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[autoparallel]integrate auto parallel feature with new tracer (#3408)

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* [autoparallel] integrate new analyzer in module level

* unify the profiling method

* polish

* fix no codegen bug

* fix pass bug

* fix liveness test

* polish
This commit is contained in:
YuliangLiu0306
2023-04-04 17:40:45 +08:00
committed by GitHub
parent 573af84184
commit ffcdbf0f65
46 changed files with 396 additions and 470 deletions
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10
colossalai/auto_parallel/meta_profiler/meta_registry/tensor.py
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@@ -2,9 +2,9 @@ from typing import Callable, List, Tuple
import torch
from colossalai._analyzer._subclasses.flop_tensor import flop_mapping
from colossalai._analyzer.fx.node_util import compute_size_in_bytes
from colossalai.auto_parallel.tensor_shard.sharding_strategy import MemoryCost, OperationDataType, TrainCycleItem
from colossalai.fx.profiler.memory_utils import activation_size
from colossalai.fx.profiler.opcount import flop_mapping
from ..registry import meta_register
@@ -35,11 +35,11 @@ def tensor_related_metainfo(bwd_mem_out_factor: float = 1, bwd_mem_tmp_factor: f
# memory costs
# NOTE: currently in SPMD solver we always believe that there will be a new tensor created in forward
fwd_mem_cost = MemoryCost(activation=activation_size(outputs) * 2, parameter=0, temp=0, buffer=0)
fwd_mem_cost = MemoryCost(activation=compute_size_in_bytes(outputs) * 2, parameter=0, temp=0, buffer=0)
bwd_mem_cost = MemoryCost(activation=activation_size(outputs) * bwd_mem_out_factor,
bwd_mem_cost = MemoryCost(activation=compute_size_in_bytes(outputs) * bwd_mem_out_factor,
parameter=0,
temp=activation_size(outputs) * bwd_mem_tmp_factor,
temp=compute_size_in_bytes(outputs) * bwd_mem_tmp_factor,
buffer=0)
total_mem_cost = MemoryCost(activation=fwd_mem_cost.activation + bwd_mem_cost.activation,