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341b12f9bf
* update (#57) * update * update datautil * add VBench prompt * update eval * update eval * update intepolation * add vbench eval * Dev/sdedit implementation (#56) * Update utils.py * update * update * update --------- Co-authored-by: YuKun Zhou <90625606+1zeryu@users.noreply.github.com>
35 lines
1 KiB
Python
35 lines
1 KiB
Python
import torch
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from colossalai.accelerator import get_accelerator
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from colossalai.utils import get_current_device
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from rotary_embedding_torch import RotaryEmbedding
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from opensora.models.layers.blocks import Attention
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# B, S, H = 7488, 1, 1152
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# B, S, H = 32, 234, 1152
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B, S, H = 128, 32, 1152
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N, D = 16, 72
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def run_attn(enable_flashattn: bool):
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get_accelerator().reset_peak_memory_stats()
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rope = RotaryEmbedding(D).to(device=get_current_device(), dtype=torch.bfloat16)
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attn = Attention(
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H,
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N,
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qkv_bias=True,
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rope=rope.rotate_queries_or_keys,
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enable_flashattn=enable_flashattn,
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).to(device=get_current_device(), dtype=torch.bfloat16)
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x = torch.randn(B, S, H, device=get_current_device(), dtype=torch.bfloat16).requires_grad_()
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y = attn(x)
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y.mean().backward()
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print(f"Peak memory: {get_accelerator().max_memory_allocated() / 1024**2:.2f} MB")
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if __name__ == "__main__":
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print("Use flashattn")
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run_attn(True)
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print("No flashattn")
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run_attn(False)
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