mirror of https://github.com/hpcaitech/ColossalAI
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
63 lines
1.6 KiB
63 lines
1.6 KiB
import torch
|
|
from torch.fx import GraphModule
|
|
from torch.utils.checkpoint import checkpoint
|
|
|
|
from colossalai.fx import ColoTracer
|
|
from colossalai.testing import clear_cache_before_run
|
|
|
|
|
|
class MLP(torch.nn.Module):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.linear1 = torch.nn.Linear(4, 4)
|
|
self.linear2 = torch.nn.Linear(4, 4)
|
|
|
|
def forward(self, x):
|
|
x = self.linear1(x)
|
|
x = self.linear2(x)
|
|
return x
|
|
|
|
|
|
# Simple module for demonstration
|
|
class MyModule(torch.nn.Module):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.mlp_1 = MLP()
|
|
self.mlp_2 = MLP()
|
|
self.output = torch.nn.Linear(4, 4)
|
|
|
|
def forward(self, x):
|
|
x = checkpoint(self.mlp_1, x)
|
|
x = checkpoint(self.mlp_2, x)
|
|
x = self.output(x)
|
|
return x
|
|
|
|
|
|
@clear_cache_before_run()
|
|
def test_activation_checkpoint_annotation():
|
|
module = MyModule()
|
|
|
|
# test tracing with activation checkpoint
|
|
tracer = ColoTracer(trace_act_ckpt=True)
|
|
graph = tracer.trace(module)
|
|
gm = GraphModule(module, graph)
|
|
|
|
for node in gm.graph.nodes:
|
|
if node.name in ["mlp_1_linear1", "mlp_1_linear2"]:
|
|
assert node.meta.get("activation_checkpoint", -1) == 0
|
|
|
|
for node in gm.graph.nodes:
|
|
if node.name in ["mlp_2_linear1", "mlp_2_linear2"]:
|
|
assert node.meta.get("activation_checkpoint", -1) == 1
|
|
|
|
tracer = ColoTracer(trace_act_ckpt=False)
|
|
graph = tracer.trace(module)
|
|
gm = GraphModule(module, graph)
|
|
|
|
for node in gm.graph.nodes:
|
|
assert not hasattr(node, "activation_checkpoint")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
test_activation_checkpoint_annotation()
|