| from comfy import sd1_clip | |
| from transformers import T5TokenizerFast | |
| import comfy.t5 | |
| import os | |
| class T5BaseModel(sd1_clip.SDClipModel): | |
| def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None): | |
| textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_config_base.json") | |
| super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.t5.T5, enable_attention_masks=True, zero_out_masked=True) | |
| class T5BaseTokenizer(sd1_clip.SDTokenizer): | |
| def __init__(self, embedding_directory=None): | |
| tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_tokenizer") | |
| super().__init__(tokenizer_path, pad_with_end=False, embedding_size=768, embedding_key='t5base', tokenizer_class=T5TokenizerFast, has_start_token=False, pad_to_max_length=False, max_length=99999999, min_length=128) | |
| class SAT5Tokenizer(sd1_clip.SD1Tokenizer): | |
| def __init__(self, embedding_directory=None): | |
| super().__init__(embedding_directory=embedding_directory, clip_name="t5base", tokenizer=T5BaseTokenizer) | |
| class SAT5Model(sd1_clip.SD1ClipModel): | |
| def __init__(self, device="cpu", dtype=None, **kwargs): | |
| super().__init__(device=device, dtype=dtype, clip_name="t5base", clip_model=T5BaseModel, **kwargs) | |