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vllm_omni.diffusion.layers.adalayernorm

logger module-attribute 

logger = init_logger(__name__)

AdaLayerNorm

Bases: CustomOp

AdaLayerNorm

out = layernorm(x) * (1 + scale) + shift

elementwise_affine instance-attribute 

elementwise_affine = elementwise_affine

eps instance-attribute 

eps = eps

hidden_size instance-attribute 

hidden_size = hidden_size

layernorm instance-attribute 

layernorm = LayerNorm(
    hidden_size,
    elementwise_affine=elementwise_affine,
    eps=eps,
)

forward_cuda 

forward_cuda(
    x: Tensor, scale: Tensor, shift: Tensor
) -> Tensor

forward_hip 

forward_hip(
    x: Tensor, scale: Tensor, shift: Tensor
) -> Tensor

forward_native 

forward_native(
    x: Tensor, scale: Tensor, shift: Tensor
) -> Tensor

forward_npu 

forward_npu(
    x: Tensor, scale: Tensor, shift: Tensor
) -> Tensor

forward_xpu 

forward_xpu(
    x: Tensor, scale: Tensor, shift: Tensor
) -> Tensor

AdaLayerNormContinuous

Bases: Module

linear instance-attribute 

linear = ReplicatedLinear(
    conditioning_embedding_dim,
    embedding_dim * 2,
    bias=bias,
    return_bias=False,
    quant_config=quant_config,
    prefix=f"{prefix}.linear",
)

norm instance-attribute 

norm = LayerNorm(
    embedding_dim,
    eps=eps,
    elementwise_affine=elementwise_affine,
)

silu instance-attribute 

silu = SiLU()

forward 

forward(
    x: Tensor, conditioning_embedding: Tensor
) -> Tensor

AdaLayerNormZero

Bases: Module

emb instance-attribute 

emb = None

linear instance-attribute 

linear = ReplicatedLinear(
    embedding_dim,
    6 * embedding_dim,
    bias=bias,
    return_bias=False,
    quant_config=quant_config,
    prefix=f"{prefix}.linear",
)

norm instance-attribute 

norm = LayerNorm(
    embedding_dim, elementwise_affine=False, eps=1e-06
)

silu instance-attribute 

silu = SiLU()

forward 

forward(
    x: Tensor, emb: Tensor
) -> tuple[Tensor, Tensor, Tensor, Tensor, Tensor]

AdaLayerNormZeroSingle

Bases: Module

linear instance-attribute 

linear = ReplicatedLinear(
    embedding_dim,
    3 * embedding_dim,
    bias=bias,
    return_bias=False,
    quant_config=quant_config,
    prefix=f"{prefix}.linear",
)

norm instance-attribute 

norm = LayerNorm(
    embedding_dim, elementwise_affine=False, eps=1e-06
)

silu instance-attribute 

silu = SiLU()

forward 

forward(x: Tensor, emb: Tensor) -> tuple[Tensor, Tensor]