mindspore.ops.avg_pool2d
- mindspore.ops.avg_pool2d(x, kernel_size=1, strides=1, pad_mode='valid', data_format='NCHW')[source]
Average pooling operation.
Applies a 2D average pooling over an input Tensor which can be regarded as a composition of 2D input planes. Typically the input is of shape \((N_{in}, C_{in}, H_{in}, W_{in})\), outputs regional average in the \((H_{in}, W_{in})\)-dimension. Given kernel size \((k_{h}, k_{w})\) and strides , the operation is as follows.
\[\text{output}(N_i, C_j, h, w) = \frac{1}{k_{h} * k_{w}} \sum_{m=0}^{k_{h}-1} \sum_{n=0}^{k_{w}-1} \text{input}(N_i, C_j, strides[0] \times h + m, strides[1] \times w + n)\]Warning
Global pooling is supported.
For Ascend, the height of kernel_size and the weight of kernel_size are positive integers within the range [1, 255]. ksize_h * ksize_w < 256.
For Ascend, due to instruction restrictions, the values of ‘strides_h’ and ‘strides_w’ are positive integers within the range [1, 63].
- Parameters
x (Tensor) – Tensor of shape \((N, C_{in}, H_{in}, W_{in})\).
kernel_size (Union[int, tuple[int]]) – The size of kernel used to take the average value. It is an int number that represents height and width of the kernel, or a tuple of two int numbers that represent height and width respectively. Default: 1.
strides (Union[int, tuple[int]]) – The distance of kernel moving, an int number that represents the height and width of movement are both strides, or a tuple of two int numbers that represent height and width of movement respectively. Default: 1.
pad_mode (str) –
The optional value for pad mode, is ‘same’ or ‘valid’. Default: ‘valid’.
same: The height and width of the output are the same as the input divided by ‘strides’ and rounded up.
valid: Returns the output of the valid calculation without filling. Redundant pixels that do not satisfy the calculation will be discarded.
data_format (str) – The format of input and output data. It should be ‘NHWC’ or ‘NCHW’. Default: ‘NCHW’.
- Returns
Tensor, with shape \((N, C_{out}, H_{out}, W_{out})\).
- Raises
TypeError – If kernel_size or strides is neither int nor tuple.
ValueError – If kernel_size or strides is less than 1.
ValueError – If pad_mode is neither ‘valid’ nor ‘same’ with not case sensitive.
ValueError – If data_format is neither ‘NCHW’ nor ‘NHWC’.
ValueError – If length of shape of x is not equal to 4.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> x = Tensor(np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4), mindspore.float32) >>> output = ops.avg_pool2d(x, kernel_size=2, strides=1, pad_mode='VALID') >>> print(output) [[[[ 2.5 3.5 4.5] [ 6.5 7.5 8.5]] [[14.5 15.5 16.5] [18.5 19.5 20.5]] [[26.5 27.5 28.5] [30.5 31.5 32.5]]]]