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[WIP] add simplefsdp's autobucketing pass entry #1658

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[WIP] add simplefsdp's autobucketing pass entry #1658

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33 changes: 13 additions & 20 deletions torchtitan/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
import os
import time
from datetime import timedelta
from functools import partial
from typing import Any, Generator, Iterable, Optional

import torch
Expand Down Expand Up @@ -125,32 +126,24 @@ def __init__(self, job_config: JobConfig):

# allow configuring inductor comms optimizations from torchtitan commandline
if job_config.experimental.enable_simplefsdp_passes:
try:
from torch._inductor.simple_fsdp.bucket import bucket_fsdp_all_gather_concat_on_scheduler_ir
except ImportError:
print("Must use pytorch from unlanded https://github.com/pytorch/pytorch/pull/160282, e.g. torchtitan_conda_prod:5e4101faa448c2ee6b62ddd76ee08e8c")
raise

# Configs from Ruisi
# enable simplefsdp's autobucketing and reorder passes (original code in https://github.com/pytorch/pytorch/pull/160282)
from autoparallel.auto_bucketing import (
simple_fsdp_autobucketing_reordering_pass, simplefsdp_autobucketing_config
)

# set to 0.1 if you want to make bucketing more efficient with mixed dtype collectives
torch._inductor.config.simplefsdp.relax_ratio = 0
torch._inductor.config.allow_buffer_reuse = False
torch._inductor.config.simplefsdp.estimate_ir = False
torch._inductor.config.simplefsdp.estimate_verbose = False
torch._inductor.config.simplefsdp.save_estimation_path = "/mnt/mffuse/cache_ruisi/estimation_mast_"+job_config.model.flavor+".pkl"
# set to True after the first communication estimation results are saved. This would reduce decision making time.
torch._inductor.config.simplefsdp.load_cache = False
torch._inductor.config.simplefsdp.enable_bucket_ir = True
torch._inductor.config.simplefsdp.enable_reorder_ir = True
torch._inductor.config.simplefsdp.simplefsdp_only = False # False for 2d True for 1d
torch._inductor.config.simplefsdp.peak_memory_offset = 0
torch._inductor.config.simplefsdp.bucketing_type = "auto"
torch._inductor.config.reorder_for_compute_comm_overlap = True
simple_fsdp_autobucketing_reordering_pass = partial(
simple_fsdp_autobucketing_reordering_pass,
configs=simplefsdp_autobucketing_config,
)
torch._inductor.config.reorder_for_compute_comm_overlap_passes = [
simple_fsdp_autobucketing_reordering_pass
]

# Don't use both sets of passes at the same time!
torch._inductor.config.bucket_all_gathers_fx = "none"
torch._inductor.config.bucket_reduce_scatters_fx = "none"
torch._inductor.config.reorder_for_compute_comm_overlap = False
else:
torch._inductor.config.bucket_all_gathers_fx = (
job_config.experimental.bucket_all_gathers_fx
Expand Down
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