torch.quantized_max_pool1d — PyTorch 2.5 documentation (original) (raw)
torch.quantized_max_pool1d(input, kernel_size, stride=[], padding=0, dilation=1, ceil_mode=False) → Tensor¶
Applies a 1D 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_pool1d applied.
Return type
Example:
qx = torch.quantize_per_tensor(torch.rand(2, 2), 1.5, 3, torch.quint8) torch.quantized_max_pool1d(qx, [2]) tensor([[0.0000], [1.5000]], size=(2, 1), dtype=torch.quint8, quantization_scheme=torch.per_tensor_affine, scale=1.5, zero_point=3)