SYMBOL INDEX (264 symbols across 22 files)

FILE: demo/animate.py
  class MagicAnimate (line 45) | class MagicAnimate():
    method __init__ (line 46) | def __init__(self, config="configs/prompts/animation.yaml") -> None:
    method __call__ (line 128) | def __call__(self, source_image, motion_sequence, random_seed, step, g...

FILE: demo/animate_dist.py
  class MagicAnimate (line 42) | class MagicAnimate():
    method __init__ (line 43) | def __init__(self, args) -> None:
    method predict (line 129) | def predict(self, source_image, motion_sequence, random_seed, step, gu...
  function distributed_main (line 190) | def distributed_main(device_id, args):
  function run (line 200) | def run(args):

FILE: demo/gradio_animate.py
  function animate (line 21) | def animate(reference_image, motion_sequence_state, seed, steps, guidanc...
  function read_video (line 54) | def read_video(video):
  function read_image (line 59) | def read_image(image, size=512):

FILE: demo/gradio_animate_dist.py
  function animate (line 23) | def animate(reference_image, motion_sequence, seed, steps, guidance_scale):
  function read_video (line 69) | def read_video(video, size=512):
  function read_image (line 80) | def read_image(image, size=512):

FILE: magicanimate/models/appearance_encoder.py
  class Identity (line 63) | class Identity(torch.nn.Module):
    method __init__ (line 83) | def __init__(self, scale=None, *args, **kwargs) -> None:
    method forward (line 86) | def forward(self, input, *args, **kwargs):
  class _LoRACompatibleLinear (line 91) | class _LoRACompatibleLinear(nn.Module):
    method __init__ (line 96) | def __init__(self, *args, lora_layer: Optional[LoRALinearLayer] = None...
    method set_lora_layer (line 100) | def set_lora_layer(self, lora_layer: Optional[LoRALinearLayer]):
    method _fuse_lora (line 103) | def _fuse_lora(self):
    method _unfuse_lora (line 106) | def _unfuse_lora(self):
    method forward (line 109) | def forward(self, hidden_states, scale=None, lora_scale: int = 1):
  class UNet2DConditionOutput (line 114) | class UNet2DConditionOutput(BaseOutput):
  class AppearanceEncoderModel (line 126) | class AppearanceEncoderModel(ModelMixin, ConfigMixin, UNet2DConditionLoa...
    method __init__ (line 217) | def __init__(
    method attn_processors (line 636) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 659) | def set_attn_processor(self, processor: Union[AttentionProcessor, Dict...
    method set_default_attn_processor (line 693) | def set_default_attn_processor(self):
    method set_attention_slice (line 708) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 773) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 777) | def forward(

FILE: magicanimate/models/attention.py
  class Transformer3DModelOutput (line 37) | class Transformer3DModelOutput(BaseOutput):
  class Transformer3DModel (line 48) | class Transformer3DModel(ModelMixin, ConfigMixin):
    method __init__ (line 50) | def __init__(
    method forward (line 112) | def forward(self, hidden_states, encoder_hidden_states=None, timestep=...
  class BasicTransformerBlock (line 164) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 165) | def __init__(
    method set_use_memory_efficient_attention_xformers (line 248) | def set_use_memory_efficient_attention_xformers(self, use_memory_effic...
    method forward (line 276) | def forward(self, hidden_states, encoder_hidden_states=None, timestep=...

FILE: magicanimate/models/controlnet.py
  class ControlNetOutput (line 44) | class ControlNetOutput(BaseOutput):
  class ControlNetConditioningEmbedding (line 49) | class ControlNetConditioningEmbedding(nn.Module):
    method __init__ (line 59) | def __init__(
    method forward (line 81) | def forward(self, conditioning):
  class ControlNetModel (line 94) | class ControlNetModel(ModelMixin, ConfigMixin):
    method __init__ (line 98) | def __init__(
    method from_unet (line 267) | def from_unet(
    method set_attention_slice (line 384) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 449) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 453) | def forward(
  function zero_module (line 575) | def zero_module(module):

FILE: magicanimate/models/embeddings.py
  function get_timestep_embedding (line 28) | def get_timestep_embedding(
  function get_2d_sincos_pos_embed (line 71) | def get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token=False, extra...
  function get_2d_sincos_pos_embed_from_grid (line 88) | def get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
  function get_1d_sincos_pos_embed_from_grid (line 100) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
  class PatchEmbed (line 121) | class PatchEmbed(nn.Module):
    method __init__ (line 124) | def __init__(
    method forward (line 152) | def forward(self, latent):
  class TimestepEmbedding (line 161) | class TimestepEmbedding(nn.Module):
    method __init__ (line 162) | def __init__(
    method forward (line 206) | def forward(self, sample, condition=None):
  class Timesteps (line 221) | class Timesteps(nn.Module):
    method __init__ (line 222) | def __init__(self, num_channels: int, flip_sin_to_cos: bool, downscale...
    method forward (line 228) | def forward(self, timesteps):
  class GaussianFourierProjection (line 238) | class GaussianFourierProjection(nn.Module):
    method __init__ (line 241) | def __init__(
    method forward (line 255) | def forward(self, x):
  class ImagePositionalEmbeddings (line 268) | class ImagePositionalEmbeddings(nn.Module):
    method __init__ (line 292) | def __init__(
    method forward (line 310) | def forward(self, index):
  class LabelEmbedding (line 333) | class LabelEmbedding(nn.Module):
    method __init__ (line 343) | def __init__(self, num_classes, hidden_size, dropout_prob):
    method token_drop (line 350) | def token_drop(self, labels, force_drop_ids=None):
    method forward (line 361) | def forward(self, labels, force_drop_ids=None):
  class CombinedTimestepLabelEmbeddings (line 369) | class CombinedTimestepLabelEmbeddings(nn.Module):
    method __init__ (line 370) | def __init__(self, num_classes, embedding_dim, class_dropout_prob=0.1):
    method forward (line 377) | def forward(self, timestep, class_labels, hidden_dtype=None):

FILE: magicanimate/models/motion_module.py
  function zero_module (line 23) | def zero_module(module):
  class TemporalTransformer3DModelOutput (line 31) | class TemporalTransformer3DModelOutput(BaseOutput):
  function get_motion_module (line 42) | def get_motion_module(
  class VanillaTemporalModule (line 53) | class VanillaTemporalModule(nn.Module):
    method __init__ (line 54) | def __init__(
    method forward (line 82) | def forward(self, input_tensor, temb, encoder_hidden_states, attention...
  class TemporalTransformer3DModel (line 90) | class TemporalTransformer3DModel(nn.Module):
    method __init__ (line 91) | def __init__(
    method forward (line 139) | def forward(self, hidden_states, encoder_hidden_states=None, attention...
  class TemporalTransformerBlock (line 166) | class TemporalTransformerBlock(nn.Module):
    method __init__ (line 167) | def __init__(
    method forward (line 215) | def forward(self, hidden_states, encoder_hidden_states=None, attention...
  class PositionalEncoding (line 230) | class PositionalEncoding(nn.Module):
    method __init__ (line 231) | def __init__(
    method forward (line 246) | def forward(self, x):
  class VersatileAttention (line 251) | class VersatileAttention(CrossAttention):
    method __init__ (line 252) | def __init__(
    method extra_repr (line 272) | def extra_repr(self):
    method forward (line 275) | def forward(self, hidden_states, encoder_hidden_states=None, attention...

FILE: magicanimate/models/mutual_self_attention.py
  class AttentionBase (line 24) | class AttentionBase:
    method __init__ (line 25) | def __init__(self):
    method after_step (line 30) | def after_step(self):
    method __call__ (line 33) | def __call__(self, q, k, v, sim, attn, is_cross, place_in_unet, num_he...
    method forward (line 43) | def forward(self, q, k, v, sim, attn, is_cross, place_in_unet, num_hea...
    method reset (line 48) | def reset(self):
  class MutualSelfAttentionControl (line 53) | class MutualSelfAttentionControl(AttentionBase):
    method __init__ (line 55) | def __init__(self, total_steps=50, hijack_init_state=True, with_negati...
    method attn_batch (line 73) | def attn_batch(self, q, k, v, num_heads, **kwargs):
    method mutual_self_attn (line 88) | def mutual_self_attn(self, q, k, v, num_heads, **kwargs):
    method mutual_self_attn_wq (line 100) | def mutual_self_attn_wq(self, q, k, v, sim, attn, is_cross, place_in_u...
    method get_queue (line 109) | def get_queue(self):
    method set_queue (line 112) | def set_queue(self, attn_queue):
    method clear_queue (line 115) | def clear_queue(self):
    method to (line 118) | def to(self, dtype):
    method forward (line 121) | def forward(self, q, k, v, sim, attn, is_cross, place_in_unet, num_hea...
  class ReferenceAttentionControl (line 128) | class ReferenceAttentionControl():
    method __init__ (line 130) | def __init__(self,
    method register_reference_hooks (line 161) | def register_reference_hooks(
    method update (line 577) | def update(self, writer, dtype=torch.float16):
    method clear (line 619) | def clear(self):

FILE: magicanimate/models/orig_attention.py
  class Transformer2DModelOutput (line 36) | class Transformer2DModelOutput(BaseOutput):
  class Transformer2DModel (line 54) | class Transformer2DModel(ModelMixin, ConfigMixin):
    method __init__ (line 93) | def __init__(
    method forward (line 184) | def forward(self, hidden_states, encoder_hidden_states=None, timestep=...
  class AttentionBlock (line 253) | class AttentionBlock(nn.Module):
    method __init__ (line 271) | def __init__(
    method set_use_memory_efficient_attention_xformers (line 296) | def set_use_memory_efficient_attention_xformers(self, use_memory_effic...
    method reshape_heads_to_batch_dim (line 320) | def reshape_heads_to_batch_dim(self, tensor):
    method reshape_batch_dim_to_heads (line 327) | def reshape_batch_dim_to_heads(self, tensor):
    method forward (line 334) | def forward(self, hidden_states):
  class BasicTransformerBlock (line 388) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 405) | def __init__(
    method set_use_memory_efficient_attention_xformers (line 458) | def set_use_memory_efficient_attention_xformers(self, use_memory_effic...
    method forward (line 485) | def forward(self, hidden_states, encoder_hidden_states=None, timestep=...
  class CrossAttention (line 516) | class CrossAttention(nn.Module):
    method __init__ (line 531) | def __init__(
    method reshape_heads_to_batch_dim (line 578) | def reshape_heads_to_batch_dim(self, tensor):
    method reshape_batch_dim_to_heads (line 585) | def reshape_batch_dim_to_heads(self, tensor):
    method set_attention_slice (line 592) | def set_attention_slice(self, slice_size):
    method forward (line 598) | def forward(self, hidden_states, encoder_hidden_states=None, attention...
    method _attention (line 655) | def _attention(self, query, key, value, attention_mask=None):
    method _sliced_attention (line 686) | def _sliced_attention(self, query, key, value, sequence_length, dim, a...
    method _memory_efficient_attention_xformers (line 729) | def _memory_efficient_attention_xformers(self, query, key, value, atte...
  class FeedForward (line 739) | class FeedForward(nn.Module):
    method __init__ (line 751) | def __init__(
    method forward (line 778) | def forward(self, hidden_states):
  class GELU (line 784) | class GELU(nn.Module):
    method __init__ (line 789) | def __init__(self, dim_in: int, dim_out: int):
    method gelu (line 793) | def gelu(self, gate):
    method forward (line 799) | def forward(self, hidden_states):
  class GEGLU (line 806) | class GEGLU(nn.Module):
    method __init__ (line 815) | def __init__(self, dim_in: int, dim_out: int):
    method gelu (line 819) | def gelu(self, gate):
    method forward (line 825) | def forward(self, hidden_states):
  class ApproximateGELU (line 830) | class ApproximateGELU(nn.Module):
    method __init__ (line 837) | def __init__(self, dim_in: int, dim_out: int):
    method forward (line 841) | def forward(self, x):
  class AdaLayerNorm (line 846) | class AdaLayerNorm(nn.Module):
    method __init__ (line 851) | def __init__(self, embedding_dim, num_embeddings):
    method forward (line 858) | def forward(self, x, timestep):
  class DualTransformer2DModel (line 865) | class DualTransformer2DModel(nn.Module):
    method __init__ (line 892) | def __init__(
    method forward (line 941) | def forward(

FILE: magicanimate/models/resnet.py
  class InflatedConv3d (line 30) | class InflatedConv3d(nn.Conv2d):
    method forward (line 31) | def forward(self, x):
  class Upsample3D (line 41) | class Upsample3D(nn.Module):
    method __init__ (line 42) | def __init__(self, channels, use_conv=False, use_conv_transpose=False,...
    method forward (line 56) | def forward(self, hidden_states, output_size=None):
  class Downsample3D (line 87) | class Downsample3D(nn.Module):
    method __init__ (line 88) | def __init__(self, channels, use_conv=False, out_channels=None, paddin...
    method forward (line 102) | def forward(self, hidden_states):
  class ResnetBlock3D (line 113) | class ResnetBlock3D(nn.Module):
    method __init__ (line 114) | def __init__(
    method forward (line 177) | def forward(self, input_tensor, temb):
  class Mish (line 210) | class Mish(torch.nn.Module):
    method forward (line 211) | def forward(self, hidden_states):

FILE: magicanimate/models/stable_diffusion_controlnet_reference.py
  function torch_dfs (line 65) | def torch_dfs(model: torch.nn.Module):
  class StableDiffusionControlNetReferencePipeline (line 72) | class StableDiffusionControlNetReferencePipeline(StableDiffusionControlN...
    method prepare_ref_latents (line 73) | def prepare_ref_latents(self, refimage, batch_size, dtype, device, gen...
    method __call__ (line 104) | def __call__(

FILE: magicanimate/models/unet.py
  class UNet3DConditionOutput (line 53) | class UNet3DConditionOutput(BaseOutput):
  class UNet3DConditionModel (line 57) | class UNet3DConditionModel(ModelMixin, ConfigMixin):
    method __init__ (line 61) | def __init__(
    method set_attention_slice (line 262) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 327) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 331) | def forward(
    method from_pretrained_2d (line 470) | def from_pretrained_2d(cls, pretrained_model_path, subfolder=None, une...

FILE: magicanimate/models/unet_3d_blocks.py
  function get_down_block (line 30) | def get_down_block(
  function get_up_block (line 106) | def get_up_block(
  class UNetMidBlock3DCrossAttn (line 181) | class UNetMidBlock3DCrossAttn(nn.Module):
    method __init__ (line 182) | def __init__(
    method forward (line 276) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None...
  class CrossAttnDownBlock3D (line 286) | class CrossAttnDownBlock3D(nn.Module):
    method __init__ (line 287) | def __init__(
    method forward (line 384) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None...
  class DownBlock3D (line 426) | class DownBlock3D(nn.Module):
    method __init__ (line 427) | def __init__(
    method forward (line 491) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class CrossAttnUpBlock3D (line 522) | class CrossAttnUpBlock3D(nn.Module):
    method __init__ (line 523) | def __init__(
    method forward (line 616) | def forward(
  class UpBlock3D (line 665) | class UpBlock3D(nn.Module):
    method __init__ (line 666) | def __init__(
    method forward (line 726) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, u...

FILE: magicanimate/models/unet_controlnet.py
  class UNet3DConditionOutput (line 50) | class UNet3DConditionOutput(BaseOutput):
  class UNet3DConditionModel (line 54) | class UNet3DConditionModel(ModelMixin, ConfigMixin):
    method __init__ (line 58) | def __init__(
    method set_attention_slice (line 259) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 324) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 328) | def forward(
    method from_pretrained_2d (line 486) | def from_pretrained_2d(cls, pretrained_model_path, subfolder=None, une...

FILE: magicanimate/pipelines/animation.py
  function main (line 46) | def main(args):
  function distributed_main (line 246) | def distributed_main(device_id, args):
  function run (line 256) | def run(args):

FILE: magicanimate/pipelines/context.py
  function ordered_halving (line 12) | def ordered_halving(val):
  function uniform (line 20) | def uniform(
  function get_context_scheduler (line 45) | def get_context_scheduler(name: str) -> Callable:
  function get_total_steps (line 52) | def get_total_steps(

FILE: magicanimate/pipelines/pipeline_animation.py
  class AnimationPipelineOutput (line 69) | class AnimationPipelineOutput(BaseOutput):
  class AnimationPipeline (line 73) | class AnimationPipeline(DiffusionPipeline):
    method __init__ (line 76) | def __init__(
    method enable_vae_slicing (line 152) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 155) | def disable_vae_slicing(self):
    method enable_sequential_cpu_offload (line 158) | def enable_sequential_cpu_offload(self, gpu_id=0):
    method _execution_device (line 172) | def _execution_device(self):
    method _encode_prompt (line 184) | def _encode_prompt(self, prompt, device, num_videos_per_prompt, do_cla...
    method decode_latents (line 273) | def decode_latents(self, latents, rank, decoder_consistency=None):
    method prepare_extra_step_kwargs (line 291) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 308) | def check_inputs(self, prompt, height, width, callback_steps):
    method prepare_latents (line 323) | def prepare_latents(self, batch_size, num_channels_latents, video_leng...
    method prepare_condition (line 352) | def prepare_condition(self, condition, num_videos_per_prompt, device, ...
    method next_step (line 361) | def next_step(
    method images2latents (line 385) | def images2latents(self, images, dtype):
    method invert (line 399) | def invert(
    method interpolate_latents (line 461) | def interpolate_latents(self, latents: torch.Tensor, interpolation_fac...
    method select_controlnet_res_samples (line 496) | def select_controlnet_res_samples(self, controlnet_res_samples_cache_d...
    method __call__ (line 525) | def __call__(

FILE: magicanimate/utils/dist_tools.py
  function distributed_init (line 18) | def distributed_init(args):
  function get_rank (line 62) | def get_rank():
  function is_master (line 72) | def is_master():
  function synchronize (line 76) | def synchronize():
  function suppress_output (line 81) | def suppress_output(is_master):

FILE: magicanimate/utils/util.py
  function save_videos_grid (line 21) | def save_videos_grid(videos: torch.Tensor, path: str, rescale=False, n_r...
  function save_images_grid (line 35) | def save_images_grid(images: torch.Tensor, path: str):
  function init_prompt (line 45) | def init_prompt(prompt, pipeline):
  function next_step (line 64) | def next_step(model_output: Union[torch.FloatTensor, np.ndarray], timest...
  function get_noise_pred_single (line 77) | def get_noise_pred_single(latents, t, context, unet):
  function ddim_loop (line 83) | def ddim_loop(pipeline, ddim_scheduler, latent, num_inv_steps, prompt):
  function ddim_inversion (line 97) | def ddim_inversion(pipeline, ddim_scheduler, video_latent, num_inv_steps...
  function video2images (line 102) | def video2images(path, step=4, length=16, start=0):
  function images2video (line 111) | def images2video(video, path, fps=8):
  function get_tensor_interpolation_method (line 118) | def get_tensor_interpolation_method():
  function set_tensor_interpolation_method (line 121) | def set_tensor_interpolation_method(is_slerp):
  function linear (line 125) | def linear(v1, v2, t):
  function slerp (line 128) | def slerp(

FILE: magicanimate/utils/videoreader.py
  class VideoReader (line 31) | class VideoReader():
    method __init__ (line 37) | def __init__(self, video, num_frames=float("inf"), decode_lossy=False,...
    method seek (line 61) | def seek(self, pts, backward=True, any_frame=False):
    method _occasional_gc (line 65) | def _occasional_gc(self):
    method _read_video (line 73) | def _read_video(self, offset):
    method _iter_frames (line 90) | def _iter_frames(self):
    method _compute_video_stats (line 95) | def _compute_video_stats(self):
    method _get_video_frame_rate (line 113) | def _get_video_frame_rate(self):
    method sample (line 116) | def sample(self, debug=False):
    method read_frames (line 141) | def read_frames(self, frame_indices):
    method read (line 150) | def read(self):
    method get_num_frames (line 155) | def get_num_frames(self):