51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
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import ixformer._C as ops
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import torch
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__all__ = ["matmul", "ref_matmul"]
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def ref_matmul(input, other, *, transa, transb, alpha):
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if transa:
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dims = list(range(input.ndim))
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dims[-1], dims[-2] = dims[-2], dims[-1]
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input = input.permute(*dims).contiguous()
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if transb:
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dims = list(range(other.ndim))
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dims[-1], dims[-2] = dims[-2], dims[-1]
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other = other.permute(*dims).contiguous()
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return alpha * torch.matmul(input, other)
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def matmul(
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input: torch.Tensor,
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other: torch.Tensor,
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*,
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transa: bool = False,
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transb: bool = False,
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alpha: float = 1.0,
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) -> torch.Tensor:
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"""
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Args:
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input: (...,m,k) or (...,k,m) torch.half
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当transa为False shape : [...,m,k], 当transa为True shape : [...,k,m]
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other: (...,k,n) or (...,n,k) torch.half
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当transa为False shape : [...,m,k], 当transa为True shape : [...,k,m]
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transa: bool
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transb: bool
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alpha: float
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Returns:
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Tensor: (..., m, n) torch.half
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"""
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if not input.is_contiguous():
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input = input.contiguous()
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if not other.is_contiguous():
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if not other.transpose(-2, -1).is_contiguous():
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other = other.contiguous()
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return ops.train.matmul(
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input, other, transa=transa, transb=transb, alpha=alpha, beta=0.0
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)
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