Class Conv3DTranspose
Transposed convolution layer (sometimes called Deconvolution). The need for transposed convolutions generally arises from the desire to use a transformation going in the opposite direction of a normal convolution, i.e., from something that has the shape of the output of some convolution to something that has the shape of its input while maintaining a connectivity pattern that is compatible with said convolution. When using this layer as the first layer in a model, provide the keyword argument input_shape (tuple of integers, does not include the batch axis), e.g. input_shape=(128, 128, 128, 3) for a 128x128x128 volume with 3 channels if data_format="channels_last".
Implements
Inherited Members
Namespace: Keras.Layers
Assembly: Keras.dll
Syntax
public class Conv3DTranspose : BaseLayer, IDisposable
Constructors
| Improve this Doc View SourceConv3DTranspose(Int32, Tuple<Int32, Int32, Int32>, Tuple<Int32, Int32, Int32>, String, Tuple<Int32, Int32, Int32>, String, Tuple<Int32, Int32, Int32>, String, Boolean, String, String, String, String, String, String, String, Shape)
Initializes a new instance of the Conv3DTranspose class.
Declaration
public Conv3DTranspose(int filters, Tuple<int, int, int> kernel_size, Tuple<int, int, int> strides = null, string padding = "valid", Tuple<int, int, int> output_padding = null, string data_format = "channels_last", Tuple<int, int, int> dilation_rate = null, string activation = "", bool use_bias = true, string kernel_initializer = "glorot_uniform", string bias_initializer = "zeros", string kernel_regularizer = "", string bias_regularizer = "", string activity_regularizer = "", string kernel_constraint = "", string bias_constraint = "", Shape input_shape = null)
Parameters
Type | Name | Description |
---|---|---|
System.Int32 | filters | Integer, the dimensionality of the output space (i.e. the number of output filters in the convolution). |
System.Tuple<System.Int32, System.Int32, System.Int32> | kernel_size | An integer or tuple/list of 3 integers, specifying the depth, height and width of the 3D convolution window. Can be a single integer to specify the same value for all spatial dimensions. |
System.Tuple<System.Int32, System.Int32, System.Int32> | strides | An integer or tuple/list of 3 integers, specifying the strides of the convolution along the depth, height and width. Can be a single integer to specify the same value for all spatial dimensions. Specifying any stride value != 1 is incompatible with specifying any dilation_ratevalue != 1. |
System.String | padding | one of "valid" or "same" (case-insensitive). |
System.Tuple<System.Int32, System.Int32, System.Int32> | output_padding | An integer or tuple/list of 3 integers, specifying the amount of padding along the depth, height, and width. Can be a single integer to specify the same value for all spatial dimensions. The amount of output padding along a given dimension must be lower than the stride along that same dimension. If set to None (default), the output shape is inferred. |
System.String | data_format | A string, one of "channels_last" or "channels_first". The ordering of the dimensions in the inputs. "channels_last" corresponds to inputs with shape (batch, depth, height, width, channels) while "channels_first" corresponds to inputs with shape (batch, channels, depth, height, width). It defaults to the image_data_format value found in your Keras config file at ~/.keras/keras.json. If you never set it, then it will be "channels_last". |
System.Tuple<System.Int32, System.Int32, System.Int32> | dilation_rate | an integer or tuple/list of 3 integers, specifying the dilation rate to use for dilated convolution. Can be a single integer to specify the same value for all spatial dimensions. Currently, specifying any dilation_rate value != 1 is incompatible with specifying any stride value != 1. |
System.String | activation | Activation function to use (see activations). If you don't specify anything, no activation is applied (ie. "linear" activation: a(x) = x). |
System.Boolean | use_bias | Boolean, whether the layer uses a bias vector. |
System.String | kernel_initializer | Initializer for the kernel weights matrix (see initializers). |
System.String | bias_initializer | Initializer for the bias vector (see initializers). |
System.String | kernel_regularizer | Regularizer function applied to the kernel weights matrix (see regularizer). |
System.String | bias_regularizer | Regularizer function applied to the bias vector (see regularizer). |
System.String | activity_regularizer | Regularizer function applied to the output of the layer (its "activation"). (see regularizer). |
System.String | kernel_constraint | Constraint function applied to the kernel matrix (see constraints). |
System.String | bias_constraint | Constraint function applied to the bias vector (see constraints). |
Shape | input_shape | 5D tensor with shape: (batch, channels, depth, rows, cols) if data_format is "channels_first" or 5D tensor with shape: (batch, depth, rows, cols, channels) if data_format is "channels_last". |