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| import torch | |
| from .sd_text_encoder import CLIPEncoderLayer | |
| class SDXLTextEncoder(torch.nn.Module): | |
| def __init__(self, embed_dim=768, vocab_size=49408, max_position_embeddings=77, num_encoder_layers=11, encoder_intermediate_size=3072): | |
| super().__init__() | |
| # token_embedding | |
| self.token_embedding = torch.nn.Embedding(vocab_size, embed_dim) | |
| # position_embeds (This is a fixed tensor) | |
| self.position_embeds = torch.nn.Parameter(torch.zeros(1, max_position_embeddings, embed_dim)) | |
| # encoders | |
| self.encoders = torch.nn.ModuleList([CLIPEncoderLayer(embed_dim, encoder_intermediate_size) for _ in range(num_encoder_layers)]) | |
| # attn_mask | |
| self.attn_mask = self.attention_mask(max_position_embeddings) | |
| # The text encoder is different to that in Stable Diffusion 1.x. | |
| # It does not include final_layer_norm. | |
| def attention_mask(self, length): | |
| mask = torch.empty(length, length) | |
| mask.fill_(float("-inf")) | |
| mask.triu_(1) | |
| return mask | |
| def forward(self, input_ids, clip_skip=1): | |
| 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): | |
| break | |
| return embeds | |
| def state_dict_converter(self): | |
| return SDXLTextEncoderStateDictConverter() | |
| class SDXLTextEncoder2(torch.nn.Module): | |
| def __init__(self, embed_dim=1280, vocab_size=49408, max_position_embeddings=77, num_encoder_layers=32, encoder_intermediate_size=5120): | |
| super().__init__() | |
| # token_embedding | |
| self.token_embedding = torch.nn.Embedding(vocab_size, embed_dim) | |
| # position_embeds (This is a fixed tensor) | |
| self.position_embeds = torch.nn.Parameter(torch.zeros(1, max_position_embeddings, embed_dim)) | |
| # encoders | |
| self.encoders = torch.nn.ModuleList([CLIPEncoderLayer(embed_dim, encoder_intermediate_size, num_heads=20, head_dim=64, use_quick_gelu=False) for _ in range(num_encoder_layers)]) | |
| # attn_mask | |
| self.attn_mask = self.attention_mask(max_position_embeddings) | |
| # final_layer_norm | |
| self.final_layer_norm = torch.nn.LayerNorm(embed_dim) | |
| # text_projection | |
| self.text_projection = torch.nn.Linear(embed_dim, embed_dim, bias=False) | |
| def attention_mask(self, length): | |
| mask = torch.empty(length, length) | |
| mask.fill_(float("-inf")) | |
| mask.triu_(1) | |
| return mask | |
| 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)] | |
| pooled_embeds = self.text_projection(pooled_embeds) | |
| return pooled_embeds, hidden_states | |
| def state_dict_converter(self): | |
| return SDXLTextEncoder2StateDictConverter() | |
| class SDXLTextEncoderStateDictConverter: | |
| 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 = { | |
| "conditioner.embedders.0.transformer.text_model.embeddings.position_embedding.weight": "position_embeds", | |
| "conditioner.embedders.0.transformer.text_model.embeddings.token_embedding.weight": "token_embedding.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.layer_norm1.bias": "encoders.0.layer_norm1.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.layer_norm1.weight": "encoders.0.layer_norm1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.layer_norm2.bias": "encoders.0.layer_norm2.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.layer_norm2.weight": "encoders.0.layer_norm2.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.mlp.fc1.bias": "encoders.0.fc1.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.mlp.fc1.weight": "encoders.0.fc1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.mlp.fc2.bias": "encoders.0.fc2.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.mlp.fc2.weight": "encoders.0.fc2.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.self_attn.k_proj.bias": "encoders.0.attn.to_k.bias", | |
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| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.self_attn.out_proj.weight": "encoders.0.attn.to_out.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.0.self_attn.q_proj.bias": "encoders.0.attn.to_q.bias", | |
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| "conditioner.embedders.0.transformer.text_model.encoder.layers.1.layer_norm1.weight": "encoders.1.layer_norm1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.1.layer_norm2.bias": "encoders.1.layer_norm2.bias", | |
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| "conditioner.embedders.0.transformer.text_model.encoder.layers.6.self_attn.k_proj.bias": "encoders.6.attn.to_k.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.6.self_attn.k_proj.weight": "encoders.6.attn.to_k.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.6.self_attn.out_proj.bias": "encoders.6.attn.to_out.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.6.self_attn.out_proj.weight": "encoders.6.attn.to_out.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.6.self_attn.q_proj.bias": "encoders.6.attn.to_q.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.6.self_attn.q_proj.weight": "encoders.6.attn.to_q.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.6.self_attn.v_proj.bias": "encoders.6.attn.to_v.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.6.self_attn.v_proj.weight": "encoders.6.attn.to_v.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.layer_norm1.bias": "encoders.7.layer_norm1.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.layer_norm1.weight": "encoders.7.layer_norm1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.layer_norm2.bias": "encoders.7.layer_norm2.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.layer_norm2.weight": "encoders.7.layer_norm2.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.mlp.fc1.bias": "encoders.7.fc1.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.mlp.fc1.weight": "encoders.7.fc1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.mlp.fc2.bias": "encoders.7.fc2.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.mlp.fc2.weight": "encoders.7.fc2.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.self_attn.k_proj.bias": "encoders.7.attn.to_k.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.self_attn.k_proj.weight": "encoders.7.attn.to_k.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.self_attn.out_proj.bias": "encoders.7.attn.to_out.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.self_attn.out_proj.weight": "encoders.7.attn.to_out.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.self_attn.q_proj.bias": "encoders.7.attn.to_q.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.self_attn.q_proj.weight": "encoders.7.attn.to_q.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.self_attn.v_proj.bias": "encoders.7.attn.to_v.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.7.self_attn.v_proj.weight": "encoders.7.attn.to_v.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.layer_norm1.bias": "encoders.8.layer_norm1.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.layer_norm1.weight": "encoders.8.layer_norm1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.layer_norm2.bias": "encoders.8.layer_norm2.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.layer_norm2.weight": "encoders.8.layer_norm2.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.mlp.fc1.bias": "encoders.8.fc1.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.mlp.fc1.weight": "encoders.8.fc1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.mlp.fc2.bias": "encoders.8.fc2.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.mlp.fc2.weight": "encoders.8.fc2.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.self_attn.k_proj.bias": "encoders.8.attn.to_k.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.self_attn.k_proj.weight": "encoders.8.attn.to_k.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.self_attn.out_proj.bias": "encoders.8.attn.to_out.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.self_attn.out_proj.weight": "encoders.8.attn.to_out.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.self_attn.q_proj.bias": "encoders.8.attn.to_q.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.self_attn.q_proj.weight": "encoders.8.attn.to_q.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.self_attn.v_proj.bias": "encoders.8.attn.to_v.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.8.self_attn.v_proj.weight": "encoders.8.attn.to_v.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.layer_norm1.bias": "encoders.9.layer_norm1.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.layer_norm1.weight": "encoders.9.layer_norm1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.layer_norm2.bias": "encoders.9.layer_norm2.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.layer_norm2.weight": "encoders.9.layer_norm2.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.mlp.fc1.bias": "encoders.9.fc1.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.mlp.fc1.weight": "encoders.9.fc1.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.mlp.fc2.bias": "encoders.9.fc2.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.mlp.fc2.weight": "encoders.9.fc2.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.self_attn.k_proj.bias": "encoders.9.attn.to_k.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.self_attn.k_proj.weight": "encoders.9.attn.to_k.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.self_attn.out_proj.bias": "encoders.9.attn.to_out.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.self_attn.out_proj.weight": "encoders.9.attn.to_out.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.self_attn.q_proj.bias": "encoders.9.attn.to_q.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.self_attn.q_proj.weight": "encoders.9.attn.to_q.weight", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.self_attn.v_proj.bias": "encoders.9.attn.to_v.bias", | |
| "conditioner.embedders.0.transformer.text_model.encoder.layers.9.self_attn.v_proj.weight": "encoders.9.attn.to_v.weight", | |
| } | |
| state_dict_ = {} | |
| for name in state_dict: | |
| if name in rename_dict: | |
| param = state_dict[name] | |
| if name == "conditioner.embedders.0.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 SDXLTextEncoder2StateDictConverter: | |
| 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", | |
| "text_projection.weight": "text_projection.weight" | |
| } | |
| 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 = { | |
| "conditioner.embedders.1.model.ln_final.bias": "final_layer_norm.bias", | |
| "conditioner.embedders.1.model.ln_final.weight": "final_layer_norm.weight", | |
| "conditioner.embedders.1.model.positional_embedding": "position_embeds", | |
| "conditioner.embedders.1.model.token_embedding.weight": "token_embedding.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.attn.in_proj_bias": ['encoders.0.attn.to_q.bias', 'encoders.0.attn.to_k.bias', 'encoders.0.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.0.attn.in_proj_weight": ['encoders.0.attn.to_q.weight', 'encoders.0.attn.to_k.weight', 'encoders.0.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.0.attn.out_proj.bias": "encoders.0.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.attn.out_proj.weight": "encoders.0.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.ln_1.bias": "encoders.0.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.ln_1.weight": "encoders.0.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.ln_2.bias": "encoders.0.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.ln_2.weight": "encoders.0.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.mlp.c_fc.bias": "encoders.0.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.mlp.c_fc.weight": "encoders.0.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.mlp.c_proj.bias": "encoders.0.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.0.mlp.c_proj.weight": "encoders.0.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.attn.in_proj_bias": ['encoders.1.attn.to_q.bias', 'encoders.1.attn.to_k.bias', 'encoders.1.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.1.attn.in_proj_weight": ['encoders.1.attn.to_q.weight', 'encoders.1.attn.to_k.weight', 'encoders.1.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.1.attn.out_proj.bias": "encoders.1.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.attn.out_proj.weight": "encoders.1.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.ln_1.bias": "encoders.1.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.ln_1.weight": "encoders.1.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.ln_2.bias": "encoders.1.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.ln_2.weight": "encoders.1.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.mlp.c_fc.bias": "encoders.1.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.mlp.c_fc.weight": "encoders.1.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.mlp.c_proj.bias": "encoders.1.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.1.mlp.c_proj.weight": "encoders.1.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.attn.in_proj_bias": ['encoders.10.attn.to_q.bias', 'encoders.10.attn.to_k.bias', 'encoders.10.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.10.attn.in_proj_weight": ['encoders.10.attn.to_q.weight', 'encoders.10.attn.to_k.weight', 'encoders.10.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.10.attn.out_proj.bias": "encoders.10.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.attn.out_proj.weight": "encoders.10.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.ln_1.bias": "encoders.10.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.ln_1.weight": "encoders.10.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.ln_2.bias": "encoders.10.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.ln_2.weight": "encoders.10.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.mlp.c_fc.bias": "encoders.10.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.mlp.c_fc.weight": "encoders.10.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.mlp.c_proj.bias": "encoders.10.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.10.mlp.c_proj.weight": "encoders.10.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.attn.in_proj_bias": ['encoders.11.attn.to_q.bias', 'encoders.11.attn.to_k.bias', 'encoders.11.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.11.attn.in_proj_weight": ['encoders.11.attn.to_q.weight', 'encoders.11.attn.to_k.weight', 'encoders.11.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.11.attn.out_proj.bias": "encoders.11.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.attn.out_proj.weight": "encoders.11.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.ln_1.bias": "encoders.11.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.ln_1.weight": "encoders.11.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.ln_2.bias": "encoders.11.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.ln_2.weight": "encoders.11.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.mlp.c_fc.bias": "encoders.11.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.mlp.c_fc.weight": "encoders.11.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.mlp.c_proj.bias": "encoders.11.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.11.mlp.c_proj.weight": "encoders.11.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.attn.in_proj_bias": ['encoders.12.attn.to_q.bias', 'encoders.12.attn.to_k.bias', 'encoders.12.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.12.attn.in_proj_weight": ['encoders.12.attn.to_q.weight', 'encoders.12.attn.to_k.weight', 'encoders.12.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.12.attn.out_proj.bias": "encoders.12.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.attn.out_proj.weight": "encoders.12.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.ln_1.bias": "encoders.12.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.ln_1.weight": "encoders.12.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.ln_2.bias": "encoders.12.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.ln_2.weight": "encoders.12.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.mlp.c_fc.bias": "encoders.12.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.mlp.c_fc.weight": "encoders.12.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.mlp.c_proj.bias": "encoders.12.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.12.mlp.c_proj.weight": "encoders.12.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.attn.in_proj_bias": ['encoders.13.attn.to_q.bias', 'encoders.13.attn.to_k.bias', 'encoders.13.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.13.attn.in_proj_weight": ['encoders.13.attn.to_q.weight', 'encoders.13.attn.to_k.weight', 'encoders.13.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.13.attn.out_proj.bias": "encoders.13.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.attn.out_proj.weight": "encoders.13.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.ln_1.bias": "encoders.13.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.ln_1.weight": "encoders.13.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.ln_2.bias": "encoders.13.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.ln_2.weight": "encoders.13.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.mlp.c_fc.bias": "encoders.13.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.mlp.c_fc.weight": "encoders.13.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.mlp.c_proj.bias": "encoders.13.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.13.mlp.c_proj.weight": "encoders.13.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.attn.in_proj_bias": ['encoders.14.attn.to_q.bias', 'encoders.14.attn.to_k.bias', 'encoders.14.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.14.attn.in_proj_weight": ['encoders.14.attn.to_q.weight', 'encoders.14.attn.to_k.weight', 'encoders.14.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.14.attn.out_proj.bias": "encoders.14.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.attn.out_proj.weight": "encoders.14.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.ln_1.bias": "encoders.14.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.ln_1.weight": "encoders.14.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.ln_2.bias": "encoders.14.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.ln_2.weight": "encoders.14.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.mlp.c_fc.bias": "encoders.14.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.mlp.c_fc.weight": "encoders.14.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.14.mlp.c_proj.bias": "encoders.14.fc2.bias", | |
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| "conditioner.embedders.1.model.transformer.resblocks.27.attn.in_proj_weight": ['encoders.27.attn.to_q.weight', 'encoders.27.attn.to_k.weight', 'encoders.27.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.27.attn.out_proj.bias": "encoders.27.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.attn.out_proj.weight": "encoders.27.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.ln_1.bias": "encoders.27.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.ln_1.weight": "encoders.27.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.ln_2.bias": "encoders.27.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.ln_2.weight": "encoders.27.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.mlp.c_fc.bias": "encoders.27.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.mlp.c_fc.weight": "encoders.27.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.mlp.c_proj.bias": "encoders.27.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.27.mlp.c_proj.weight": "encoders.27.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.attn.in_proj_bias": ['encoders.28.attn.to_q.bias', 'encoders.28.attn.to_k.bias', 'encoders.28.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.28.attn.in_proj_weight": ['encoders.28.attn.to_q.weight', 'encoders.28.attn.to_k.weight', 'encoders.28.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.28.attn.out_proj.bias": "encoders.28.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.attn.out_proj.weight": "encoders.28.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.ln_1.bias": "encoders.28.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.ln_1.weight": "encoders.28.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.ln_2.bias": "encoders.28.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.ln_2.weight": "encoders.28.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.mlp.c_fc.bias": "encoders.28.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.mlp.c_fc.weight": "encoders.28.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.mlp.c_proj.bias": "encoders.28.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.28.mlp.c_proj.weight": "encoders.28.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.attn.in_proj_bias": ['encoders.29.attn.to_q.bias', 'encoders.29.attn.to_k.bias', 'encoders.29.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.29.attn.in_proj_weight": ['encoders.29.attn.to_q.weight', 'encoders.29.attn.to_k.weight', 'encoders.29.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.29.attn.out_proj.bias": "encoders.29.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.attn.out_proj.weight": "encoders.29.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.ln_1.bias": "encoders.29.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.ln_1.weight": "encoders.29.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.ln_2.bias": "encoders.29.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.ln_2.weight": "encoders.29.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.mlp.c_fc.bias": "encoders.29.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.mlp.c_fc.weight": "encoders.29.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.mlp.c_proj.bias": "encoders.29.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.29.mlp.c_proj.weight": "encoders.29.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.attn.in_proj_bias": ['encoders.3.attn.to_q.bias', 'encoders.3.attn.to_k.bias', 'encoders.3.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.3.attn.in_proj_weight": ['encoders.3.attn.to_q.weight', 'encoders.3.attn.to_k.weight', 'encoders.3.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.3.attn.out_proj.bias": "encoders.3.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.attn.out_proj.weight": "encoders.3.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.ln_1.bias": "encoders.3.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.ln_1.weight": "encoders.3.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.ln_2.bias": "encoders.3.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.ln_2.weight": "encoders.3.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.mlp.c_fc.bias": "encoders.3.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.mlp.c_fc.weight": "encoders.3.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.mlp.c_proj.bias": "encoders.3.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.3.mlp.c_proj.weight": "encoders.3.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.attn.in_proj_bias": ['encoders.30.attn.to_q.bias', 'encoders.30.attn.to_k.bias', 'encoders.30.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.30.attn.in_proj_weight": ['encoders.30.attn.to_q.weight', 'encoders.30.attn.to_k.weight', 'encoders.30.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.30.attn.out_proj.bias": "encoders.30.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.attn.out_proj.weight": "encoders.30.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.ln_1.bias": "encoders.30.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.ln_1.weight": "encoders.30.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.ln_2.bias": "encoders.30.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.ln_2.weight": "encoders.30.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.mlp.c_fc.bias": "encoders.30.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.mlp.c_fc.weight": "encoders.30.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.mlp.c_proj.bias": "encoders.30.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.30.mlp.c_proj.weight": "encoders.30.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.attn.in_proj_bias": ['encoders.31.attn.to_q.bias', 'encoders.31.attn.to_k.bias', 'encoders.31.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.31.attn.in_proj_weight": ['encoders.31.attn.to_q.weight', 'encoders.31.attn.to_k.weight', 'encoders.31.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.31.attn.out_proj.bias": "encoders.31.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.attn.out_proj.weight": "encoders.31.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.ln_1.bias": "encoders.31.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.ln_1.weight": "encoders.31.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.ln_2.bias": "encoders.31.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.ln_2.weight": "encoders.31.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.mlp.c_fc.bias": "encoders.31.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.mlp.c_fc.weight": "encoders.31.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.mlp.c_proj.bias": "encoders.31.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.31.mlp.c_proj.weight": "encoders.31.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.attn.in_proj_bias": ['encoders.4.attn.to_q.bias', 'encoders.4.attn.to_k.bias', 'encoders.4.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.4.attn.in_proj_weight": ['encoders.4.attn.to_q.weight', 'encoders.4.attn.to_k.weight', 'encoders.4.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.4.attn.out_proj.bias": "encoders.4.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.attn.out_proj.weight": "encoders.4.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.ln_1.bias": "encoders.4.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.ln_1.weight": "encoders.4.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.ln_2.bias": "encoders.4.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.ln_2.weight": "encoders.4.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.mlp.c_fc.bias": "encoders.4.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.mlp.c_fc.weight": "encoders.4.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.mlp.c_proj.bias": "encoders.4.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.4.mlp.c_proj.weight": "encoders.4.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.attn.in_proj_bias": ['encoders.5.attn.to_q.bias', 'encoders.5.attn.to_k.bias', 'encoders.5.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.5.attn.in_proj_weight": ['encoders.5.attn.to_q.weight', 'encoders.5.attn.to_k.weight', 'encoders.5.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.5.attn.out_proj.bias": "encoders.5.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.attn.out_proj.weight": "encoders.5.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.ln_1.bias": "encoders.5.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.ln_1.weight": "encoders.5.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.ln_2.bias": "encoders.5.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.ln_2.weight": "encoders.5.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.mlp.c_fc.bias": "encoders.5.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.mlp.c_fc.weight": "encoders.5.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.mlp.c_proj.bias": "encoders.5.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.5.mlp.c_proj.weight": "encoders.5.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.attn.in_proj_bias": ['encoders.6.attn.to_q.bias', 'encoders.6.attn.to_k.bias', 'encoders.6.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.6.attn.in_proj_weight": ['encoders.6.attn.to_q.weight', 'encoders.6.attn.to_k.weight', 'encoders.6.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.6.attn.out_proj.bias": "encoders.6.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.attn.out_proj.weight": "encoders.6.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.ln_1.bias": "encoders.6.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.ln_1.weight": "encoders.6.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.ln_2.bias": "encoders.6.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.ln_2.weight": "encoders.6.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.mlp.c_fc.bias": "encoders.6.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.mlp.c_fc.weight": "encoders.6.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.mlp.c_proj.bias": "encoders.6.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.6.mlp.c_proj.weight": "encoders.6.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.attn.in_proj_bias": ['encoders.7.attn.to_q.bias', 'encoders.7.attn.to_k.bias', 'encoders.7.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.7.attn.in_proj_weight": ['encoders.7.attn.to_q.weight', 'encoders.7.attn.to_k.weight', 'encoders.7.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.7.attn.out_proj.bias": "encoders.7.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.attn.out_proj.weight": "encoders.7.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.ln_1.bias": "encoders.7.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.ln_1.weight": "encoders.7.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.ln_2.bias": "encoders.7.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.ln_2.weight": "encoders.7.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.mlp.c_fc.bias": "encoders.7.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.mlp.c_fc.weight": "encoders.7.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.mlp.c_proj.bias": "encoders.7.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.7.mlp.c_proj.weight": "encoders.7.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.attn.in_proj_bias": ['encoders.8.attn.to_q.bias', 'encoders.8.attn.to_k.bias', 'encoders.8.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.8.attn.in_proj_weight": ['encoders.8.attn.to_q.weight', 'encoders.8.attn.to_k.weight', 'encoders.8.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.8.attn.out_proj.bias": "encoders.8.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.attn.out_proj.weight": "encoders.8.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.ln_1.bias": "encoders.8.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.ln_1.weight": "encoders.8.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.ln_2.bias": "encoders.8.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.ln_2.weight": "encoders.8.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.mlp.c_fc.bias": "encoders.8.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.mlp.c_fc.weight": "encoders.8.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.mlp.c_proj.bias": "encoders.8.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.8.mlp.c_proj.weight": "encoders.8.fc2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.attn.in_proj_bias": ['encoders.9.attn.to_q.bias', 'encoders.9.attn.to_k.bias', 'encoders.9.attn.to_v.bias'], | |
| "conditioner.embedders.1.model.transformer.resblocks.9.attn.in_proj_weight": ['encoders.9.attn.to_q.weight', 'encoders.9.attn.to_k.weight', 'encoders.9.attn.to_v.weight'], | |
| "conditioner.embedders.1.model.transformer.resblocks.9.attn.out_proj.bias": "encoders.9.attn.to_out.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.attn.out_proj.weight": "encoders.9.attn.to_out.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.ln_1.bias": "encoders.9.layer_norm1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.ln_1.weight": "encoders.9.layer_norm1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.ln_2.bias": "encoders.9.layer_norm2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.ln_2.weight": "encoders.9.layer_norm2.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.mlp.c_fc.bias": "encoders.9.fc1.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.mlp.c_fc.weight": "encoders.9.fc1.weight", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.mlp.c_proj.bias": "encoders.9.fc2.bias", | |
| "conditioner.embedders.1.model.transformer.resblocks.9.mlp.c_proj.weight": "encoders.9.fc2.weight", | |
| "conditioner.embedders.1.model.text_projection": "text_projection.weight", | |
| } | |
| state_dict_ = {} | |
| for name in state_dict: | |
| if name in rename_dict: | |
| param = state_dict[name] | |
| if name == "conditioner.embedders.1.model.positional_embedding": | |
| param = param.reshape((1, param.shape[0], param.shape[1])) | |
| elif name == "conditioner.embedders.1.model.text_projection": | |
| param = param.T | |
| if isinstance(rename_dict[name], str): | |
| state_dict_[rename_dict[name]] = param | |
| else: | |
| length = param.shape[0] // 3 | |
| for i, rename in enumerate(rename_dict[name]): | |
| state_dict_[rename] = param[i*length: i*length+length] | |
| return state_dict_ |