avg_pool3d¶

dragon.vm.tensorflow.nn.avg_pool3d(
  input,
  ksize,
  strides,
  padding='VALID',
  data_format='NHWC',
  name=None
)[source]¶

Apply the 3d average pooling.

• If data_format is 'NCHW', excepts input shape \((N, C, D, H, W)\), and output shape is \((N, C, D_{\text{out}}, H_{\text{out}}, W_{\text{out}})\).
• If data_format is 'NHWC', excepts input shape \((N, D, H, W, C)\), and output shape is \((N, D_{\text{out}}, H_{\text{out}}, W_{\text{out}}, C)\).
• padding could be 'VALID', 'SAME' or explicit padding size.

Examples:

x = tf.ones((1, 2, 2, 2, 2))
y = tf.nn.avg_pool3d(x, ksize=2, strides=2)
assert y.shape == (1, 1, 1, 1, 2)

Parameters:

• input (dragon.Tensor) – The input tensor.
• ksize (Union[int, Sequence[int]]) – The size of pooling window.
• strides (Union[int, Sequence[int]]) – The stride of pooling window.
• padding (Union[int, Sequence[int], str], optional, default='VALID') – The padding algorithm or size.
• data_format (str, optional, default='NHWC') – 'NCHW' or 'NHWC'.
• name (str, optional) – The operation name.

Returns:

dragon.Tensor – The output tensor.