tf.layers.conv3d_transpose

tf.layers.conv3d_transpose

tf.layers.conv3d_transpose

conv3d_transpose(
    inputs,
    filters,
    kernel_size,
    strides=(1, 1, 1),
    padding='valid',
    data_format='channels_last',
    activation=None,
    use_bias=True,
    kernel_initializer=None,
    bias_initializer=tf.zeros_initializer(),
    kernel_regularizer=None,
    bias_regularizer=None,
    activity_regularizer=None,
    trainable=True,
    name=None,
    reuse=None
)

Defined in tensorflow/python/layers/convolutional.py.

Functional interface for transposed 3D convolution layer.

Arguments:

• inputs: Input tensor.
• filters: Integer, the dimensionality of the output space (i.e. the number of filters in the convolution).
• kernel_size: A tuple or list of 3 positive integers specifying the spatial dimensions of of the filters. Can be a single integer to specify the same value for all spatial dimensions.
• strides: A tuple or list of 3 positive integers specifying the strides of the convolution. Can be a single integer to specify the same value for all spatial dimensions.
• padding: one of "valid" or "same" (case-insensitive).
• data_format: A string, one of channels_last (default) or channels_first. The ordering of the dimensions in the inputs. channels_last corresponds to inputs with shape (batch, height, width, channels) while channels_first corresponds to inputs with shape (batch, channels, height, width).
• activation: Activation function. Set it to None to maintain a linear activation.
• use_bias: Boolean, whether the layer uses a bias.
• kernel_initializer: An initializer for the convolution kernel.
• bias_initializer: An initializer for the bias vector. If None, no bias will be applied.
• kernel_regularizer: Optional regularizer for the convolution kernel.
• bias_regularizer: Optional regularizer for the bias vector.
• activity_regularizer: Regularizer function for the output.
• trainable: Boolean, if True also add variables to the graph collection GraphKeys.TRAINABLE_VARIABLES (see tf.Variable).
• name: A string, the name of the layer.
• reuse: Boolean, whether to reuse the weights of a previous layer by the same name.

Returns:

Output tensor.