroup, PPGroup
from paddle.distributed.fleet.base.orthogonal_strategy import OrthogonalStrategy
dist.init_parallel_env()
strategy = OrthogonalStrategy([("dp", 2, DPGroup), ("mp", 2, MPGroup), ("pp", 2, PPGroup)], fused_strategy_dict={"check": ["mp", "pp"]})
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
>>> import paddle
>>> import paddle.distributed as dist
>>> from paddle.distributed.fleet.base.strategy_group import DPGroup, MPGroup, PPGroup
>>> from paddle.distributed.fleet.base.orthogonal_strategy import OrthogonalStrategy
>>> dist.init_parallel_env()
>>> strategy = OrthogonalStrategy([("dp", 2, DPGroup), ("mp", 2, MPGroup), ("pp", 2, PPGroup)], fused_strategy_dict={"check": ["mp", "pp"]})
"""
......
python/paddle/distributed/fleet/base/strategy_group.py
浏览文件 @ f9c51e8c
......@@ -29,12 +29,15 @@ class StrategyGroupBase:
Examples:
.. code-block:: python
import paddle.distributed as dist
from paddle.distributed.fleet.base.strategy_group import StrategyGroupBase
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
>>> import paddle.distributed as dist
>>> from paddle.distributed.fleet.base.strategy_group import StrategyGroupBase
>>> dist.init_parallel_env()
>>> strategy_group = dist.fleet.base.strategy_group.StrategyGroupBase([[0, 1], [2, 3]])
>>> print(strategy_group.world_size)
2
dist.init_parallel_env()
strategy_group = dist.fleet.base.strategy_group.StrategyGroupBase([[0, 1], [2, 3]])
print(strategy_group.world_size) # 2
"""
......
python/paddle/distributed/fleet/base/topology.py
浏览文件 @ f9c51e8c
......@@ -43,9 +43,11 @@ class ParallelMode:
Examples:
.. code-block:: python
import paddle
parallel_mode = paddle.distributed.ParallelMode
print(parallel_mode.DATA_PARALLEL) # 0
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
>>> import paddle
>>> parallel_mode = paddle.distributed.ParallelMode
>>> print(parallel_mode.DATA_PARALLEL)
0
"""
......
python/paddle/distributed/fleet/base/util_factory.py
浏览文件 @ f9c51e8c
......@@ -78,37 +78,36 @@ class UtilBase:
Examples:
.. code-block:: python
# Save the following code in `train.py` , and then execute the command `fleetrun --server_num 2 --worker_num 2 train.py` .
import paddle.distributed.fleet as fleet
from paddle.distributed.fleet import PaddleCloudRoleMaker
import sys
import numpy as np
import os
os.environ["PADDLE_WITH_GLOO"] = "2"
def train():
role = PaddleCloudRoleMaker(
is_collective=False,
init_gloo=True,
path="./tmp_gloo")
fleet.init(role)
if fleet.is_server():
input = [1, 2]
output = fleet.util.all_reduce(input, "sum", "server")
print(output)
# [2, 4]
elif fleet.is_worker():
input = np.array([3, 4])
output = fleet.util.all_reduce(input, "sum", "worker")
print(output)
# [6, 8]
output = fleet.util.all_reduce(input, "sum", "all")
print(output)
# [8, 12]
if __name__ == "__main__":
train()
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
>>> # Save the following code in `train.py` , and then execute the command `fleetrun --server_num 2 --worker_num 2 train.py` .
>>> import paddle.distributed.fleet as fleet
>>> from paddle.distributed.fleet import PaddleCloudRoleMaker
>>> import sys
>>> import numpy as np
>>> import os
>>> os.environ["PADDLE_WITH_GLOO"] = "2"
>>> def train():
... role = PaddleCloudRoleMaker(
... is_collective=False,
... init_gloo=True,
... path="./tmp_gloo")
... fleet.init(role)
...
... if fleet.is_server():
... input = np.array([1, 2])
... output = fleet.util.all_reduce(input, "sum", "server")
... print(output) # [2, 4]
... elif fleet.is_worker():
... input = np.array([3, 4])
... output = fleet.util.all_reduce(input, "sum", "worker")
... print(output) # [6, 8]
... output = fleet.util.all_reduce(input, "sum", "all")
... print(output) # [8, 12]
>>> if __name__ == "__main__":
... train()
"""
return self.role_maker._all_reduce(input, mode, comm_world)
......@@ -123,33 +122,33 @@ class UtilBase:
.. code-block:: python
# Save the following code in `train.py` , and then execute the command `fleetrun --server_num 2 --worker_num 2 train.py` .
import paddle.distributed.fleet as fleet
from paddle.distributed.fleet import PaddleCloudRoleMaker
import sys
import os
os.environ["PADDLE_WITH_GLOO"] = "2"
def train():
role = PaddleCloudRoleMaker(
is_collective=False,
init_gloo=True,
path="./tmp_gloo")
fleet.init(role)
if fleet.is_server():
fleet.util.barrier("server")
print("all server arrive here")
elif fleet.is_worker():
fleet.util.barrier("worker")
print("all server arrive here")
fleet.util.barrier("all")
print("all servers and workers arrive here")
if __name__ == "__main__":
train()
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
>>> # Save the following code in `train.py` , and then execute the command `fleetrun --server_num 2 --worker_num 2 train.py` .
>>> import paddle.distributed.fleet as fleet
>>> from paddle.distributed.fleet import PaddleCloudRoleMaker
>>> import sys
>>> import os
>>> os.environ["PADDLE_WITH_GLOO"] = "2"
>>> def train():
... role = PaddleCloudRoleMaker(
... is_collective=False,
... init_gloo=True,
... path="./tmp_gloo")
... fleet.init(role)
...
... if fleet.is_server():
... fleet.util.barrier("server")
... print("all server arrive here") # all server arrive here
... elif fleet.is_worker():
... fleet.util.barrier("worker")
... print("all server arrive here") # all server arrive here
... fleet.util.barrier("all")
... print("all servers and workers arrive here") #all servers and workers arrive here
>>> if __name__ == "__main__":
... train()
"""
self.role_maker._barrier(comm_world)
......@@ -168,37 +167,35 @@ class UtilBase:
.. code-block:: python
# Save the following code in `train.py` , and then execute the command `fleetrun --server_num 2 --worker_num 2 train.py` .
import paddle.distributed.fleet as fleet
from paddle.distributed.fleet import PaddleCloudRoleMaker
import sys
import os
os.environ["PADDLE_WITH_GLOO"] = "2"
def train():
role = PaddleCloudRoleMaker(
is_collective=False,
init_gloo=True,
path="./tmp_gloo")
fleet.init(role)
if fleet.is_server():
input = fleet.server_index()
output = fleet.util.all_gather(input, "server")
print(output)
# output = [0, 1]
elif fleet.is_worker():
input = fleet.worker_index()
output = fleet.util.all_gather(input, "worker")
# output = [0, 1]
print(output)
output = fleet.util.all_gather(input, "all")
print(output)
# output = [0, 1, 0, 1]
if __name__ == "__main__":
train()
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
>>> # Save the following code in `train.py` , and then execute the command `fleetrun --server_num 2 --worker_num 2 train.py` .
>>> import paddle.distributed.fleet as fleet
>>> from paddle.distributed.fleet import PaddleCloudRoleMaker
>>> import sys
>>> import os
>>> os.environ["PADDLE_WITH_GLOO"] = "2"
>>> def train():
... role = PaddleCloudRoleMaker(
... is_collective=False,
... init_gloo=True,
... path="./tmp_gloo")
... fleet.init(role)
...
... if fleet.is_server():
... input = fleet.server_index()
... output = fleet.util.all_gather(input, "server")
... print(output) # [0, 1]
... elif fleet.is_worker():
... input = fleet.worker_index()
... output = fleet.util.all_gather(input, "worker")
... print(output) # [0, 1]
... output = fleet.util.all_gather(input, "all")
... print(output) # [0, 1, 0, 1]
>>> if __name__ == "__main__":
... train()
"""
return self.role_maker._all_gather(input, comm_world)
......@@ -250,21 +247,22 @@ class UtilBase:
.. code-block:: python
import paddle.distributed.fleet as fleet
from paddle.distributed.fleet import UserDefinedRoleMaker
role = UserDefinedRoleMaker(
is_collective=False,
init_gloo=False,
current_id=0,
role=fleet.Role.WORKER,
worker_endpoints=["127.0.0.1:6003", "127.0.0.1:6004"],
server_endpoints=["127.0.0.1:6001", "127.0.0.1:6002"])
fleet.init(role)
files = fleet.util.get_file_shard(["file1", "file2", "file3"])
print(files)
# files = ["file1", "file2"]
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
>>> import paddle.distributed.fleet as fleet
>>> from paddle.distributed.fleet import UserDefinedRoleMaker
>>> role = UserDefinedRoleMaker(
... is_collective=False,
... init_gloo=False,
... current_id=0,
... role=fleet.Role.WORKER,
... worker_endpoints=["127.0.0.1:6003", "127.0.0.1:6004"],
... server_endpoints=["127.0.0.1:6001", "127.0.0.1:6002"])
>>> fleet.init(role)
>>> files = fleet.util.get_file_shard(["file1", "file2", "file3"])
>>> print(files)
["file1", "file2"]
"""
if not isinstance(files, list):
raise TypeError("files should be a list of file need to be read.")
......@@ -299,19 +297,21 @@ class UtilBase:
.. code-block:: python
import paddle.distributed.fleet as fleet
from paddle.distributed.fleet import UserDefinedRoleMaker
role = UserDefinedRoleMaker(
is_collective=False,
init_gloo=False,
current_id=0,
role=fleet.Role.WORKER,
worker_endpoints=["127.0.0.1:6003", "127.0.0.1:6004"],
server_endpoints=["127.0.0.1:6001", "127.0.0.1:6002"])
fleet.init(role)
fleet.util.print_on_rank("I'm worker 0", 0)
>>> # doctest: +REQUIRES(env: DISTRIBUTED)
>>> import paddle.distributed.fleet as fleet
>>> from paddle.distributed.fleet import UserDefinedRoleMaker
>>> role = UserDefinedRoleMaker(
... is_collective=False,
... init_gloo=False,
... current_id=0,
... role=fleet.Role.WORKER,
... worker_endpoints=["127.0.0.1:6003", "127.0.0.1:6004"],
... server_endpoints=["127.0.0.1:6001", "127.0.0.1:6002"])
>>> fleet.init(role)
>>> fleet.util.print_on_rank("I'm worker 0", 0)
I'm worker 0
"""
if self.role_maker._worker_index() != rank_id:
return
......
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