o }oi@sxddlmZmZmZmZddlZddlmZeeeee gej feej dfZ Gdddej Z Gdddej Z dS))CallableListTypeUnionNc seZdZdZ  ddededededed ef fd d Zd ej d ej fddZ e ddedededed e e jf ddZZS)MLPa A Multi-Layer Perceptron (MLP) module. Args: num_input_dims (int): Number of input dimensions. num_output_dims (int): Number of output dimensions. num_hidden_dims (int): Number of hidden dimensions. num_layers (int): Number of layers in the MLP. bias (bool): If True, enables the bias in Linear layers. Default is True. block (BlockBuilder): A callable or class for constructing a block. Default is None. TNnum_input_dimsnum_output_dimsnum_hidden_dims num_layersbiasblockc stg}|tj|||d|tjddtd|dD] }||||||q"|tj|||dt ||_ dS)Nr Tinplace) super__init__appendnnLinearReLUrangeextend build_layer ModuleListnet) selfrrr r r r network_ __class__l/home/ubuntu/.local/lib/python3.10/site-packages/nemo/collections/multimodal/modules/nerf/geometry/layers.pyr#s z MLP.__init__xreturncCs|jD]}||}q|S)z Forward pass through the MLP. Args: x (torch.Tensor): Input tensor. Returns: torch.Tensor: Output tensor. )r)rr#moduler!r!r"forward?s z MLP.forward block_buildercCs4|durtj|||dtjddgS||||dgS)a Build a single layer for the MLP. Args: num_input_dims (int): Number of input dimensions. num_output_dims (int): Number of output dimensions. bias (bool): If True, enables the bias in Linear layers. Default is True. block_builder (BlockBuilder): A callable or class for constructing a block. Default is None. Returns: List[nn.Module]: A list containing the layer's modules. Nr Tr)rrr)rrr r'r!r!r"rMszMLP.build_layer)TN)__name__ __module__ __qualname____doc__intbool BlockBuilderrtorchTensorr& staticmethodrrModuler __classcell__r!r!rr"rs>rcsFeZdZdZd dededeffdd Zdejd ejfd d Z Z S) ResBlockz A residual block module. Args: num_input_dims (int): Number of input dimensions. num_output_dims (int): Number of output dimensions. bias (bool): If True, enables the bias in Linear layers. Default is True. Trrr cs^ttj|||d|_t||_tjdd|_||kr*tj||dd|_ dSd|_ dS)Nr TrF) rrrrdense LayerNormnormSiLU activationskip)rrrr rr!r"rms   zResBlock.__init__r#r$cCsB|}||}||}|jdur||}||7}||}|S)z Forward pass through the residual block. Args: x (torch.Tensor): Input tensor. Returns: torch.Tensor: Output tensor. N)r5r7r:r9)rr#identityoutr!r!r"r&ys     zResBlock.forward)T) r(r)r*r+r,r-rr/r0r&r3r!r!rr"r4cs  r4)typingrrrrr/torch.nnrr,r-r2r.rr4r!r!r!r"s   $M