avg_pool3d¶

class torch.nn.quantized.functional.avg_pool3d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True, divisor_override=None)[source]

Applies 3D average-pooling operation in $kD \ times kH \times kW$ regions by step size $sD \times sH \times sW$ steps. The number of output features is equal to the number of input planes.

Note

The input quantization parameters propagate to the output.

Parameters
• input – quantized input tensor $(\text{minibatch} , \text{in\_channels} , iH , iW)$

• kernel_size – size of the pooling region. Can be a single number or a tuple (kD, kH, kW)

• stride – stride of the pooling operation. Can be a single number or a tuple (sD, sH, sW). Default: kernel_size

• ceil_mode – when True, will use ceil instead of floor in the formula to compute the output shape. Default: False
• count_include_pad – when True, will include the zero-padding in the averaging calculation. Default: True