cnns

conv_blocks

parts.cnns.conv_blocks.conv_actv(layer_type, name, inputs, filters, kernel_size, activation_fn, strides, padding, regularizer, training, data_format, dilation=1)

Helper function that applies convolution and activation. :param layer_type: the following types are supported

‘conv1d’, ‘conv2d’

parts.cnns.conv_blocks.conv_bn_actv(layer_type, name, inputs, filters, kernel_size, activation_fn, strides, padding, regularizer, training, data_format, bn_momentum, bn_epsilon, dilation=1)

Helper function that applies convolution, batch norm and activation. :param layer_type: the following types are supported

‘conv1d’, ‘conv2d’

parts.cnns.conv_blocks.conv_bn_res_bn_actv(layer_type, name, inputs, res_inputs, filters, kernel_size, activation_fn, strides, padding, regularizer, training, data_format, bn_momentum, bn_epsilon, dilation=1, drop_block_prob=0.0, drop_block=False)

parts.cnns.conv_blocks.conv_in_actv(layer_type, name, inputs, filters, kernel_size, activation_fn, strides, padding, regularizer, training, data_format, dilation=1)

Helper function that applies convolution, instance norm and activation. :param layer_type: the following types are supported

‘conv1d’, ‘conv2d’

parts.cnns.conv_blocks.conv_ln_actv(layer_type, name, inputs, filters, kernel_size, activation_fn, strides, padding, regularizer, training, data_format, dilation=1)

Helper function that applies convolution, layer norm and activation. :param layer_type: the following types are supported

‘conv1d’, ‘conv2d’