ColossalAI/tests/test_fx/test_meta_info_prop.py

41 lines
1.3 KiB
Python

import torch
from torch.fx import symbolic_trace
from colossalai.fx._compatibility import is_compatible_with_meta
from colossalai.fx.passes.meta_info_prop import MetaInfoProp, TensorMetadata
from colossalai.testing import clear_cache_before_run
if is_compatible_with_meta():
from colossalai.fx.profiler import MetaTensor
BATCH_SIZE = 2
DIM_IN = 4
DIM_OUT = 16
def meta_check(meta_info_spec: TensorMetadata, orig_tensor: torch.Tensor):
assert meta_info_spec.shape == orig_tensor.shape
assert meta_info_spec.dtype == orig_tensor.dtype
assert meta_info_spec.stride == orig_tensor.stride()
assert meta_info_spec.numel == orig_tensor.numel()
@clear_cache_before_run()
def test_meta_info_prop():
model = torch.nn.Linear(DIM_IN, DIM_OUT)
input_sample = torch.rand(BATCH_SIZE, DIM_IN, device='meta')
if is_compatible_with_meta():
input_sample = MetaTensor(input_sample, fake_device='cpu')
orig_output = model(input_sample)
gm = symbolic_trace(model)
MetaInfoProp(gm).run(input_sample)
for node in gm.graph.nodes:
if node.op == 'placeholder':
meta_check(node.meta['tensor_meta'], input_sample)
if node.op == 'output':
meta_check(node.meta['tensor_meta'], orig_output)
if __name__ == '__main__':
test_meta_info_prop()