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Add workaround for MPS gather crash #15

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merged 1 commit into from
Apr 3, 2023
Merged

Add workaround for MPS gather crash #15

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28 changes: 20 additions & 8 deletions tomesd/merge.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,13 @@ def do_nothing(x: torch.Tensor, mode:str=None):
return x


def mps_gather_workaround(input, dim, index):
if input.shape[-1] == 1:
return torch.gather(input.unsqueeze(-1), dim - 1 if dim < 0 else dim, index.unsqueeze(-1)).squeeze(-1)
else:
return torch.gather(input, dim, index)


def bipartite_soft_matching_random2d(metric: torch.Tensor,
w: int, h: int, sx: int, sy: int, r: int,
no_rand: bool = False) -> Tuple[Callable, Callable]:
Expand All @@ -26,6 +33,11 @@ def bipartite_soft_matching_random2d(metric: torch.Tensor,

if r <= 0:
return do_nothing, do_nothing

if metric.device.type == 'mps':
gather = mps_gather_workaround
else:
gather = torch.gather

with torch.no_grad():

Expand Down Expand Up @@ -62,8 +74,8 @@ def bipartite_soft_matching_random2d(metric: torch.Tensor,

def split(x):
C = x.shape[-1]
src = x.gather(dim=1, index=a_idx.expand(B, N - num_dst, C))
dst = x.gather(dim=1, index=b_idx.expand(B, num_dst, C))
src = gather(x, dim=1, index=a_idx.expand(B, N - num_dst, C))
dst = gather(x, dim=1, index=b_idx.expand(B, num_dst, C))
return src, dst

# Cosine similarity between A and B
Expand All @@ -80,14 +92,14 @@ def split(x):

unm_idx = edge_idx[..., r:, :] # Unmerged Tokens
src_idx = edge_idx[..., :r, :] # Merged Tokens
dst_idx = node_idx[..., None].gather(dim=-2, index=src_idx)
dst_idx = gather(node_idx[..., None], dim=-2, index=src_idx)

def merge(x: torch.Tensor, mode="mean") -> torch.Tensor:
src, dst = split(x)
n, t1, c = src.shape

unm = src.gather(dim=-2, index=unm_idx.expand(n, t1 - r, c))
src = src.gather(dim=-2, index=src_idx.expand(n, r, c))
unm = gather(src, dim=-2, index=unm_idx.expand(n, t1 - r, c))
src = gather(src, dim=-2, index=src_idx.expand(n, r, c))
dst = dst.scatter_reduce(-2, dst_idx.expand(n, r, c), src, reduce=mode)

return torch.cat([unm, dst], dim=1)
Expand All @@ -97,13 +109,13 @@ def unmerge(x: torch.Tensor) -> torch.Tensor:
unm, dst = x[..., :unm_len, :], x[..., unm_len:, :]
_, _, c = unm.shape

src = dst.gather(dim=-2, index=dst_idx.expand(B, r, c))
src = gather(dst, dim=-2, index=dst_idx.expand(B, r, c))

# Combine back to the original shape
out = torch.zeros(B, N, c, device=x.device, dtype=x.dtype)
out.scatter_(dim=-2, index=b_idx.expand(B, num_dst, c), src=dst)
out.scatter_(dim=-2, index=a_idx.expand(B, a_idx.shape[1], 1).gather(dim=1, index=unm_idx).expand(B, unm_len, c), src=unm)
out.scatter_(dim=-2, index=a_idx.expand(B, a_idx.shape[1], 1).gather(dim=1, index=src_idx).expand(B, r, c), src=src)
out.scatter_(dim=-2, index=gather(a_idx.expand(B, a_idx.shape[1], 1), dim=1, index=unm_idx).expand(B, unm_len, c), src=unm)
out.scatter_(dim=-2, index=gather(a_idx.expand(B, a_idx.shape[1], 1), dim=1, index=src_idx).expand(B, r, c), src=src)

return out

Expand Down