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Fix potential dtype issue with ideogram 4. (#14436)

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comfyanonymous 2026-06-12 07:51:12 -07:00 committed by GitHub
parent 822aca1983
commit 02656ea0bb
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1 changed files with 3 additions and 3 deletions
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comfy/ldm/ideogram4/model.py
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@ -106,11 +106,11 @@ class Ideogram4EmbedScalar(nn.Module):
self.mlp_in = operations.Linear(dim, dim, bias=True, dtype=dtype, device=device) self.mlp_in = operations.Linear(dim, dim, bias=True, dtype=dtype, device=device)
self.mlp_out = operations.Linear(dim, dim, bias=True, dtype=dtype, device=device) self.mlp_out = operations.Linear(dim, dim, bias=True, dtype=dtype, device=device)
def forward(self, x): def forward(self, x, dtype):
x = x.to(torch.float32) x = x.to(torch.float32)
scaled = 1e4 * (x - self.range_min) / (self.range_max - self.range_min) scaled = 1e4 * (x - self.range_min) / (self.range_max - self.range_min)
emb = _sinusoidal_embedding(scaled, self.dim) emb = _sinusoidal_embedding(scaled, self.dim)
emb = emb.to(self.mlp_in.weight.dtype) emb = emb.to(dtype)
emb = F.silu(self.mlp_in(emb)) emb = F.silu(self.mlp_in(emb))
return self.mlp_out(emb) return self.mlp_out(emb)
@ -161,7 +161,7 @@ class Ideogram4Transformer(nn.Module):
x = x * output_image_mask x = x * output_image_mask
h = self.input_proj(x) * output_image_mask h = self.input_proj(x) * output_image_mask
t_cond = self.t_embedding(t) t_cond = self.t_embedding(t, dtype=x.dtype)
if t.dim() == 1: if t.dim() == 1:
t_cond = t_cond.unsqueeze(1) t_cond = t_cond.unsqueeze(1)
adaln_input = F.silu(self.adaln_proj(t_cond)) adaln_input = F.silu(self.adaln_proj(t_cond))