diffusers/pr_12595/en/api/models/easyanimate_transformer3d.md

EasyAnimateTransformer3DModel

A Diffusion Transformer model for 3D data from EasyAnimate was introduced by Alibaba PAI.

The model can be loaded with the following code snippet.

from diffusers import EasyAnimateTransformer3DModel

transformer = EasyAnimateTransformer3DModel.from_pretrained("alibaba-pai/EasyAnimateV5.1-12b-zh", subfolder="transformer", torch_dtype=torch.float16).to("cuda")

EasyAnimateTransformer3DModel[[diffusers.EasyAnimateTransformer3DModel]]

class diffusers.EasyAnimateTransformer3DModeldiffusers.EasyAnimateTransformer3DModelhttps://github.com/huggingface/diffusers/blob/vr_12595/src/diffusers/models/transformers/transformer_easyanimate.py#L318[{"name": "num_attention_heads", "val": ": int = 48"}, {"name": "attention_head_dim", "val": ": int = 64"}, {"name": "in_channels", "val": ": typing.Optional[int] = None"}, {"name": "out_channels", "val": ": typing.Optional[int] = None"}, {"name": "patch_size", "val": ": typing.Optional[int] = None"}, {"name": "sample_width", "val": ": int = 90"}, {"name": "sample_height", "val": ": int = 60"}, {"name": "activation_fn", "val": ": str = 'gelu-approximate'"}, {"name": "timestep_activation_fn", "val": ": str = 'silu'"}, {"name": "freq_shift", "val": ": int = 0"}, {"name": "num_layers", "val": ": int = 48"}, {"name": "mmdit_layers", "val": ": int = 48"}, {"name": "dropout", "val": ": float = 0.0"}, {"name": "time_embed_dim", "val": ": int = 512"}, {"name": "add_norm_text_encoder", "val": ": bool = False"}, {"name": "text_embed_dim", "val": ": int = 3584"}, {"name": "text_embed_dim_t5", "val": ": int = None"}, {"name": "norm_eps", "val": ": float = 1e-05"}, {"name": "norm_elementwise_affine", "val": ": bool = True"}, {"name": "flip_sin_to_cos", "val": ": bool = True"}, {"name": "time_position_encoding_type", "val": ": str = '3d_rope'"}, {"name": "after_norm", "val": " = False"}, {"name": "resize_inpaint_mask_directly", "val": ": bool = True"}, {"name": "enable_text_attention_mask", "val": ": bool = True"}, {"name": "add_noise_in_inpaint_model", "val": ": bool = True"}]- num_attention_heads (int, defaults to 48) -- The number of heads to use for multi-head attention.

• attention_head_dim (int, defaults to 64) -- The number of channels in each head.
• in_channels (int, defaults to 16) -- The number of channels in the input.
• out_channels (int, optional, defaults to 16) -- The number of channels in the output.
• patch_size (int, defaults to 2) -- The size of the patches to use in the patch embedding layer.
• sample_width (int, defaults to 90) -- The width of the input latents.
• sample_height (int, defaults to 60) -- The height of the input latents.
• activation_fn (str, defaults to "gelu-approximate") -- Activation function to use in feed-forward.
• timestep_activation_fn (str, defaults to "silu") -- Activation function to use when generating the timestep embeddings.
• num_layers (int, defaults to 30) -- The number of layers of Transformer blocks to use.
• mmdit_layers (int, defaults to 1000) -- The number of layers of Multi Modal Transformer blocks to use.
• dropout (float, defaults to 0.0) -- The dropout probability to use.
• time_embed_dim (int, defaults to 512) -- Output dimension of timestep embeddings.
• text_embed_dim (int, defaults to 4096) -- Input dimension of text embeddings from the text encoder.
• norm_eps (float, defaults to 1e-5) -- The epsilon value to use in normalization layers.
• norm_elementwise_affine (bool, defaults to True) -- Whether to use elementwise affine in normalization layers.
• flip_sin_to_cos (bool, defaults to True) -- Whether to flip the sin to cos in the time embedding.
• time_position_encoding_type (str, defaults to 3d_rope) -- Type of time position encoding.
• after_norm (bool, defaults to False) -- Flag to apply normalization after.
• resize_inpaint_mask_directly (bool, defaults to True) -- Flag to resize inpaint mask directly.
• enable_text_attention_mask (bool, defaults to True) -- Flag to enable text attention mask.
• add_noise_in_inpaint_model (bool, defaults to False) -- Flag to add noise in inpaint model.0

A Transformer model for video-like data in EasyAnimate.

Transformer2DModelOutput[[diffusers.models.modeling_outputs.Transformer2DModelOutput]]

class diffusers.models.modeling_outputs.Transformer2DModelOutputdiffusers.models.modeling_outputs.Transformer2DModelOutputhttps://github.com/huggingface/diffusers/blob/vr_12595/src/diffusers/models/modeling_outputs.py#L21[{"name": "sample", "val": ": torch.Tensor"}]- sample (torch.Tensor of shape (batch_size, num_channels, height, width) or (batch size, num_vector_embeds - 1, num_latent_pixels) if Transformer2DModel is discrete) -- The hidden states output conditioned on the encoder_hidden_states input. If discrete, returns probability distributions for the unnoised latent pixels.0

The output of Transformer2DModel.