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Merge 27d11db345 into 5ac3b26a7d

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envy-ai 2025-12-14 07:26:09 -06:00 committed by GitHub
commit 9adc834f79
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4 changed files with 11 additions and 4 deletions
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12
comfy/text_encoders/hidream.py
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@ -5,6 +5,7 @@ from comfy import sdxl_clip
import comfy.model_management import comfy.model_management
import torch import torch
import logging import logging
import folder_paths
class HiDreamTokenizer: class HiDreamTokenizer:
@ -91,6 +92,8 @@ class HiDreamTEModel(torch.nn.Module):
token_weight_pairs_llama = token_weight_pairs["llama"] token_weight_pairs_llama = token_weight_pairs["llama"]
lg_out = None lg_out = None
pooled = None pooled = None
t5_out = None
ll_out = None
extra = {} extra = {}
if len(token_weight_pairs_g) > 0 or len(token_weight_pairs_l) > 0: if len(token_weight_pairs_g) > 0 or len(token_weight_pairs_l) > 0:
@ -104,7 +107,8 @@ class HiDreamTEModel(torch.nn.Module):
else: else:
g_pooled = torch.zeros((1, 1280), device=comfy.model_management.intermediate_device()) g_pooled = torch.zeros((1, 1280), device=comfy.model_management.intermediate_device())
pooled = torch.cat((l_pooled, g_pooled), dim=-1) if self.clip_g is not None and self.clip_l is not None:
pooled = torch.cat((l_pooled, g_pooled), dim=-1)
if self.t5xxl is not None: if self.t5xxl is not None:
t5_output = self.t5xxl.encode_token_weights(token_weight_pairs_t5) t5_output = self.t5xxl.encode_token_weights(token_weight_pairs_t5)
@ -120,13 +124,15 @@ class HiDreamTEModel(torch.nn.Module):
ll_out = None ll_out = None
if t5_out is None: if t5_out is None:
t5_out = torch.zeros((1, 128, 4096), device=comfy.model_management.intermediate_device()) t5_path = folder_paths.get_full_path_or_raise("hidream_empty_latents", "t5_blank.pt")
t5_out = torch.load(t5_path, map_location=comfy.model_management.intermediate_device())
if ll_out is None: if ll_out is None:
ll_out = torch.zeros((1, 32, 1, 4096), device=comfy.model_management.intermediate_device()) ll_out = torch.zeros((1, 32, 1, 4096), device=comfy.model_management.intermediate_device())
if pooled is None: if pooled is None:
pooled = torch.zeros((1, 768 + 1280), device=comfy.model_management.intermediate_device()) pooled_path = folder_paths.get_full_path_or_raise("hidream_empty_latents", "pooled_blank.pt")
pooled = torch.load(pooled_path, map_location=comfy.model_management.intermediate_device())
extra["conditioning_llama3"] = ll_out extra["conditioning_llama3"] = ll_out
return t5_out, pooled, extra return t5_out, pooled, extra

1
folder_paths.py
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@ -47,6 +47,7 @@ folder_names_and_paths["hypernetworks"] = ([os.path.join(models_dir, "hypernetwo
folder_names_and_paths["photomaker"] = ([os.path.join(models_dir, "photomaker")], supported_pt_extensions) folder_names_and_paths["photomaker"] = ([os.path.join(models_dir, "photomaker")], supported_pt_extensions)
folder_names_and_paths["classifiers"] = ([os.path.join(models_dir, "classifiers")], {""}) folder_names_and_paths["classifiers"] = ([os.path.join(models_dir, "classifiers")], {""})
folder_names_and_paths["hidream_empty_latents"] = ([os.path.join(models_dir, "hidream_empty_latents")], supported_pt_extensions)
folder_names_and_paths["model_patches"] = ([os.path.join(models_dir, "model_patches")], supported_pt_extensions) folder_names_and_paths["model_patches"] = ([os.path.join(models_dir, "model_patches")], supported_pt_extensions)

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models/hidream_empty_latents/pooled_blank.pt Normal file
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models/hidream_empty_latents/t5_blank.pt Normal file
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