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Skip layer guidance now works on hydit model.
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@ -287,7 +287,7 @@ class HunYuanDiT(nn.Module):
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style=None,
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return_dict=False,
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control=None,
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transformer_options=None,
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transformer_options={},
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):
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"""
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Forward pass of the encoder.
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@ -315,8 +315,7 @@ class HunYuanDiT(nn.Module):
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return_dict: bool
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Whether to return a dictionary.
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"""
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#import pdb
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#pdb.set_trace()
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patches_replace = transformer_options.get("patches_replace", {})
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encoder_hidden_states = context
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text_states = encoder_hidden_states # 2,77,1024
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text_states_t5 = encoder_hidden_states_t5 # 2,256,2048
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@ -364,6 +363,8 @@ class HunYuanDiT(nn.Module):
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# Concatenate all extra vectors
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c = t + self.extra_embedder(extra_vec) # [B, D]
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blocks_replace = patches_replace.get("dit", {})
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controls = None
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if control:
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controls = control.get("output", None)
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@ -375,9 +376,20 @@ class HunYuanDiT(nn.Module):
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skip = skips.pop() + controls.pop().to(dtype=x.dtype)
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else:
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skip = skips.pop()
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x = block(x, c, text_states, freqs_cis_img, skip) # (N, L, D)
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else:
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x = block(x, c, text_states, freqs_cis_img) # (N, L, D)
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skip = None
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if ("double_block", layer) in blocks_replace:
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def block_wrap(args):
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out = {}
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out["img"] = block(args["img"], args["vec"], args["txt"], args["pe"], args["skip"])
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return out
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out = blocks_replace[("double_block", layer)]({"img": x, "txt": text_states, "vec": c, "pe": freqs_cis_img, "skip": skip}, {"original_block": block_wrap})
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x = out["img"]
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else:
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x = block(x, c, text_states, freqs_cis_img, skip) # (N, L, D)
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if layer < (self.depth // 2 - 1):
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skips.append(x)
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