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[fx] added apex normalization to patched modules #1300

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Merged
YuliangLiu0306 merged 2 commits into from
Jul 14, 2022
Merged

[fx] added apex normalization to patched modules #1300

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12a9836
[fx] added apex normalization to patched modules
FrankLeeeee Jul 13, 2022
d51e6b0
remove unused imports
FrankLeeeee Jul 13, 2022
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12 changes: 11 additions & 1 deletion colossalai/fx/tracer/meta_patch/patched_module/normalization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,4 +17,14 @@ def torch_nn_normalize(self, input):
assert input.dim() == 5

# normalization maintain the same shape as the input
return input.clone()
return input.clone()


try:
import apex
meta_patched_module.register(apex.normalization.FusedLayerNorm)(torch_nn_normalize)
meta_patched_module.register(apex.normalization.FusedRMSNorm)(torch_nn_normalize)
meta_patched_module.register(apex.normalization.MixedFusedLayerNorm)(torch_nn_normalize)
meta_patched_module.register(apex.normalization.MixedFusedRMSNorm)(torch_nn_normalize)
except ImportError:
pass
9 changes: 0 additions & 9 deletions tests/test_fx/test_pipeline/test_hf_model/test_t5.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,15 +2,6 @@
import transformers
import torch
from hf_utils import split_model_and_compare_output
from colossalai.fx.tracer.meta_patch import meta_patched_module
try:
import apex

@meta_patched_module.register(apex.normalization.FusedRMSNorm)
def apex_fused_layernorm(self, input):
return torch.empty(input.shape, device='meta')
except ImportError:
pass

BATCH_SIZE = 1
SEQ_LENGHT = 16
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10 changes: 0 additions & 10 deletions tests/test_fx/test_tracer/test_hf_model/test_hf_t5.py
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Original file line number Diff line number Diff line change
@@ -1,18 +1,8 @@
import pytest
import transformers
import torch
from colossalai.fx.tracer.meta_patch import meta_patched_module
from utils import trace_model_and_compare_output

try:
import apex

@meta_patched_module.register(apex.normalization.FusedRMSNorm)
def apex_fused_layernorm(self, input):
return torch.empty(input.shape, device='meta')
except ImportError:
pass

BATCH_SIZE = 1
SEQ_LENGHT = 16

Expand Down