SYMBOL INDEX (287 symbols across 28 files)

FILE: inference.py
  function main (line 6) | def main():

FILE: ltx_video/inference.py
  function get_total_gpu_memory (line 44) | def get_total_gpu_memory():
  function get_device (line 51) | def get_device():
  function load_image_to_tensor_with_resize_and_crop (line 59) | def load_image_to_tensor_with_resize_and_crop(
  function calculate_padding (line 108) | def calculate_padding(
  function convert_prompt_to_filename (line 128) | def convert_prompt_to_filename(text: str, max_len: int = 20) -> str:
  function get_unique_filename (line 155) | def get_unique_filename(
  function seed_everething (line 175) | def seed_everething(seed: int):
  function create_transformer (line 185) | def create_transformer(ckpt_path: str, precision: str) -> Transformer3DM...
  function create_ltx_video_pipeline (line 207) | def create_ltx_video_pipeline(
  function create_latent_upsampler (line 294) | def create_latent_upsampler(latent_upsampler_model_path: str, device: str):
  function load_pipeline_config (line 301) | def load_pipeline_config(pipeline_config: str):
  class InferenceConfig (line 317) | class InferenceConfig:
  function infer (line 389) | def infer(config: InferenceConfig):
  function prepare_conditioning (line 637) | def prepare_conditioning(
  function get_media_num_frames (line 690) | def get_media_num_frames(media_path: str) -> int:
  function load_media_file (line 702) | def load_media_file(

FILE: ltx_video/models/autoencoders/causal_conv3d.py
  class CausalConv3d (line 7) | class CausalConv3d(nn.Module):
    method __init__ (line 8) | def __init__(
    method forward (line 44) | def forward(self, x, causal: bool = True):
    method weight (line 62) | def weight(self):

FILE: ltx_video/models/autoencoders/causal_video_autoencoder.py
  class CausalVideoAutoencoder (line 33) | class CausalVideoAutoencoder(AutoencoderKLWrapper):
    method from_pretrained (line 35) | def from_pretrained(
    method from_config (line 123) | def from_config(config):
    method config (line 180) | def config(self):
    method is_video_supported (line 201) | def is_video_supported(self):
    method spatial_downscale_factor (line 208) | def spatial_downscale_factor(self):
    method temporal_downscale_factor (line 228) | def temporal_downscale_factor(self):
    method to_json_string (line 243) | def to_json_string(self) -> str:
    method load_state_dict (line 248) | def load_state_dict(self, state_dict: Mapping[str, Any], strict: bool ...
    method last_layer (line 298) | def last_layer(self):
    method set_use_tpu_flash_attention (line 308) | def set_use_tpu_flash_attention(self):
  class Encoder (line 315) | class Encoder(nn.Module):
    method __init__ (line 340) | def __init__(
    method forward (line 508) | def forward(self, sample: torch.FloatTensor) -> torch.FloatTensor:
  class Decoder (line 558) | class Decoder(nn.Module):
    method __init__ (line 583) | def __init__(
    method forward (line 733) | def forward(
  class UNetMidBlock3D (line 803) | class UNetMidBlock3D(nn.Module):
    method __init__ (line 829) | def __init__(
    method forward (line 895) | def forward(
  class SpaceToDepthDownsample (line 974) | class SpaceToDepthDownsample(nn.Module):
    method __init__ (line 975) | def __init__(self, dims, in_channels, out_channels, stride, spatial_pa...
    method forward (line 989) | def forward(self, x, causal: bool = True):
  class DepthToSpaceUpsample (line 1021) | class DepthToSpaceUpsample(nn.Module):
    method __init__ (line 1022) | def __init__(
    method forward (line 1049) | def forward(self, x, causal: bool = True):
  class LayerNorm (line 1066) | class LayerNorm(nn.Module):
    method __init__ (line 1067) | def __init__(self, dim, eps, elementwise_affine=True) -> None:
    method forward (line 1071) | def forward(self, x):
  class ResnetBlock3D (line 1078) | class ResnetBlock3D(nn.Module):
    method __init__ (line 1091) | def __init__(
    method _feed_spatial_noise (line 1181) | def _feed_spatial_noise(
    method forward (line 1195) | def forward(
  function patchify (line 1259) | def patchify(x, patch_size_hw, patch_size_t=1):
  function unpatchify (line 1280) | def unpatchify(x, patch_size_hw, patch_size_t=1):
  function create_video_autoencoder_demo_config (line 1300) | def create_video_autoencoder_demo_config(
  function test_vae_patchify_unpatchify (line 1334) | def test_vae_patchify_unpatchify():
  function demo_video_autoencoder_forward_backward (line 1343) | def demo_video_autoencoder_forward_backward():

FILE: ltx_video/models/autoencoders/conv_nd_factory.py
  function make_conv_nd (line 9) | def make_conv_nd(
  function make_linear_nd (line 75) | def make_linear_nd(

FILE: ltx_video/models/autoencoders/dual_conv3d.py
  class DualConv3d (line 10) | class DualConv3d(nn.Module):
    method __init__ (line 11) | def __init__(
    method reset_parameters (line 86) | def reset_parameters(self):
    method forward (line 97) | def forward(self, x, use_conv3d=False, skip_time_conv=False):
    method forward_with_3d (line 103) | def forward_with_3d(self, x, skip_time_conv):
    method forward_with_2d (line 133) | def forward_with_2d(self, x, skip_time_conv):
    method weight (line 185) | def weight(self):
  function test_dual_conv3d_consistency (line 189) | def test_dual_conv3d_consistency():

FILE: ltx_video/models/autoencoders/latent_upsampler.py
  class ResBlock (line 15) | class ResBlock(nn.Module):
    method __init__ (line 16) | def __init__(
    method forward (line 31) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class LatentUpsampler (line 42) | class LatentUpsampler(ModelMixin, ConfigMixin):
    method __init__ (line 55) | def __init__(
    method forward (line 109) | def forward(self, latent: torch.Tensor) -> torch.Tensor:
    method from_config (line 152) | def from_config(cls, config):
    method config (line 162) | def config(self):
    method from_pretrained (line 174) | def from_pretrained(

FILE: ltx_video/models/autoencoders/pixel_norm.py
  class PixelNorm (line 5) | class PixelNorm(nn.Module):
    method __init__ (line 6) | def __init__(self, dim=1, eps=1e-8):
    method forward (line 11) | def forward(self, x):

FILE: ltx_video/models/autoencoders/pixel_shuffle.py
  class PixelShuffleND (line 5) | class PixelShuffleND(nn.Module):
    method __init__ (line 6) | def __init__(self, dims, upscale_factors=(2, 2, 2)):
    method forward (line 12) | def forward(self, x):

FILE: ltx_video/models/autoencoders/vae.py
  class AutoencoderKLWrapper (line 16) | class AutoencoderKLWrapper(ModelMixin, ConfigMixin):
    method __init__ (line 31) | def __init__(
    method set_tiling_params (line 79) | def set_tiling_params(self, sample_size: int = 512, overlap_factor: fl...
    method enable_z_tiling (line 85) | def enable_z_tiling(self, z_sample_size: int = 8):
    method disable_z_tiling (line 98) | def disable_z_tiling(self):
    method enable_hw_tiling (line 105) | def enable_hw_tiling(self):
    method disable_hw_tiling (line 111) | def disable_hw_tiling(self):
    method _hw_tiled_encode (line 117) | def _hw_tiled_encode(self, x: torch.FloatTensor, return_dict: bool = T...
    method blend_z (line 154) | def blend_z(
    method blend_v (line 164) | def blend_v(
    method blend_h (line 174) | def blend_h(
    method _hw_tiled_decode (line 184) | def _hw_tiled_decode(self, z: torch.FloatTensor, target_shape):
    method encode (line 226) | def encode(
    method _normalize_latent_channels (line 261) | def _normalize_latent_channels(self, z: torch.FloatTensor) -> torch.Fl...
    method _unnormalize_latent_channels (line 275) | def _unnormalize_latent_channels(self, z: torch.FloatTensor) -> torch....
    method _encode (line 286) | def _encode(self, x: torch.FloatTensor) -> AutoencoderKLOutput:
    method _decode (line 292) | def _decode(
    method decode (line 306) | def decode(
    method forward (line 352) | def forward(

FILE: ltx_video/models/autoencoders/vae_encode.py
  function vae_encode (line 22) | def vae_encode(
  function vae_decode (line 94) | def vae_decode(
  function _run_decoder (line 134) | def _run_decoder(
  function get_vae_size_scale_factor (line 168) | def get_vae_size_scale_factor(vae: AutoencoderKL) -> float:
  function latent_to_pixel_coords (line 190) | def latent_to_pixel_coords(
  function latent_to_pixel_coords_from_factors (line 215) | def latent_to_pixel_coords_from_factors(
  function normalize_latents (line 228) | def normalize_latents(
  function un_normalize_latents (line 239) | def un_normalize_latents(

FILE: ltx_video/models/autoencoders/video_autoencoder.py
  class VideoAutoencoder (line 22) | class VideoAutoencoder(AutoencoderKLWrapper):
    method from_pretrained (line 24) | def from_pretrained(
    method from_config (line 61) | def from_config(config):
    method config (line 112) | def config(self):
    method is_video_supported (line 135) | def is_video_supported(self):
    method downscale_factor (line 142) | def downscale_factor(self):
    method to_json_string (line 145) | def to_json_string(self) -> str:
    method load_state_dict (line 150) | def load_state_dict(self, state_dict: Mapping[str, Any], strict: bool ...
    method last_layer (line 174) | def last_layer(self):
  class Encoder (line 185) | class Encoder(nn.Module):
    method __init__ (line 208) | def __init__(
    method downscale_factor (line 300) | def downscale_factor(self):
    method forward (line 313) | def forward(
  class Decoder (line 378) | class Decoder(nn.Module):
    method __init__ (line 399) | def __init__(
    method forward (line 479) | def forward(self, sample: torch.FloatTensor, target_shape) -> torch.Fl...
  class DownEncoderBlock3D (line 517) | class DownEncoderBlock3D(nn.Module):
    method __init__ (line 518) | def __init__(
    method forward (line 560) | def forward(
  class UNetMidBlock3D (line 573) | class UNetMidBlock3D(nn.Module):
    method __init__ (line 591) | def __init__(
    method forward (line 621) | def forward(self, hidden_states: torch.FloatTensor) -> torch.FloatTensor:
  class UpDecoderBlock3D (line 628) | class UpDecoderBlock3D(nn.Module):
    method __init__ (line 629) | def __init__(
    method forward (line 671) | def forward(
  class ResnetBlock3D (line 682) | class ResnetBlock3D(nn.Module):
    method __init__ (line 695) | def __init__(
    method forward (line 746) | def forward(
  class Downsample3D (line 773) | class Downsample3D(nn.Module):
    method __init__ (line 774) | def __init__(
    method forward (line 796) | def forward(self, x, downsample_in_time=True):
  class Upsample3D (line 812) | class Upsample3D(nn.Module):
    method __init__ (line 819) | def __init__(self, dims, channels, out_channels=None):
    method forward (line 828) | def forward(self, x, upsample_in_time):
  function patchify (line 868) | def patchify(x, patch_size_hw, patch_size_t=1, add_channel_padding=False):
  function unpatchify (line 906) | def unpatchify(x, patch_size_hw, patch_size_t=1, add_channel_padding=Fal...
  function create_video_autoencoder_config (line 934) | def create_video_autoencoder_config(
  function create_video_autoencoder_pathify4x4x4_config (line 958) | def create_video_autoencoder_pathify4x4x4_config(
  function create_video_autoencoder_pathify4x4_config (line 979) | def create_video_autoencoder_pathify4x4_config(
  function test_vae_patchify_unpatchify (line 997) | def test_vae_patchify_unpatchify():
  function demo_video_autoencoder_forward_backward (line 1006) | def demo_video_autoencoder_forward_backward():

FILE: ltx_video/models/transformers/attention.py
  class BasicTransformerBlock (line 38) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 77) | def __init__(
    method set_use_tpu_flash_attention (line 184) | def set_use_tpu_flash_attention(self):
    method set_chunk_feed_forward (line 193) | def set_chunk_feed_forward(self, chunk_size: Optional[int], dim: int =...
    method forward (line 198) | def forward(
  class Attention (line 325) | class Attention(nn.Module):
    method __init__ (line 378) | def __init__(
    method set_use_tpu_flash_attention (line 526) | def set_use_tpu_flash_attention(self):
    method set_processor (line 532) | def set_processor(self, processor: "AttnProcessor") -> None:
    method get_processor (line 554) | def get_processor(
    method forward (line 660) | def forward(
    method batch_to_head_dim (line 720) | def batch_to_head_dim(self, tensor: torch.Tensor) -> torch.Tensor:
    method head_to_batch_dim (line 739) | def head_to_batch_dim(self, tensor: torch.Tensor, out_dim: int = 3) ->...
    method get_attention_scores (line 771) | def get_attention_scores(
    method prepare_attention_mask (line 825) | def prepare_attention_mask(
    method norm_encoder_hidden_states (line 884) | def norm_encoder_hidden_states(
    method apply_rotary_emb (line 918) | def apply_rotary_emb(
  class AttnProcessor2_0 (line 935) | class AttnProcessor2_0:
    method __init__ (line 940) | def __init__(self):
    method __call__ (line 943) | def __call__(
  class AttnProcessor (line 1117) | class AttnProcessor:
    method __call__ (line 1122) | def __call__(
  class FeedForward (line 1204) | class FeedForward(nn.Module):
    method __init__ (line 1218) | def __init__(
    method forward (line 1257) | def forward(self, hidden_states: torch.Tensor, scale: float = 1.0) -> ...

FILE: ltx_video/models/transformers/embeddings.py
  function get_timestep_embedding (line 10) | def get_timestep_embedding(
  function get_3d_sincos_pos_embed (line 53) | def get_3d_sincos_pos_embed(embed_dim, grid, w, h, f):
  function get_3d_sincos_pos_embed_from_grid (line 66) | def get_3d_sincos_pos_embed_from_grid(embed_dim, grid):
  function get_1d_sincos_pos_embed_from_grid (line 79) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
  class SinusoidalPositionalEmbedding (line 103) | class SinusoidalPositionalEmbedding(nn.Module):
    method __init__ (line 115) | def __init__(self, embed_dim: int, max_seq_length: int = 32):
    method forward (line 126) | def forward(self, x):

FILE: ltx_video/models/transformers/symmetric_patchifier.py
  class Patchifier (line 10) | class Patchifier(ConfigMixin, ABC):
    method __init__ (line 11) | def __init__(self, patch_size: int):
    method patchify (line 16) | def patchify(self, latents: Tensor) -> Tuple[Tensor, Tensor]:
    method unpatchify (line 20) | def unpatchify(
    method patch_size (line 30) | def patch_size(self):
    method get_latent_coords (line 33) | def get_latent_coords(
  class SymmetricPatchifier (line 54) | class SymmetricPatchifier(Patchifier):
    method patchify (line 55) | def patchify(self, latents: Tensor) -> Tuple[Tensor, Tensor]:
    method unpatchify (line 67) | def unpatchify(

FILE: ltx_video/models/transformers/transformer3d.py
  class Transformer3DModelOutput (line 35) | class Transformer3DModelOutput(BaseOutput):
  class Transformer3DModel (line 48) | class Transformer3DModel(ModelMixin, ConfigMixin):
    method __init__ (line 52) | def __init__(
    method set_use_tpu_flash_attention (line 162) | def set_use_tpu_flash_attention(self):
    method create_skip_layer_mask (line 173) | def create_skip_layer_mask(
    method _set_gradient_checkpointing (line 190) | def _set_gradient_checkpointing(self, module, value=False):
    method get_fractional_positions (line 194) | def get_fractional_positions(self, indices_grid):
    method precompute_freqs_cis (line 204) | def precompute_freqs_cis(self, indices_grid, spacing="exp"):
    method load_state_dict (line 259) | def load_state_dict(
    method from_pretrained (line 274) | def from_pretrained(
    method forward (line 330) | def forward(

FILE: ltx_video/pipelines/crf_compressor.py
  function _encode_single_frame (line 7) | def _encode_single_frame(output_file, image_array: np.ndarray, crf):
  function _decode_single_frame (line 24) | def _decode_single_frame(video_file):
  function compress (line 34) | def compress(image: torch.Tensor, crf=29):

FILE: ltx_video/pipelines/pipeline_ltx_video.py
  function retrieve_timesteps (line 125) | def retrieve_timesteps(
  class ConditioningItem (line 194) | class ConditioningItem:
  class LTXVideoPipeline (line 213) | class LTXVideoPipeline(DiffusionPipeline):
    method __init__ (line 262) | def __init__(
    method mask_text_embeddings (line 298) | def mask_text_embeddings(self, emb, mask):
    method encode_prompt (line 307) | def encode_prompt(
    method prepare_extra_step_kwargs (line 479) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 500) | def check_inputs(
    method _text_preprocessing (line 586) | def _text_preprocessing(self, text):
    method add_noise_to_image_conditioning_latents (line 597) | def add_noise_to_image_conditioning_latents(
    method prepare_latents (line 623) | def prepare_latents(
    method classify_height_width_bin (line 704) | def classify_height_width_bin(
    method resize_and_crop_tensor (line 714) | def resize_and_crop_tensor(
    method resize_tensor (line 740) | def resize_tensor(media_items, height, width):
    method __call__ (line 754) | def __call__(
    method denoising_step (line 1348) | def denoising_step(
    method prepare_conditioning (line 1383) | def prepare_conditioning(
    method _resize_conditioning_item (line 1590) | def _resize_conditioning_item(
    method _get_latent_spatial_position (line 1605) | def _get_latent_spatial_position(
    method _handle_non_first_conditioning_sequence (line 1653) | def _handle_non_first_conditioning_sequence(
    method trim_conditioning_sequence (line 1728) | def trim_conditioning_sequence(
    method tone_map_latents (line 1749) | def tone_map_latents(
  function adain_filter_latent (line 1790) | def adain_filter_latent(
  class LTXMultiScalePipeline (line 1821) | class LTXMultiScalePipeline:
    method _upsample_latents (line 1822) | def _upsample_latents(
    method __init__ (line 1836) | def __init__(
    method __call__ (line 1843) | def __call__(

FILE: ltx_video/schedulers/rf.py
  function linear_quadratic_schedule (line 25) | def linear_quadratic_schedule(num_steps, threshold_noise=0.025, linear_s...
  function simple_diffusion_resolution_dependent_timestep_shift (line 49) | def simple_diffusion_resolution_dependent_timestep_shift(
  function time_shift (line 69) | def time_shift(mu: float, sigma: float, t: Tensor):
  function get_normal_shift (line 73) | def get_normal_shift(
  function strech_shifts_to_terminal (line 85) | def strech_shifts_to_terminal(shifts: Tensor, terminal=0.1):
  function sd3_resolution_dependent_timestep_shift (line 112) | def sd3_resolution_dependent_timestep_shift(
  class TimestepShifter (line 152) | class TimestepShifter(ABC):
    method shift_timesteps (line 154) | def shift_timesteps(self, samples_shape: torch.Size, timesteps: Tensor...
  class RectifiedFlowSchedulerOutput (line 159) | class RectifiedFlowSchedulerOutput(BaseOutput):
  class RectifiedFlowScheduler (line 176) | class RectifiedFlowScheduler(SchedulerMixin, ConfigMixin, TimestepShifter):
    method __init__ (line 180) | def __init__(
    method get_initial_timesteps (line 201) | def get_initial_timesteps(
    method shift_timesteps (line 216) | def shift_timesteps(self, samples_shape: torch.Size, timesteps: Tensor...
    method set_timesteps (line 227) | def set_timesteps(
    method from_pretrained (line 264) | def from_pretrained(pretrained_model_path: Union[str, os.PathLike]):
    method scale_model_input (line 288) | def scale_model_input(
    method step (line 305) | def step(
    method add_noise (line 376) | def add_noise(

FILE: ltx_video/utils/diffusers_config_mapping.py
  function make_hashable_key (line 1) | def make_hashable_key(dict_key):

FILE: ltx_video/utils/prompt_enhance_utils.py
  function tensor_to_pil (line 47) | def tensor_to_pil(tensor):
  function generate_cinematic_prompt (line 64) | def generate_cinematic_prompt(
  function _get_first_frames_from_conditioning_item (line 113) | def _get_first_frames_from_conditioning_item(conditioning_item) -> List[...
  function _generate_t2v_prompt (line 121) | def _generate_t2v_prompt(
  function _generate_i2v_prompt (line 151) | def _generate_i2v_prompt(
  function _generate_image_captions (line 188) | def _generate_image_captions(
  function _generate_and_decode_prompts (line 211) | def _generate_and_decode_prompts(

FILE: ltx_video/utils/skip_layer_strategy.py
  class SkipLayerStrategy (line 4) | class SkipLayerStrategy(Enum):

FILE: ltx_video/utils/torch_utils.py
  function append_dims (line 5) | def append_dims(x: torch.Tensor, target_dims: int) -> torch.Tensor:
  class Identity (line 17) | class Identity(nn.Module):
    method __init__ (line 20) | def __init__(self, *args, **kwargs) -> None:  # pylint: disable=unused...
    method forward (line 24) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:

FILE: tests/conftest.py
  function pytest_make_parametrize_id (line 14) | def pytest_make_parametrize_id(config, val, argname):
  function num_latent_channels (line 21) | def num_latent_channels():
  function video_autoencoder (line 26) | def video_autoencoder(num_latent_channels):
  function transformer_config (line 34) | def transformer_config(num_latent_channels):
  function synthetic_ckpt_path (line 67) | def synthetic_ckpt_path(

FILE: tests/test_configs.py
  function prompt (line 10) | def prompt():
  function test_run_config (line 20) | def test_run_config(tmp_path, prompt, pipeline_config):

FILE: tests/test_inference.py
  function input_image_path (line 16) | def input_image_path():
  function input_video_path (line 21) | def input_video_path():
  function base_inference_config (line 25) | def base_inference_config(tmp_path, pipeline_config):
  function base_pipeline_config (line 44) | def base_pipeline_config(synthetic_ckpt_path):
  function test_condition_modes (line 66) | def test_condition_modes(
  function test_vid2vid (line 93) | def test_vid2vid(tmp_path, input_video_path, base_pipeline_config):
  function test_pipeline_on_batch (line 106) | def test_pipeline_on_batch(tmp_path, base_pipeline_config):
  function test_prompt_enhancement (line 161) | def test_prompt_enhancement(tmp_path, base_pipeline_config):

FILE: tests/test_scheduler.py
  function init_latents_and_scheduler (line 6) | def init_latents_and_scheduler(sampler):
  function test_scheduler_default_behavior (line 18) | def test_scheduler_default_behavior(sampler):
  function test_scheduler_per_token (line 41) | def test_scheduler_per_token(sampler):
  function test_scheduler_t_not_in_list (line 71) | def test_scheduler_t_not_in_list(sampler):

FILE: tests/test_vae.py
  function test_encode_decode_shape (line 8) | def test_encode_decode_shape(video_autoencoder, num_latent_channels):
  function test_temporal_causality (line 32) | def test_temporal_causality(video_autoencoder):
  function test_downscale_factors (line 59) | def test_downscale_factors(