Class DepthwiseConv2d

tensorlayer/layers/convolution/depthwise_conv.py:18–162

Separable/Depthwise Convolutional 2D layer, see `tf.nn.depthwise_conv2d `__. Input: 4-D Tensor (batch, height, width, in_channels). Output: 4-D Tensor (batch, new height, new width, in_channel

class DepthwiseConv2d(Layer):
    """Separable/Depthwise Convolutional 2D layer, see `tf.nn.depthwise_conv2d <https://tensorflow.google.cn/versions/r2.0/api_docs/python/tf/nn/depthwise_conv2d>`__.

    Input:
        4-D Tensor (batch, height, width, in_channels).
    Output:
        4-D Tensor (batch, new height, new width, in_channels * depth_multiplier).

    Parameters
    ------------
    filter_size : tuple of 2 int
        The filter size (height, width).
    strides : tuple of 2 int
        The stride step (height, width).
    act : activation function
        The activation function of this layer.
    padding : str
        The padding algorithm type: "SAME" or "VALID".
    data_format : str
        "channels_last" (NHWC, default) or "channels_first" (NCHW).
    dilation_rate: tuple of 2 int
        The dilation rate in which we sample input values across the height and width dimensions in atrous convolution. If it is greater than 1, then all values of strides must be 1.
    depth_multiplier : int
        The number of channels to expand to.
    W_init : initializer
        The initializer for the weight matrix.
    b_init : initializer or None
        The initializer for the bias vector. If None, skip bias.
    in_channels : int
        The number of in channels.
    name : str
        A unique layer name.

    Examples
    ---------
    With TensorLayer

    >>> net = tl.layers.Input([8, 200, 200, 32], name='input')
    >>> depthwiseconv2d = tl.layers.DepthwiseConv2d(
    ...     filter_size=(3, 3), strides=(1, 1), dilation_rate=(2, 2), act=tf.nn.relu, depth_multiplier=2, name='depthwise'
    ... )(net)
    >>> print(depthwiseconv2d)
    >>> output shape : (8, 200, 200, 64)


    References
    -----------
    - tflearn&#x27;s `grouped_conv_2d <https://github.com/tflearn/tflearn/blob/3e0c3298ff508394f3ef191bcd7d732eb8860b2e/tflearn/layers/conv.py>`__
    - keras&#x27;s `separableconv2d <https://keras.io/layers/convolutional/#separableconv2d>`__

    """

    # https://zhuanlan.zhihu.com/p/31551004  https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/MobileNet.py
    def __init__(
        self,
        filter_size=(3, 3),
        strides=(1, 1),
        act=None,