forked from mindspore-Ecosystem/mindspore
fix typesetting issues
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@ -148,14 +148,19 @@ class AdaptiveAvgPool2D(PrimitiveWithInfer):
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Outputs:
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Outputs:
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Tensor, with the same type as the `input_x`.
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Tensor, with the same type as the `input_x`.
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Shape of the output is `input_x_shape[:len(input_x_shape) - len(out_shape)] + out_shape`.
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Shape of the output is `input_x_shape[:len(input_x_shape) - len(out_shape)] + out_shape`.
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If `output_size` contains `None`:
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If `output_size` contains `None`:
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`out_shape = input_x_shape[-2] + output_size[1]`: If `output_size` is `(None, w)`
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`out_shape = output_size[0] + input_x_shape[-1]`: If `output_size` is `(h, None)`
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- `out_shape = input_x_shape[-2] + output_size[1]`: If `output_size` is `(None, w)`
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`out_shape = input_x_shape[-2:]: If output_size` is `(None, None)`
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- `out_shape = output_size[0] + input_x_shape[-1]`: If `output_size` is `(h, None)`
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- `out_shape = input_x_shape[-2:]: If output_size` is `(None, None)`
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If `output_size` does not contain `None`:
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If `output_size` does not contain `None`:
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`out_shape = (h, h)`: If `output_size` is `h`
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`out_shape = (h, w)`: If `output_size` is `(h, w)`
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- `out_shape = (h, h)`: If `output_size` is `h`
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- `out_shape = (h, w)`: If `output_size` is `(h, w)`
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Raises:
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Raises:
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ValueError: If `output_size` is a tuple and if `output_size` length is not 2.
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ValueError: If `output_size` is a tuple and if `output_size` length is not 2.
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