[BUG] [Shardformer]: Error in blip2 testing with half precision

[insujang]

🐛 Describe the bug

1. It seems blip2 testing doesn't work correctly at all if model is half precision (torch.float16).
2. With bfloat16, colossalai.shardformer.layer.FusedLayerNorm doesn't seem to work correctly.

https://github.com/hpcaitech/ColossalAI/blob/main/tests/test_shardformer/test_model/test_shard_blip2.py
This test file passes as it is.

But if I change dtype to torch.float16:

ColossalAI/tests/test_shardformer/test_model/test_shard_blip2.py

Line 92 in 89049b0

dtype=torch.float,

It fails:

E         File "test_shard_blip2.py", line 28, in check_forward_backward
E           assert_hf_output_close(org_output, shard_output, ignore_keys=["past_key_values"])
E         File "colossalai/testing/comparison.py", line 125, in assert_hf_output_close
E           assert_hf_output_close(
E         File "colossalai/testing/comparison.py", line 149, in assert_hf_output_close
E           assert_close(
E         File "/opt/conda/lib/python3.10/site-packages/torch/testing/_comparison.py", line 1520, in assert_close
E           raise error_metas[0].to_error(msg)
E       AssertionError: Tensor-likes are not close!
E       
E       Mismatched elements: 5947392 / 5947392 (100.0%)
E       Greatest absolute difference: nan at index (0, 0) (up to 1e-06 allowed)
E       Greatest relative difference: nan at index (0, 0) (up to 1e-05 allowed)

With dtype=torch.bfloat16 and without enable_fused_normalization it passes, but if I enable enable_fused_normalization, it fails again:

E         File "test_shard_blip2.py", line 28, in check_forward_backward
E           assert_hf_output_close(org_output, shard_output, ignore_keys=["past_key_values"])
E         File "/colossalai/testing/comparison.py", line 125, in assert_hf_output_close
E           assert_hf_output_close(
E         File "/colossalai/testing/comparison.py", line 125, in assert_hf_output_close
E           assert_hf_output_close(
E         File "/colossalai/testing/comparison.py", line 149, in assert_hf_output_close
E           assert_close(
E         File "/opt/conda/lib/python3.10/site-packages/torch/testing/_comparison.py", line 1520, in assert_close
E           raise error_metas[0].to_error(msg)
E       AssertionError: Tensor-likes are not close!
E       
E       Mismatched elements: 24271 / 2161696 (1.1%)
E       Greatest absolute difference: 0.0078125 at index (0, 3, 47) (up to 1e-05 allowed)
E       Greatest relative difference: 169.0 at index (0, 3, 47325) (up to 1e-05 allowed)

Environment

torch 2.2.1 / CUDA 12.1
colossalai 0.3.6
transformesr 4.36.0

[insujang]

I am not sure if it is a bug or an unavoidable error due to lower precision and it was intended to test only on fp32. Would appreciate it if you could share some insights about it. Thanks.