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feat: added gather example #54

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176 changes: 176 additions & 0 deletions examples/gather/m8d.py
Original file line number Diff line number Diff line change
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# Copyright 2024 Cisco Systems, Inc. and its affiliates
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# SPDX-License-Identifier: Apache-2.0

"""
m8d.py: This script demonstrates how to
execute gather on tensors for each rank in a world.
"""

import argparse
import asyncio
import os

import torch
import torch.distributed as dist

NUM_OF_STEPS = 100


async def init_world(world_name, rank, size, backend="gloo", addr="127.0.0.1", port=-1):
"""
Initialize the distributed environment.

Args:
world_name (str): Name of the world.
rank (int): Rank of the process.
size (int): Number of processes.
backend (str): Backend used for communication.
addr (str): Address to use for communication.
port (int): Port to use for communication.
"""
await world_manager.initialize_world(
world_name, rank, size, backend=backend, addr=addr, port=port
)


def _prepare_tensors(world_size, rank, backend):
"""
Prepare tensors

Args:
world_size (int): Size of the world.
rank (int): Rank of the process.
backend (str): Backend used for communication.
"""
tensors = [
torch.round(torch.rand(world_size) * 5 + 1),
torch.round(torch.rand(world_size) * 5 + 3),
torch.round(torch.rand(world_size) * 5 + 5),
]
tensor = torch.round(torch.rand(world_size) * 5 + 1)

if backend == "nccl":
tensors = [tensor.to(f"cuda:{rank}") for tensor in tensors]
tensor = tensor.to(f"cuda:{rank}")

return tensors, tensor


async def gather(world_name, world_size, rank, backend):
"""
Perform gather

Args:
world_name (str): Name of the world.
world_size (int): Size of the world.
rank (int): Rank in the world.
backend (str): Backend used for communication.
"""
world_communicator = world_manager.communicator

step = 1

while step <= NUM_OF_STEPS:
tensors, tensor = _prepare_tensors(world_size, rank, backend)
dst = step % world_size

print(
"Rank ",
rank,
" within world ",
world_name,
" sends tensor ",
tensor,
" to ",
dst,
)

await world_communicator.gather(
tensor, tensors if rank == dst else None, dst, world_name
)

if rank == dst:
print(
"Rank ",
rank,
" within world ",
world_name,
" has gathered tensors ",
tensors,
)

print(f"done with step: {step}")

await asyncio.sleep(1)
step += 1


world_manager = None


async def main(args):
"""
Main function to run the script.

Args:
args: Command line arguments.
"""
world_size = 3
global world_manager

world_manager = dist.WorldManager()

assert len(args.worldinfo) <= 2, "the number of worldinfo arguments must be <= 2"

worlds_ranks = {}

for item in args.worldinfo:
world_index, rank = item.split(",")
rank = int(rank)
world_index = int(world_index)

assert rank <= 2, "the rank must be <= 2"
assert world_index > 0, "the world index must be greater than 0"

port = 29500 + world_index * 1000
world_name = f"world{world_index}"
worlds_ranks[world_name] = rank

await init_world(world_name, rank, world_size, args.backend, args.addr, port)

tasks = []

for world_name, rank in worlds_ranks.items():
t = asyncio.create_task(gather(world_name, world_size, rank, args.backend))
tasks.append(t)

await asyncio.gather(*tasks)

world_manager.cleanup()


if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--backend", default="gloo")
parser.add_argument("--addr", default="127.0.0.1")
# --worldinfo argument is composed by the world index and the rank of the worker in that world.
# for example: --worldinfo 1,0` means world with the index 1 will have a rank 0
parser.add_argument("--worldinfo", type=str, action="append")

args = parser.parse_args()

loop = asyncio.get_event_loop()
loop.run_until_complete(main(args))