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sandyhouse merged 1 commit into from
Sep 17, 2021
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fix launch doc #35824

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49 changes: 24 additions & 25 deletions python/paddle/distributed/fleet/launch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -400,33 +400,33 @@ def launch():


Base Parameters:
- ``--log_dir``: The path for each process's log. e.g ``--log_dir=output_dir``. Default ``--log_dir=log``.
- ``--log_dir``: The path for each process's log. e.g., ``--log_dir=output_dir``. Default ``--log_dir=log``.

- ``--nproc_per_node``: The number of processes to launch on a node. In gpu training, it should be less or equal to the gpus number of you system(or you set by --gpus). And so each process can bound to one or average number of gpus. e.g ``--nproc_per_node=8``
- ``--nproc_per_node``: The number of processes to launch on a node. In gpu training, it should be less or equal to the gpus number of you system(or you set by --gpus). e.g., ``--nproc_per_node=8``

- ``--run_mode``: run mode of job, can be:collective/ps/ps-heter. e.g ``--run_mode=ps``. Default ``--run_mode=collective``.
- ``--run_mode``: run mode of job, can be:collective/ps/ps-heter. e.g., ``--run_mode=ps``. Default ``--run_mode=collective``.

- ``--gpus``: It's for gpu training. e.g ``--gpus=0,1,2,3`` will launch four training processes each bound to one gpu.
- ``--gpus``: It's for gpu training. e.g., ``--gpus=0,1,2,3`` will launch four training processes each bound to one gpu.

- ``--selected_gpus``: gpus aliases, recommend to use ``--gpus``.

- ``--xpus``: It's for xpu training if xpu is available. e.g ``--xpus=0,1,2,3``.
- ``--xpus``: It's for xpu training if xpu is available. e.g., ``--xpus=0,1,2,3``.

- ``--selected_xpus``: xpus aliases, recommend to use ``--xpus``.

- ``training_script``: The full path to the single GPU training program/script to be launched in parallel, followed by all the arguments for the training script. e.g ``traing.py``
- ``training_script``: The full path to the single GPU training program/script to be launched in parallel, followed by all the arguments for the training script. e.g., ``traing.py``

- ``training_script_args``: The args of training_script. e.g ``--lr=0.1``
- ``training_script_args``: The args of training_script. e.g., ``--lr=0.1``

Collective Parameters:
- ``--ips``: Paddle cluster nodes ips, e.g ``--ips=192.168.0.16,192.168.0.17``. Default ``--ips=127.0.0.1``.
- ``--ips``: Paddle cluster nodes ips, e.g., ``--ips=192.168.0.16,192.168.0.17``. Default ``--ips=127.0.0.1``.

Parameter-Server Parameters:
- ``--servers``: User defined servers ip:port, e.g ``--servers="192.168.0.16:6170,192.168.0.17:6170"``
- ``--servers``: User defined servers ip:port, e.g., ``--servers="192.168.0.16:6170,192.168.0.17:6170"``

- ``--workers``: User defined workers ip:port, e.g ``--workers="192.168.0.16:6171,192.168.0.16:6172,192.168.0.17:6171,192.168.0.17:6172"``
- ``--workers``: User defined workers ip:port, e.g., ``--workers="192.168.0.16:6171,192.168.0.16:6172,192.168.0.17:6171,192.168.0.17:6172"``

- ``--heter_workers``: User defined heter workers ip:port, e.g ``--heter_workers="192.168.0.16:6172,192.168.0.17:6172"``
- ``--heter_workers``: User defined heter workers ip:port, e.g., ``--heter_workers="192.168.0.16:6172,192.168.0.17:6172"``

- ``--worker_num``: Number of workers (It recommend to set when in the emulated distributed environment using single node)

Expand All @@ -437,17 +437,14 @@ def launch():
- ``--http_port``: Gloo http Port

Elastic Parameters:
- ``--elastic_server``: etcd server host:port, e.g ``--elastic_server=127.0.0.1:2379``
- ``--elastic_server``: etcd server host:port, e.g., ``--elastic_server=127.0.0.1:2379``

- ``--job_id``: job unique id, e.g ``--job_id=job1``
- ``--job_id``: job unique id, e.g., ``--job_id=job1``

- ``--np``: job pod/node number, e.g ``--np=2``

- ``--scale``: scale np, not be used now!
- ``--np``: job pod/node number, e.g., ``--np=2``

- ``--host``: bind host, default to POD_IP env.

- ``--force``: update np force, not be used now!

Returns:
``None``
Expand All @@ -456,15 +453,17 @@ def launch():
.. code-block:: bash
:name: code-block-example-bash1

# For single node training using 4 gpus
# For training on single node using 4 gpus.

python -m paddle.distributed.launch --gpus=0,1,2,3 train.py --lr=0.01

Examples 2 (collective, multi node):
.. code-block:: bash
:name: code-block-example-bash2

# For multiple node training such as two node:192.168.0.16, 192.168.0.17
# The parameters of --gpus and --ips must be consistent in each node.

# For training on multiple nodes, e.g., 192.168.0.16, 192.168.0.17

# On 192.168.0.16:

Expand All @@ -477,15 +476,15 @@ def launch():
.. code-block:: bash
:name: code-block-example-bash3

# The emulated distributed environment using single node, 2 server and 4 worker
# To simulate distributed environment using single node, e.g., 2 servers and 4 workers.

python -m paddle.distributed.launch --server_num=2 --worker_num=4 train.py --lr=0.01

Examples 4 (ps, cpu, multi node):
.. code-block:: bash
:name: code-block-example-bash4

# For multiple node training such as two node:192.168.0.16, 192.168.0.17 with 2 servers and total 4 workers
# For training on multiple nodes, e.g., 192.168.0.16, 192.168.0.17 where each node with 1 server and 2 workers.

# On 192.168.0.16:

Expand All @@ -499,7 +498,7 @@ def launch():
.. code-block:: bash
:name: code-block-example-bash5

# The emulated distributed environment using single node, 2 server and 4 worker, each worker use single gpu
# To simulate distributed environment using single node, e.g., 2 servers and 4 workers, each worker use single gpu.

export CUDA_VISIBLE_DEVICES=0,1,2,3
python -m paddle.distributed.launch --server_num=2 --worker_num=4 train.py --lr=0.01
Expand All @@ -508,7 +507,7 @@ def launch():
.. code-block:: bash
:name: code-block-example-bash6

# For multiple node training such as two node:192.168.0.16, 192.168.0.17 with 2 servers and total 4 workers
# For training on multiple nodes, e.g., 192.168.0.16, 192.168.0.17 where each node with 1 server and 2 workers.

# On 192.168.0.16:

Expand All @@ -524,7 +523,7 @@ def launch():
.. code-block:: bash
:name: code-block-example-bash7

# The emulated distributed environment using single node, 2 server and 4 worker, two worker use gpu, two worker use cpu
# To simulate distributed environment using single node, e.g., 2 servers and 4 workers, two workers use gpu, two workers use cpu.

export CUDA_VISIBLE_DEVICES=0,1
python -m paddle.distributed.launch --server_num=2 --worker_num=2 --heter_worker_num=2 train.py --lr=0.01
Expand All @@ -533,7 +532,7 @@ def launch():
.. code-block:: bash
:name: code-block-example-bash8

# For multiple node training such as two node:192.168.0.16, 192.168.0.17 with 2 servers and total 4 workers
# For training on multiple nodes, e.g., 192.168.0.16, 192.168.0.17 where each node with 1 server, 1 gpu worker, 1 cpu worker.

# On 192.168.0.16:

Expand Down