SYMBOL INDEX (142 symbols across 14 files)

FILE: baseline.py
  class QFormer (line 5) | class QFormer(nn.Module):
    method __init__ (line 6) | def __init__(self,
    method forward (line 31) | def forward(self, image_feat, text_feat):
  class MLP (line 67) | class MLP(nn.Module):
    method __init__ (line 68) | def __init__(self, image_dim=320, text_dim=2048, fused_dim=768,num_hea...
    method forward (line 81) | def forward(self, image_feat, text_feat):
  class GatedAttentionFusion (line 103) | class GatedAttentionFusion(nn.Module):
    method __init__ (line 104) | def __init__(self, input_dim=768, hidden_dim=512):
    method forward (line 114) | def forward(self, img_feat, txt_feat):
  class AttentionFusionWrapper (line 126) | class AttentionFusionWrapper(nn.Module):
    method __init__ (line 127) | def __init__(self, image_dim=320, text_dim=2048, fused_dim=768,num_hea...
    method forward (line 135) | def forward(self, image_feat, text_feat):

FILE: convert_bin.py
  function convert_checkpoint_to_ip_adapter (line 5) | def convert_checkpoint_to_ip_adapter(pytorch_model_path, output_ip_adapt...

FILE: demo.py
  function generate_image (line 94) | def generate_image(uploaded_image: Image.Image, local_path: str, save_pa...

FILE: ip_adapter/attention_processor.py
  class Cross_Attention (line 12) | class Cross_Attention(nn.Module):
    method __init__ (line 13) | def __init__(self,
    method forward (line 35) | def forward(self, query_input, context_input):
  class AttnProcessor (line 60) | class AttnProcessor(nn.Module):
    method __init__ (line 65) | def __init__(
    method __call__ (line 72) | def __call__(
  class IPAttnProcessor (line 135) | class IPAttnProcessor(nn.Module):
    method __init__ (line 149) | def __init__(self, hidden_size, cross_attention_dim=None, scale=1.0, n...
    method __call__ (line 161) | def __call__(
  class AttnProcessor2_0 (line 244) | class AttnProcessor2_0(torch.nn.Module):
    method __init__ (line 249) | def __init__(
    method __call__ (line 258) | def __call__(
  class IPAttnProcessor2_0 (line 335) | class IPAttnProcessor2_0(torch.nn.Module):
    method __init__ (line 349) | def __init__(self, hidden_size, cross_attention_dim=None, scale=1.0, n...
    method __call__ (line 364) | def __call__(
  class CNAttnProcessor (line 469) | class CNAttnProcessor:
    method __init__ (line 474) | def __init__(self, num_tokens=4):
    method __call__ (line 477) | def __call__(self, attn, hidden_states, encoder_hidden_states=None, at...
  class CNAttnProcessor2_0 (line 534) | class CNAttnProcessor2_0:
    method __init__ (line 539) | def __init__(self, num_tokens=4):
    method __call__ (line 544) | def __call__(

FILE: ip_adapter/custom_pipelines.py
  class StableDiffusionXLCustomPipeline (line 16) | class StableDiffusionXLCustomPipeline(StableDiffusionXLPipeline):
    method set_scale (line 17) | def set_scale(self, scale):
    method __call__ (line 23) | def __call__(  # noqa: C901

FILE: ip_adapter/ip_adapter.py
  class ImageProjModel (line 28) | class ImageProjModel(torch.nn.Module):
    method __init__ (line 31) | def __init__(self, cross_attention_dim=1024, clip_embeddings_dim=1024,...
    method forward (line 41) | def forward(self, image_embeds):
  class MLPProjModel (line 51) | class MLPProjModel(torch.nn.Module):
    method __init__ (line 53) | def __init__(self, cross_attention_dim=1024, clip_embeddings_dim=1024):
    method forward (line 64) | def forward(self, image_embeds):
  class IPAdapter (line 69) | class IPAdapter:
    method __init__ (line 70) | def __init__(self, sd_pipe, image_encoder_path, ip_ckpt, device, num_t...
    method init_proj (line 91) | def init_proj(self):
    method set_ip_adapter (line 99) | def set_ip_adapter(self):
    method load_ip_adapter (line 135) | def load_ip_adapter(self):
    method get_image_embeds (line 159) | def get_image_embeds(self, pil_image=None, clip_image_embeds=None, ext...
    method set_scale (line 179) | def set_scale(self, scale):
    method generate (line 184) | def generate(
  class IPAdapterXL (line 249) | class IPAdapterXL(IPAdapter):
    method __init__ (line 251) | def __init__(self, sd_pipe, image_encoder_path, ip_ckpt, device,
    method generate (line 257) | def generate(
  class IPAdapterPlus (line 344) | class IPAdapterPlus(IPAdapter):
    method init_proj (line 347) | def init_proj(self):
    method get_image_embeds (line 363) | def get_image_embeds(self, pil_image=None, clip_image_embeds=None):
  class IPAdapterFull (line 378) | class IPAdapterFull(IPAdapterPlus):
    method init_proj (line 381) | def init_proj(self):
  class IPAdapterPlusXL (line 389) | class IPAdapterPlusXL(IPAdapter):
    method init_proj (line 392) | def init_proj(self):
    method get_image_embeds (line 406) | def get_image_embeds(self, pil_image):
    method generate (line 419) | def generate(

FILE: ip_adapter/ip_adapter_origin.py
  class ImageProjModel (line 28) | class ImageProjModel(torch.nn.Module):
    method __init__ (line 31) | def __init__(self, cross_attention_dim=1024, clip_embeddings_dim=1024,...
    method forward (line 41) | def forward(self, image_embeds):
  class MLPProjModel (line 51) | class MLPProjModel(torch.nn.Module):
    method __init__ (line 53) | def __init__(self, cross_attention_dim=1024, clip_embeddings_dim=1024):
    method forward (line 64) | def forward(self, image_embeds):
  class IPAdapter (line 69) | class IPAdapter:
    method __init__ (line 70) | def __init__(self, sd_pipe, image_encoder_path, ip_ckpt, device, num_t...
    method init_proj (line 89) | def init_proj(self):
    method set_ip_adapter (line 97) | def set_ip_adapter(self):
    method load_ip_adapter (line 127) | def load_ip_adapter(self):
    method get_image_embeds (line 143) | def get_image_embeds(self, pil_image=None, clip_image_embeds=None):
    method set_scale (line 155) | def set_scale(self, scale):
    method generate (line 160) | def generate(
  class IPAdapterXL (line 225) | class IPAdapterXL(IPAdapter):
    method generate (line 228) | def generate(
  class IPAdapterPlus (line 291) | class IPAdapterPlus(IPAdapter):
    method init_proj (line 294) | def init_proj(self):
    method get_image_embeds (line 310) | def get_image_embeds(self, pil_image=None, clip_image_embeds=None):
  class IPAdapterFull (line 326) | class IPAdapterFull(IPAdapterPlus):
    method init_proj (line 329) | def init_proj(self):
  class IPAdapterPlusXL (line 337) | class IPAdapterPlusXL(IPAdapter):
    method init_proj (line 340) | def init_proj(self):
    method get_image_embeds (line 354) | def get_image_embeds(self, pil_image):
    method generate (line 367) | def generate(

FILE: ip_adapter/resampler.py
  function FeedForward (line 13) | def FeedForward(dim, mult=4):
  function reshape_tensor (line 23) | def reshape_tensor(x, heads):
  class PerceiverAttention (line 34) | class PerceiverAttention(nn.Module):
    method __init__ (line 35) | def __init__(self, *, dim, dim_head=64, heads=8):
    method forward (line 49) | def forward(self, x, latents):
  class Resampler (line 81) | class Resampler(nn.Module):
    method __init__ (line 82) | def __init__(
    method forward (line 127) | def forward(self, x):
  function masked_mean (line 150) | def masked_mean(t, *, dim, mask=None):

FILE: ip_adapter/shared_models.py
  class Cross_Attention (line 16) | class Cross_Attention(nn.Module):
    method __init__ (line 17) | def __init__(self,
    method forward (line 39) | def forward(self, query_input, context_input):
  class ImageProjModel (line 64) | class ImageProjModel(torch.nn.Module):
    method __init__ (line 67) | def __init__(self, cross_attention_dim=1024, clip_embeddings_dim=1024,...
    method forward (line 77) | def forward(self, image_embeds):
  class Composed_Attention (line 88) | class Composed_Attention(torch.nn.Module):#Number_Class_crossAttention
    method __init__ (line 89) | def __init__(self, hidden_size=1280, cross_attention_dim=64, scale=1.0):
    method forward (line 108) | def forward(self, text_embeds,image_embeds):
    method load_from_checkpoint (line 124) | def load_from_checkpoint(self, ckpt_path: str):

FILE: ip_adapter/test_resampler.py
  function main (line 13) | def main():

FILE: ip_adapter/utils.py
  function hook_fn (line 7) | def hook_fn(name):
  function register_cross_attention_hook (line 15) | def register_cross_attention_hook(unet):
  function upscale (line 22) | def upscale(attn_map, target_size):
  function get_net_attn_map (line 46) | def get_net_attn_map(image_size, batch_size=2, instance_or_negative=Fals...
  function attnmaps2images (line 61) | def attnmaps2images(net_attn_maps):
  function is_torch2_available (line 80) | def is_torch2_available():
  function get_generator (line 83) | def get_generator(seed, device):

FILE: shared_models.py
  class Cross_Attention (line 16) | class Cross_Attention(nn.Module):
    method __init__ (line 17) | def __init__(self,
    method forward (line 39) | def forward(self, query_input, context_input):
  class ImageProjModel (line 64) | class ImageProjModel(torch.nn.Module):
    method __init__ (line 67) | def __init__(self, cross_attention_dim=1024, clip_embeddings_dim=1024,...
    method forward (line 77) | def forward(self, image_embeds):
  class Composed_Attention (line 88) | class Composed_Attention(torch.nn.Module):#Number_Class_crossAttention
    method __init__ (line 89) | def __init__(self, hidden_size=1280, cross_attention_dim=64, scale=1.0):
    method forward (line 108) | def forward(self, text_embeds,image_embeds):
    method load_from_checkpoint (line 124) | def load_from_checkpoint(self, ckpt_path: str):

FILE: test.py
  function generate_image (line 21) | def generate_image(input_path, prompt, extra_text, output_path="output.p...

FILE: train.py
  function count_model_params (line 35) | def count_model_params(model):
  class MyDataset (line 39) | class MyDataset(torch.utils.data.Dataset):
    method __init__ (line 41) | def __init__(self, json_file, tokenizer, tokenizer_2, size=1024, cente...
    method __getitem__ (line 63) | def __getitem__(self, idx):
    method __len__ (line 155) | def __len__(self):
  function collate_fn (line 159) | def collate_fn(data):
  class HarmonyAttention (line 188) | class HarmonyAttention(nn.Module):
    method __init__ (line 189) | def __init__(self,
    method forward (line 243) | def forward(self, text_embeds, image_embeds):
  class IPAdapter (line 275) | class IPAdapter(torch.nn.Module):
    method __init__ (line 277) | def __init__(self, unet, image_proj_model, adapter_modules, ckpt_path=...
    method forward (line 303) | def forward(self, noisy_latents, timesteps, encoder_hidden_states, une...
    method load_from_checkpoint (line 313) | def load_from_checkpoint(self, ckpt_path: str):
  function parse_args (line 344) | def parse_args():
  function main (line 485) | def main():