# tensorplay.functional.quantized_max_pool1d

Source: https://www.tensorplay.cn/docs/generated/tensorplay.functional.quantized_max_pool1d.html

```python
tensorplay.functional.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](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – quantized tensor

- kernel_size ([list](https://docs.python.org/3/builtins/stdtypes.html#list) of [int](https://docs.python.org/3/builtins/functions.html#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  0. Default 1

- ceil_mode ([bool](https://docs.python.org/3/builtins/functions.html#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:

[Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)

Example:

```
>>> qx = tensorplay.quantize_per_tensor(tensorplay.rand(2, 2), 1.5, 3, tensorplay.quint8)
>>> tensorplay.quantized_max_pool1d(qx, [2])
tensor([[0.0000],
        [1.5000]], size=(2, 1), dtype=tensorplay.quint8,
    quantization_scheme=tensorplay.per_tensor_affine, scale=1.5, zero_point=3)
```