torch.quantized_max_pool2d — PyTorch 2.7 documentation (original) (raw)

torch.quantized_max_pool2d(input, kernel_size, stride=[], padding=0, dilation=1, ceil_mode=False) → Tensor¶

Applies a 2D max pooling over an input quantized tensor composed of several input planes.

Parameters

• input (Tensor) – quantized tensor
• kernel_size (list of int) – the size of the sliding window
• stride (list of int, optional) – the stride of the sliding window
• padding (list of int, optional) – padding to be added on both sides, must be >= 0 and <= kernel_size / 2
• dilation (list of int, optional) – The stride between elements within a sliding window, must be > 0. Default 1
• ceil_mode (bool, optional) – If True, will use ceil instead of floor to compute the output shape. Defaults to False.

Returns

A quantized tensor with max_pool2d applied.

Return type

Tensor

Example:

qx = torch.quantize_per_tensor(torch.rand(2, 2, 2, 2), 1.5, 3, torch.quint8) torch.quantized_max_pool2d(qx, [2,2]) tensor([[[[1.5000]],

    [[1.5000]]],


    [[[0.0000]],

    [[0.0000]]]], size=(2, 2, 1, 1), dtype=torch.quint8,
quantization_scheme=torch.per_tensor_affine, scale=1.5, zero_point=3)