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@ -36,14 +36,14 @@ class ReduceLogSumExp(Cell):
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The dtype of the tensor to be reduced is number.
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Args:
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keep_dims (bool): If true, keep these reduced dimensions and the length is 1.
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If false, don't keep these dimensions.
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keep_dims (bool): If True, keep these reduced dimensions and the length is 1.
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If False, don't keep these dimensions.
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Default : False.
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axis (Union[int, tuple(int), list(int)]) - The dimensions to reduce. Default: (), reduce all dimensions.
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Only constant value is allowed.
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Inputs:
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- **input_x** (Tensor[Number]) - The input tensor. With float16 or float32 data type.
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- **axis** (Union[int, tuple(int), list(int)]) - The dimensions to reduce. Default: (), reduce all dimensions.
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Only constant value is allowed.
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Outputs:
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Tensor, has the same dtype as the `input_x`.
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@ -57,8 +57,8 @@ class ReduceLogSumExp(Cell):
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Examples:
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>>> input_x = Tensor(np.random.randn(3, 4, 5, 6).astype(np.float32))
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>>> op = nn.ReduceLogSumExp(keep_dims=True)
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>>> output = op(input_x, 1)
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>>> op = nn.ReduceLogSumExp(keep_dims=True, 1)
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>>> output = op(input_x)
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>>> output.shape
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(3, 1, 5, 6)
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"""
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