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import torch | |
from .sd_text_encoder import CLIPEncoderLayer | |
class CLIPVisionEmbeddings(torch.nn.Module): | |
def __init__(self, embed_dim=1280, image_size=224, patch_size=14, num_channels=3): | |
super().__init__() | |
# class_embeds (This is a fixed tensor) | |
self.class_embedding = torch.nn.Parameter(torch.randn(1, 1, embed_dim)) | |
# position_embeds | |
self.patch_embedding = torch.nn.Conv2d(in_channels=num_channels, out_channels=embed_dim, kernel_size=patch_size, stride=patch_size, bias=False) | |
# position_embeds (This is a fixed tensor) | |
self.position_embeds = torch.nn.Parameter(torch.zeros(1, (image_size // patch_size) ** 2 + 1, embed_dim)) | |
def forward(self, pixel_values): | |
batch_size = pixel_values.shape[0] | |
patch_embeds = self.patch_embedding(pixel_values) | |
patch_embeds = patch_embeds.flatten(2).transpose(1, 2) | |
class_embeds = self.class_embedding.repeat(batch_size, 1, 1) | |
embeddings = torch.cat([class_embeds, patch_embeds], dim=1) + self.position_embeds | |
return embeddings | |
class SVDImageEncoder(torch.nn.Module): | |
def __init__(self, embed_dim=1280, layer_norm_eps=1e-5, num_encoder_layers=32, encoder_intermediate_size=5120, projection_dim=1024, num_heads=16, head_dim=80): | |
super().__init__() | |
self.embeddings = CLIPVisionEmbeddings(embed_dim=embed_dim) | |
self.pre_layernorm = torch.nn.LayerNorm(embed_dim, eps=layer_norm_eps) | |
self.encoders = torch.nn.ModuleList([ | |
CLIPEncoderLayer(embed_dim, encoder_intermediate_size, num_heads=num_heads, head_dim=head_dim, use_quick_gelu=False) | |
for _ in range(num_encoder_layers)]) | |
self.post_layernorm = torch.nn.LayerNorm(embed_dim, eps=layer_norm_eps) | |
self.visual_projection = torch.nn.Linear(embed_dim, projection_dim, bias=False) | |
def forward(self, pixel_values): | |
embeds = self.embeddings(pixel_values) | |
embeds = self.pre_layernorm(embeds) | |
for encoder_id, encoder in enumerate(self.encoders): | |
embeds = encoder(embeds) | |
embeds = self.post_layernorm(embeds[:, 0, :]) | |
embeds = self.visual_projection(embeds) | |
return embeds | |
def state_dict_converter(self): | |
return SVDImageEncoderStateDictConverter() | |
class SVDImageEncoderStateDictConverter: | |
def __init__(self): | |
pass | |
def from_diffusers(self, state_dict): | |
rename_dict = { | |
"vision_model.embeddings.patch_embedding.weight": "embeddings.patch_embedding.weight", | |
"vision_model.embeddings.class_embedding": "embeddings.class_embedding", | |
"vision_model.embeddings.position_embedding.weight": "embeddings.position_embeds", | |
"vision_model.pre_layrnorm.weight": "pre_layernorm.weight", | |
"vision_model.pre_layrnorm.bias": "pre_layernorm.bias", | |
"vision_model.post_layernorm.weight": "post_layernorm.weight", | |
"vision_model.post_layernorm.bias": "post_layernorm.bias", | |
"visual_projection.weight": "visual_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 == "vision_model.embeddings.class_embedding": | |
param = state_dict[name].view(1, 1, -1) | |
elif name == "vision_model.embeddings.position_embedding.weight": | |
param = state_dict[name].unsqueeze(0) | |
state_dict_[rename_dict[name]] = param | |
elif name.startswith("vision_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.open_clip.model.visual.class_embedding": "embeddings.class_embedding", | |
"conditioner.embedders.0.open_clip.model.visual.conv1.weight": "embeddings.patch_embedding.weight", | |
"conditioner.embedders.0.open_clip.model.visual.ln_post.bias": "post_layernorm.bias", | |
"conditioner.embedders.0.open_clip.model.visual.ln_post.weight": "post_layernorm.weight", | |
"conditioner.embedders.0.open_clip.model.visual.ln_pre.bias": "pre_layernorm.bias", | |
"conditioner.embedders.0.open_clip.model.visual.ln_pre.weight": "pre_layernorm.weight", | |
"conditioner.embedders.0.open_clip.model.visual.positional_embedding": "embeddings.position_embeds", | |
"conditioner.embedders.0.open_clip.model.visual.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.0.open_clip.model.visual.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.0.open_clip.model.visual.transformer.resblocks.0.attn.out_proj.bias": "encoders.0.attn.to_out.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.attn.out_proj.weight": "encoders.0.attn.to_out.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.ln_1.bias": "encoders.0.layer_norm1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.ln_1.weight": "encoders.0.layer_norm1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.ln_2.bias": "encoders.0.layer_norm2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.ln_2.weight": "encoders.0.layer_norm2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.mlp.c_fc.bias": "encoders.0.fc1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.mlp.c_fc.weight": "encoders.0.fc1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.mlp.c_proj.bias": "encoders.0.fc2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.0.mlp.c_proj.weight": "encoders.0.fc2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.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.0.open_clip.model.visual.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.0.open_clip.model.visual.transformer.resblocks.1.attn.out_proj.bias": "encoders.1.attn.to_out.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.attn.out_proj.weight": "encoders.1.attn.to_out.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.ln_1.bias": "encoders.1.layer_norm1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.ln_1.weight": "encoders.1.layer_norm1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.ln_2.bias": "encoders.1.layer_norm2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.ln_2.weight": "encoders.1.layer_norm2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.mlp.c_fc.bias": "encoders.1.fc1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.mlp.c_fc.weight": "encoders.1.fc1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.mlp.c_proj.bias": "encoders.1.fc2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.1.mlp.c_proj.weight": "encoders.1.fc2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.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.0.open_clip.model.visual.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.0.open_clip.model.visual.transformer.resblocks.10.attn.out_proj.bias": "encoders.10.attn.to_out.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.attn.out_proj.weight": "encoders.10.attn.to_out.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.ln_1.bias": "encoders.10.layer_norm1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.ln_1.weight": "encoders.10.layer_norm1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.ln_2.bias": "encoders.10.layer_norm2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.ln_2.weight": "encoders.10.layer_norm2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.mlp.c_fc.bias": "encoders.10.fc1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.mlp.c_fc.weight": "encoders.10.fc1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.mlp.c_proj.bias": "encoders.10.fc2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.10.mlp.c_proj.weight": "encoders.10.fc2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.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.0.open_clip.model.visual.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.0.open_clip.model.visual.transformer.resblocks.11.attn.out_proj.bias": "encoders.11.attn.to_out.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.attn.out_proj.weight": "encoders.11.attn.to_out.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.ln_1.bias": "encoders.11.layer_norm1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.ln_1.weight": "encoders.11.layer_norm1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.ln_2.bias": "encoders.11.layer_norm2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.ln_2.weight": "encoders.11.layer_norm2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.mlp.c_fc.bias": "encoders.11.fc1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.mlp.c_fc.weight": "encoders.11.fc1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.mlp.c_proj.bias": "encoders.11.fc2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.11.mlp.c_proj.weight": "encoders.11.fc2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.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.0.open_clip.model.visual.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.0.open_clip.model.visual.transformer.resblocks.12.attn.out_proj.bias": "encoders.12.attn.to_out.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.12.attn.out_proj.weight": "encoders.12.attn.to_out.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.12.ln_1.bias": "encoders.12.layer_norm1.bias", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.12.mlp.c_fc.weight": "encoders.12.fc1.weight", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.12.mlp.c_proj.weight": "encoders.12.fc2.weight", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.13.ln_1.bias": "encoders.13.layer_norm1.bias", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.13.ln_2.bias": "encoders.13.layer_norm2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.13.ln_2.weight": "encoders.13.layer_norm2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.13.mlp.c_fc.bias": "encoders.13.fc1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.13.mlp.c_fc.weight": "encoders.13.fc1.weight", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.13.mlp.c_proj.weight": "encoders.13.fc2.weight", | |
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"conditioner.embedders.0.open_clip.model.visual.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.0.open_clip.model.visual.transformer.resblocks.14.attn.out_proj.bias": "encoders.14.attn.to_out.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.14.attn.out_proj.weight": "encoders.14.attn.to_out.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.14.ln_1.bias": "encoders.14.layer_norm1.bias", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.14.ln_2.bias": "encoders.14.layer_norm2.bias", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.14.mlp.c_fc.bias": "encoders.14.fc1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.14.mlp.c_fc.weight": "encoders.14.fc1.weight", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.15.attn.out_proj.weight": "encoders.15.attn.to_out.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.15.ln_1.bias": "encoders.15.layer_norm1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.15.ln_1.weight": "encoders.15.layer_norm1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.15.ln_2.bias": "encoders.15.layer_norm2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.15.ln_2.weight": "encoders.15.layer_norm2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.15.mlp.c_fc.bias": "encoders.15.fc1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.15.mlp.c_fc.weight": "encoders.15.fc1.weight", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.15.mlp.c_proj.weight": "encoders.15.fc2.weight", | |
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"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.attn.in_proj_weight": ['encoders.16.attn.to_q.weight', 'encoders.16.attn.to_k.weight', 'encoders.16.attn.to_v.weight'], | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.attn.out_proj.bias": "encoders.16.attn.to_out.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.attn.out_proj.weight": "encoders.16.attn.to_out.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.ln_1.bias": "encoders.16.layer_norm1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.ln_1.weight": "encoders.16.layer_norm1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.ln_2.bias": "encoders.16.layer_norm2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.ln_2.weight": "encoders.16.layer_norm2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.mlp.c_fc.bias": "encoders.16.fc1.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.mlp.c_fc.weight": "encoders.16.fc1.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.mlp.c_proj.bias": "encoders.16.fc2.bias", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.16.mlp.c_proj.weight": "encoders.16.fc2.weight", | |
"conditioner.embedders.0.open_clip.model.visual.transformer.resblocks.17.attn.in_proj_bias": ['encoders.17.attn.to_q.bias', 'encoders.17.attn.to_k.bias', 'encoders.17.attn.to_v.bias'], | |
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} | |
state_dict_ = {} | |
for name in state_dict: | |
if name in rename_dict: | |
param = state_dict[name] | |
if name == "conditioner.embedders.0.open_clip.model.visual.class_embedding": | |
param = param.reshape((1, 1, param.shape[0])) | |
elif name == "conditioner.embedders.0.open_clip.model.visual.positional_embedding": | |
param = param.reshape((1, param.shape[0], param.shape[1])) | |
elif name == "conditioner.embedders.0.open_clip.model.visual.proj": | |
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_ | |