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Merge 27d11db345 into 5ac3b26a7d
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9adc834f79
@ -5,6 +5,7 @@ from comfy import sdxl_clip
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import comfy.model_management
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import torch
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import logging
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import folder_paths
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class HiDreamTokenizer:
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@ -91,6 +92,8 @@ class HiDreamTEModel(torch.nn.Module):
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token_weight_pairs_llama = token_weight_pairs["llama"]
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lg_out = None
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pooled = None
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t5_out = None
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ll_out = None
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extra = {}
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if len(token_weight_pairs_g) > 0 or len(token_weight_pairs_l) > 0:
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@ -104,8 +107,9 @@ class HiDreamTEModel(torch.nn.Module):
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else:
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g_pooled = torch.zeros((1, 1280), device=comfy.model_management.intermediate_device())
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pooled = torch.cat((l_pooled, g_pooled), dim=-1)
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if self.clip_g is not None and self.clip_l is not None:
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pooled = torch.cat((l_pooled, g_pooled), dim=-1)
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if self.t5xxl is not None:
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t5_output = self.t5xxl.encode_token_weights(token_weight_pairs_t5)
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t5_out, t5_pooled = t5_output[:2]
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@ -120,13 +124,15 @@ class HiDreamTEModel(torch.nn.Module):
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ll_out = None
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if t5_out is None:
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t5_out = torch.zeros((1, 128, 4096), device=comfy.model_management.intermediate_device())
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t5_path = folder_paths.get_full_path_or_raise("hidream_empty_latents", "t5_blank.pt")
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t5_out = torch.load(t5_path, map_location=comfy.model_management.intermediate_device())
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if ll_out is None:
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ll_out = torch.zeros((1, 32, 1, 4096), device=comfy.model_management.intermediate_device())
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if pooled is None:
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pooled = torch.zeros((1, 768 + 1280), device=comfy.model_management.intermediate_device())
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pooled_path = folder_paths.get_full_path_or_raise("hidream_empty_latents", "pooled_blank.pt")
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pooled = torch.load(pooled_path, map_location=comfy.model_management.intermediate_device())
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extra["conditioning_llama3"] = ll_out
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return t5_out, pooled, extra
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@ -47,6 +47,7 @@ folder_names_and_paths["hypernetworks"] = ([os.path.join(models_dir, "hypernetwo
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folder_names_and_paths["photomaker"] = ([os.path.join(models_dir, "photomaker")], supported_pt_extensions)
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folder_names_and_paths["classifiers"] = ([os.path.join(models_dir, "classifiers")], {""})
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folder_names_and_paths["hidream_empty_latents"] = ([os.path.join(models_dir, "hidream_empty_latents")], supported_pt_extensions)
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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
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models/hidream_empty_latents/pooled_blank.pt
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models/hidream_empty_latents/t5_blank.pt
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models/hidream_empty_latents/t5_blank.pt
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