diff --git "a/diffsynth/models/sd3_text_encoder.py" "b/diffsynth/models/sd3_text_encoder.py" new file mode 100644--- /dev/null +++ "b/diffsynth/models/sd3_text_encoder.py" @@ -0,0 +1,1104 @@ +import torch +from transformers import T5EncoderModel, T5Config +from .sd_text_encoder import SDTextEncoder +from .sdxl_text_encoder import SDXLTextEncoder2, SDXLTextEncoder2StateDictConverter + + +class SD3TextEncoder1(SDTextEncoder): + def __init__(self, vocab_size=49408): + super().__init__(vocab_size=vocab_size) + + def forward(self, input_ids, clip_skip=2): + embeds = self.token_embedding(input_ids) + self.position_embeds + attn_mask = self.attn_mask.to(device=embeds.device, dtype=embeds.dtype) + for encoder_id, encoder in enumerate(self.encoders): + embeds = encoder(embeds, attn_mask=attn_mask) + if encoder_id + clip_skip == len(self.encoders): + hidden_states = embeds + embeds = self.final_layer_norm(embeds) + pooled_embeds = embeds[torch.arange(embeds.shape[0]), input_ids.to(dtype=torch.int).argmax(dim=-1)] + return pooled_embeds, hidden_states + + def state_dict_converter(self): + return SD3TextEncoder1StateDictConverter() + + + +class SD3TextEncoder2(SDXLTextEncoder2): + def __init__(self): + super().__init__() + + def state_dict_converter(self): + return SD3TextEncoder2StateDictConverter() + + +class SD3TextEncoder3(T5EncoderModel): + def __init__(self): + config = T5Config( + _name_or_path = ".", + architectures = ["T5EncoderModel"], + classifier_dropout = 0.0, + d_ff = 10240, + d_kv = 64, + d_model = 4096, + decoder_start_token_id = 0, + dense_act_fn = "gelu_new", + dropout_rate = 0.1, + eos_token_id = 1, + feed_forward_proj = "gated-gelu", + initializer_factor = 1.0, + is_encoder_decoder = True, + is_gated_act = True, + layer_norm_epsilon = 1e-06, + model_type = "t5", + num_decoder_layers = 24, + num_heads = 64, + num_layers = 24, + output_past = True, + pad_token_id = 0, + relative_attention_max_distance = 128, + relative_attention_num_buckets = 32, + tie_word_embeddings = False, + torch_dtype = torch.float16, + transformers_version = "4.41.2", + use_cache = True, + vocab_size = 32128 + ) + super().__init__(config) + self.eval() + + def forward(self, input_ids): + outputs = super().forward(input_ids=input_ids) + prompt_emb = outputs.last_hidden_state + return prompt_emb + + def state_dict_converter(self): + return SD3TextEncoder3StateDictConverter() + + + +class SD3TextEncoder1StateDictConverter: + def __init__(self): + pass + + def from_diffusers(self, state_dict): + rename_dict = { + "text_model.embeddings.token_embedding.weight": "token_embedding.weight", + "text_model.embeddings.position_embedding.weight": "position_embeds", + "text_model.final_layer_norm.weight": "final_layer_norm.weight", + "text_model.final_layer_norm.bias": "final_layer_norm.bias", + } + attn_rename_dict = { + "self_attn.q_proj": "attn.to_q", + "self_attn.k_proj": "attn.to_k", + "self_attn.v_proj": "attn.to_v", + "self_attn.out_proj": "attn.to_out", + "layer_norm1": "layer_norm1", + "layer_norm2": "layer_norm2", + "mlp.fc1": "fc1", + "mlp.fc2": "fc2", + } + state_dict_ = {} + for name in state_dict: + if name in rename_dict: + param = state_dict[name] + if name == "text_model.embeddings.position_embedding.weight": + param = param.reshape((1, param.shape[0], param.shape[1])) + state_dict_[rename_dict[name]] = param + elif name.startswith("text_model.encoder.layers."): + param = state_dict[name] + names = name.split(".") + layer_id, layer_type, tail = names[3], ".".join(names[4:-1]), names[-1] + name_ = ".".join(["encoders", layer_id, attn_rename_dict[layer_type], tail]) + state_dict_[name_] = param + return state_dict_ + + def from_civitai(self, state_dict): + rename_dict = { + "text_encoders.clip_l.transformer.text_model.embeddings.position_embedding.weight": "position_embeds", + "text_encoders.clip_l.transformer.text_model.embeddings.token_embedding.weight": "token_embedding.weight", + 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"text_encoders.clip_l.transformer.text_model.encoder.layers.9.mlp.fc1.weight": "encoders.9.fc1.weight", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.mlp.fc2.bias": "encoders.9.fc2.bias", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.mlp.fc2.weight": "encoders.9.fc2.weight", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.self_attn.k_proj.bias": "encoders.9.attn.to_k.bias", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.self_attn.k_proj.weight": "encoders.9.attn.to_k.weight", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.self_attn.out_proj.bias": "encoders.9.attn.to_out.bias", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.self_attn.out_proj.weight": "encoders.9.attn.to_out.weight", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.self_attn.q_proj.bias": "encoders.9.attn.to_q.bias", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.self_attn.q_proj.weight": "encoders.9.attn.to_q.weight", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.self_attn.v_proj.bias": "encoders.9.attn.to_v.bias", + "text_encoders.clip_l.transformer.text_model.encoder.layers.9.self_attn.v_proj.weight": "encoders.9.attn.to_v.weight", + "text_encoders.clip_l.transformer.text_model.final_layer_norm.bias": "final_layer_norm.bias", + "text_encoders.clip_l.transformer.text_model.final_layer_norm.weight": "final_layer_norm.weight", + } + state_dict_ = {} + for name in state_dict: + if name in rename_dict: + param = state_dict[name] + if name == "text_encoders.clip_l.transformer.text_model.embeddings.position_embedding.weight": + param = param.reshape((1, param.shape[0], param.shape[1])) + state_dict_[rename_dict[name]] = param + return state_dict_ + + + +class SD3TextEncoder2StateDictConverter(SDXLTextEncoder2StateDictConverter): + def __init__(self): + pass + + def from_diffusers(self, state_dict): + return super().from_diffusers(state_dict) + + def from_civitai(self, state_dict): + rename_dict = { + "text_encoders.clip_g.transformer.text_model.embeddings.position_embedding.weight": "position_embeds", + "text_encoders.clip_g.transformer.text_model.embeddings.token_embedding.weight": "token_embedding.weight", + "text_encoders.clip_g.transformer.text_model.encoder.layers.0.layer_norm1.bias": "encoders.0.layer_norm1.bias", + "text_encoders.clip_g.transformer.text_model.encoder.layers.0.layer_norm1.weight": "encoders.0.layer_norm1.weight", + "text_encoders.clip_g.transformer.text_model.encoder.layers.0.layer_norm2.bias": "encoders.0.layer_norm2.bias", + "text_encoders.clip_g.transformer.text_model.encoder.layers.0.layer_norm2.weight": "encoders.0.layer_norm2.weight", + "text_encoders.clip_g.transformer.text_model.encoder.layers.0.mlp.fc1.bias": "encoders.0.fc1.bias", + "text_encoders.clip_g.transformer.text_model.encoder.layers.0.mlp.fc1.weight": 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"text_encoders.clip_g.transformer.text_model.encoder.layers.9.self_attn.q_proj.weight": "encoders.9.attn.to_q.weight", + "text_encoders.clip_g.transformer.text_model.encoder.layers.9.self_attn.v_proj.bias": "encoders.9.attn.to_v.bias", + "text_encoders.clip_g.transformer.text_model.encoder.layers.9.self_attn.v_proj.weight": "encoders.9.attn.to_v.weight", + "text_encoders.clip_g.transformer.text_model.final_layer_norm.bias": "final_layer_norm.bias", + "text_encoders.clip_g.transformer.text_model.final_layer_norm.weight": "final_layer_norm.weight", + "text_encoders.clip_g.transformer.text_projection.weight": "text_projection.weight", + } + state_dict_ = {} + for name in state_dict: + if name in rename_dict: + param = state_dict[name] + if name == "text_encoders.clip_g.transformer.text_model.embeddings.position_embedding.weight": + param = param.reshape((1, param.shape[0], param.shape[1])) + state_dict_[rename_dict[name]] = param + return state_dict_ + + + +class SD3TextEncoder3StateDictConverter(): + def __init__(self): + pass + + def from_diffusers(self, state_dict): + state_dict_ = state_dict + return state_dict_ + + def from_civitai(self, state_dict): + prefix = "text_encoders.t5xxl.transformer." + state_dict_ = {name[len(prefix):]: param for name, param in state_dict.items() if name.startswith(prefix)} + if len(state_dict_) > 0: + return self.from_diffusers(state_dict_) + name_list = [ + "encoder.block.0.layer.0.SelfAttention.k.weight", + "encoder.block.0.layer.0.SelfAttention.o.weight", + "encoder.block.0.layer.0.SelfAttention.q.weight", + "encoder.block.0.layer.0.SelfAttention.relative_attention_bias.weight", + "encoder.block.0.layer.0.SelfAttention.v.weight", + "encoder.block.0.layer.0.layer_norm.weight", + "encoder.block.0.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.0.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.0.layer.1.DenseReluDense.wo.weight", + "encoder.block.0.layer.1.layer_norm.weight", + "encoder.block.1.layer.0.SelfAttention.k.weight", + "encoder.block.1.layer.0.SelfAttention.o.weight", + "encoder.block.1.layer.0.SelfAttention.q.weight", + "encoder.block.1.layer.0.SelfAttention.v.weight", + "encoder.block.1.layer.0.layer_norm.weight", + "encoder.block.1.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.1.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.1.layer.1.DenseReluDense.wo.weight", + "encoder.block.1.layer.1.layer_norm.weight", + "encoder.block.10.layer.0.SelfAttention.k.weight", + "encoder.block.10.layer.0.SelfAttention.o.weight", + "encoder.block.10.layer.0.SelfAttention.q.weight", + "encoder.block.10.layer.0.SelfAttention.v.weight", + "encoder.block.10.layer.0.layer_norm.weight", + "encoder.block.10.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.10.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.10.layer.1.DenseReluDense.wo.weight", + "encoder.block.10.layer.1.layer_norm.weight", + "encoder.block.11.layer.0.SelfAttention.k.weight", + "encoder.block.11.layer.0.SelfAttention.o.weight", + "encoder.block.11.layer.0.SelfAttention.q.weight", + "encoder.block.11.layer.0.SelfAttention.v.weight", + "encoder.block.11.layer.0.layer_norm.weight", + "encoder.block.11.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.11.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.11.layer.1.DenseReluDense.wo.weight", + "encoder.block.11.layer.1.layer_norm.weight", + "encoder.block.12.layer.0.SelfAttention.k.weight", + "encoder.block.12.layer.0.SelfAttention.o.weight", + "encoder.block.12.layer.0.SelfAttention.q.weight", + "encoder.block.12.layer.0.SelfAttention.v.weight", + "encoder.block.12.layer.0.layer_norm.weight", + "encoder.block.12.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.12.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.12.layer.1.DenseReluDense.wo.weight", + "encoder.block.12.layer.1.layer_norm.weight", + "encoder.block.13.layer.0.SelfAttention.k.weight", + "encoder.block.13.layer.0.SelfAttention.o.weight", + "encoder.block.13.layer.0.SelfAttention.q.weight", + "encoder.block.13.layer.0.SelfAttention.v.weight", + "encoder.block.13.layer.0.layer_norm.weight", + "encoder.block.13.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.13.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.13.layer.1.DenseReluDense.wo.weight", + "encoder.block.13.layer.1.layer_norm.weight", + "encoder.block.14.layer.0.SelfAttention.k.weight", + "encoder.block.14.layer.0.SelfAttention.o.weight", + "encoder.block.14.layer.0.SelfAttention.q.weight", + "encoder.block.14.layer.0.SelfAttention.v.weight", + "encoder.block.14.layer.0.layer_norm.weight", + "encoder.block.14.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.14.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.14.layer.1.DenseReluDense.wo.weight", + "encoder.block.14.layer.1.layer_norm.weight", + "encoder.block.15.layer.0.SelfAttention.k.weight", + "encoder.block.15.layer.0.SelfAttention.o.weight", + "encoder.block.15.layer.0.SelfAttention.q.weight", + "encoder.block.15.layer.0.SelfAttention.v.weight", + "encoder.block.15.layer.0.layer_norm.weight", + "encoder.block.15.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.15.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.15.layer.1.DenseReluDense.wo.weight", + "encoder.block.15.layer.1.layer_norm.weight", + "encoder.block.16.layer.0.SelfAttention.k.weight", + "encoder.block.16.layer.0.SelfAttention.o.weight", + "encoder.block.16.layer.0.SelfAttention.q.weight", + "encoder.block.16.layer.0.SelfAttention.v.weight", + "encoder.block.16.layer.0.layer_norm.weight", + "encoder.block.16.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.16.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.16.layer.1.DenseReluDense.wo.weight", + "encoder.block.16.layer.1.layer_norm.weight", + "encoder.block.17.layer.0.SelfAttention.k.weight", + "encoder.block.17.layer.0.SelfAttention.o.weight", + "encoder.block.17.layer.0.SelfAttention.q.weight", + "encoder.block.17.layer.0.SelfAttention.v.weight", + "encoder.block.17.layer.0.layer_norm.weight", + "encoder.block.17.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.17.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.17.layer.1.DenseReluDense.wo.weight", + "encoder.block.17.layer.1.layer_norm.weight", + "encoder.block.18.layer.0.SelfAttention.k.weight", + "encoder.block.18.layer.0.SelfAttention.o.weight", + "encoder.block.18.layer.0.SelfAttention.q.weight", + "encoder.block.18.layer.0.SelfAttention.v.weight", + "encoder.block.18.layer.0.layer_norm.weight", + "encoder.block.18.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.18.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.18.layer.1.DenseReluDense.wo.weight", + "encoder.block.18.layer.1.layer_norm.weight", + "encoder.block.19.layer.0.SelfAttention.k.weight", + "encoder.block.19.layer.0.SelfAttention.o.weight", + "encoder.block.19.layer.0.SelfAttention.q.weight", + "encoder.block.19.layer.0.SelfAttention.v.weight", + "encoder.block.19.layer.0.layer_norm.weight", + "encoder.block.19.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.19.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.19.layer.1.DenseReluDense.wo.weight", + "encoder.block.19.layer.1.layer_norm.weight", + "encoder.block.2.layer.0.SelfAttention.k.weight", + "encoder.block.2.layer.0.SelfAttention.o.weight", + "encoder.block.2.layer.0.SelfAttention.q.weight", + "encoder.block.2.layer.0.SelfAttention.v.weight", + "encoder.block.2.layer.0.layer_norm.weight", + "encoder.block.2.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.2.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.2.layer.1.DenseReluDense.wo.weight", + "encoder.block.2.layer.1.layer_norm.weight", + "encoder.block.20.layer.0.SelfAttention.k.weight", + "encoder.block.20.layer.0.SelfAttention.o.weight", + "encoder.block.20.layer.0.SelfAttention.q.weight", + "encoder.block.20.layer.0.SelfAttention.v.weight", + "encoder.block.20.layer.0.layer_norm.weight", + "encoder.block.20.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.20.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.20.layer.1.DenseReluDense.wo.weight", + "encoder.block.20.layer.1.layer_norm.weight", + "encoder.block.21.layer.0.SelfAttention.k.weight", + "encoder.block.21.layer.0.SelfAttention.o.weight", + "encoder.block.21.layer.0.SelfAttention.q.weight", + "encoder.block.21.layer.0.SelfAttention.v.weight", + "encoder.block.21.layer.0.layer_norm.weight", + "encoder.block.21.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.21.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.21.layer.1.DenseReluDense.wo.weight", + "encoder.block.21.layer.1.layer_norm.weight", + "encoder.block.22.layer.0.SelfAttention.k.weight", + "encoder.block.22.layer.0.SelfAttention.o.weight", + "encoder.block.22.layer.0.SelfAttention.q.weight", + "encoder.block.22.layer.0.SelfAttention.v.weight", + "encoder.block.22.layer.0.layer_norm.weight", + "encoder.block.22.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.22.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.22.layer.1.DenseReluDense.wo.weight", + "encoder.block.22.layer.1.layer_norm.weight", + "encoder.block.23.layer.0.SelfAttention.k.weight", + "encoder.block.23.layer.0.SelfAttention.o.weight", + "encoder.block.23.layer.0.SelfAttention.q.weight", + "encoder.block.23.layer.0.SelfAttention.v.weight", + "encoder.block.23.layer.0.layer_norm.weight", + "encoder.block.23.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.23.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.23.layer.1.DenseReluDense.wo.weight", + "encoder.block.23.layer.1.layer_norm.weight", + "encoder.block.3.layer.0.SelfAttention.k.weight", + "encoder.block.3.layer.0.SelfAttention.o.weight", + "encoder.block.3.layer.0.SelfAttention.q.weight", + "encoder.block.3.layer.0.SelfAttention.v.weight", + "encoder.block.3.layer.0.layer_norm.weight", + "encoder.block.3.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.3.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.3.layer.1.DenseReluDense.wo.weight", + "encoder.block.3.layer.1.layer_norm.weight", + "encoder.block.4.layer.0.SelfAttention.k.weight", + "encoder.block.4.layer.0.SelfAttention.o.weight", + "encoder.block.4.layer.0.SelfAttention.q.weight", + "encoder.block.4.layer.0.SelfAttention.v.weight", + "encoder.block.4.layer.0.layer_norm.weight", + "encoder.block.4.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.4.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.4.layer.1.DenseReluDense.wo.weight", + "encoder.block.4.layer.1.layer_norm.weight", + "encoder.block.5.layer.0.SelfAttention.k.weight", + "encoder.block.5.layer.0.SelfAttention.o.weight", + "encoder.block.5.layer.0.SelfAttention.q.weight", + "encoder.block.5.layer.0.SelfAttention.v.weight", + "encoder.block.5.layer.0.layer_norm.weight", + "encoder.block.5.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.5.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.5.layer.1.DenseReluDense.wo.weight", + "encoder.block.5.layer.1.layer_norm.weight", + "encoder.block.6.layer.0.SelfAttention.k.weight", + "encoder.block.6.layer.0.SelfAttention.o.weight", + "encoder.block.6.layer.0.SelfAttention.q.weight", + "encoder.block.6.layer.0.SelfAttention.v.weight", + "encoder.block.6.layer.0.layer_norm.weight", + "encoder.block.6.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.6.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.6.layer.1.DenseReluDense.wo.weight", + "encoder.block.6.layer.1.layer_norm.weight", + "encoder.block.7.layer.0.SelfAttention.k.weight", + "encoder.block.7.layer.0.SelfAttention.o.weight", + "encoder.block.7.layer.0.SelfAttention.q.weight", + "encoder.block.7.layer.0.SelfAttention.v.weight", + "encoder.block.7.layer.0.layer_norm.weight", + "encoder.block.7.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.7.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.7.layer.1.DenseReluDense.wo.weight", + "encoder.block.7.layer.1.layer_norm.weight", + "encoder.block.8.layer.0.SelfAttention.k.weight", + "encoder.block.8.layer.0.SelfAttention.o.weight", + "encoder.block.8.layer.0.SelfAttention.q.weight", + "encoder.block.8.layer.0.SelfAttention.v.weight", + "encoder.block.8.layer.0.layer_norm.weight", + "encoder.block.8.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.8.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.8.layer.1.DenseReluDense.wo.weight", + "encoder.block.8.layer.1.layer_norm.weight", + "encoder.block.9.layer.0.SelfAttention.k.weight", + "encoder.block.9.layer.0.SelfAttention.o.weight", + "encoder.block.9.layer.0.SelfAttention.q.weight", + "encoder.block.9.layer.0.SelfAttention.v.weight", + "encoder.block.9.layer.0.layer_norm.weight", + "encoder.block.9.layer.1.DenseReluDense.wi_0.weight", + "encoder.block.9.layer.1.DenseReluDense.wi_1.weight", + "encoder.block.9.layer.1.DenseReluDense.wo.weight", + "encoder.block.9.layer.1.layer_norm.weight", + "encoder.embed_tokens.weight", + "encoder.final_layer_norm.weight", + "shared.weight", + ] + state_dict_ = {} + for name, param in state_dict.items(): + if name in name_list: + state_dict_[name] = param + return state_dict_ +