o %ݫi@s.dZddlZddlZGdddejjjZdS)zKVanilla Neural Network for simple tests. Authors * Elena Rastorgueva 2020 Ncs,eZdZdZejjddffdd ZZS) VanillaNNaIA simple vanilla Deep Neural Network. Arguments --------- input_shape : tuple Expected shape of the input tensors. activation : torch class A class used for constructing the activation layers. dnn_blocks : int The number of linear neural blocks to include. dnn_neurons : int The number of neurons in the linear layers. Example ------- >>> inputs = torch.rand([10, 120, 60]) >>> model = VanillaNN(input_shape=inputs.shape) >>> outputs = model(inputs) >>> outputs.shape torch.Size([10, 120, 512]) icsHtj|dt|D]}|jtjjj|ddd|j|ddq dS)N) input_shapeTlinear) n_neuronsbias layer_nameact)r)super__init__rangeappendsbnnetrLinear)selfr activation dnn_blocks dnn_neurons block_index __class__V/home/ubuntu/.local/lib/python3.10/site-packages/speechbrain/lobes/models/VanillaNN.pyr #s zVanillaNN.__init__) __name__ __module__ __qualname____doc__torchnn LeakyReLUr __classcell__rrrrr s r)rr speechbrainrr containers Sequentialrrrrrs