Transformer Temporal A Transformer model for video-like data.  TransformerTemporalModel  class diffusers.models.TransformerTemporalModel  < source > ( num_attention_heads: int = 16 attention_head_dim: int = 88 in_channels: Optional = None out_channels: Optional = None num_layers: int = 1 dropout: float = 0.0 norm_num_groups: int = 32 cross_attention_dim: Optional = None attention_bias: bool = False sample_size: Optional = None activation_fn: str = 'geglu' norm_elementwise_affine: bool = True double_self_attention: bool = True positional_embeddings: Optional = None num_positional_embeddings: Optional = None  )   Parameters   num_attention_heads (int, optional, defaults to 16) — The number of heads to use for multi-head attention.   attention_head_dim (int, optional, defaults to 88) — The number of channels in each head.   in_channels (int, optional) —