mindspore.ops.AdaptiveAvgPool2D

class mindspore.ops.AdaptiveAvgPool2D(output_size)[source]

2D adaptive average pooling for temporal data.

Refer to mindspore.ops.adaptive_avg_pool2d() for more detail.

Supported Platforms:: GPU

Examples

>>> # case 1: output_size=(None, 2)
>>> input_x = Tensor(np.array([[[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]],
...                             [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]],
...                             [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]]]), mindspore.float32)
>>> adaptive_avg_pool_2d = ops.AdaptiveAvgPool2D((None, 2))
>>> output = adaptive_avg_pool_2d(input_x)
>>> print(output)
[[[[1.5 2.5]
   [4.5 5.5]
   [7.5 8.5]]
  [[1.5 2.5]
   [4.5 5.5]
   [7.5 8.5]]
  [[1.5 2.5]
   [4.5 5.5]
   [7.5 8.5]]]]
>>> # case 2: output_size=2
>>> adaptive_avg_pool_2d = ops.AdaptiveAvgPool2D(2)
>>> output = adaptive_avg_pool_2d(input_x)
>>> print(output)
[[[[3. 4.]
   [6. 7.]]
  [[3. 4.]
   [6. 7.]]
  [[3. 4.]
   [6. 7.]]]]
>>> # case 3: output_size=(1, 2)
>>> adaptive_avg_pool_2d = ops.AdaptiveAvgPool2D((1, 2))
>>> output = adaptive_avg_pool_2d(input_x)
>>> print(output)
[[[[4.5 5.5]]
  [[4.5 5.5]]
  [[4.5 5.5]]]]