pixelcnn_conv2d_resnet¶
-
tfsnippet.layers.
pixelcnn_conv2d_resnet
(*args, **kwargs)¶ PixelCNN 2D convolutional ResNet block.
Parameters: - input (PixelCNN2DOutput) – The output from the previous PixelCNN layer.
- out_channels (int) – The channel numbers of the output.
- conv_fn – The convolution function for “conv_0” and “conv_1”
convolutional layers. See
resnet_general_block()
. - vertical_kernel_size (int or tuple[int]) – Kernel size over spatial dimensions, for “conv_0” and “conv_1” convolutional layers in the PixelCNN vertical stack.
- horizontal_kernel_size (int or tuple[int]) – Kernel size over spatial dimensions, for “conv_0” and “conv_1” convolutional layers in the PixelCNN horizontal stack.
- strides (int or tuple[int]) – Strides over spatial dimensions, for “conv_0”, “conv_1” and “shortcut” convolutional layers.
- channels_last (bool) – Whether or not the channel axis is the last axis in input? (i.e., the data format is “NHWC”)
- use_shortcut_conv (True or None) – If
True
, force to apply a linear convolution transformation on the shortcut path. IfNone
(by default), only use shortcut if necessary. - shortcut_conv_fn – The convolution function for the “shortcut” convolutional layer. If not specified, use conv_fn.
- shortcut_kernel_size (int or tuple[int]) – Kernel size over spatial dimensions, for the “shortcut” convolutional layer.
- activation_fn – The activation function.
- normalizer_fn – The normalizer function.
- dropout_fn – The dropout function.
- gated (bool) – Whether or not to use gate on the output of “conv_1”? conv_1_output = activation_fn(conv_1_output) * sigmoid(gate).
- gate_sigmoid_bias (Tensor) – The bias added to gate before applying the sigmoid activation.
- use_bias (bool or None) – Whether or not to use bias in “conv_0” and
“conv_1”? If
True
, will always use bias. IfNone
, will use bias only if normalizer_fn is not given. IfFalse
, will never use bias. Default isNone
. - name (str) – Default name of the variable scope. Will be uniquified. If not specified, generate one according to the class name.
- scope (str) – The name of the variable scope.
- **kwargs – Other named arguments passed to “conv_0”, “conv_1” and “shortcut” convolutional layers.
Returns: The PixelCNN layer output.
Return type: