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@ -2288,10 +2288,10 @@ class MirrorPad(PrimitiveWithInfer):
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Inputs:
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- **input_x** (Tensor) - The input tensor.
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- **paddings** (Tensor) - The paddings tensor. The value of `paddings` is a matrix(list),
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and its shape is (N, 2). N is the rank of input data. All elements of paddings
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are int type. For `D` th dimension of input, paddings[D, 0] indicates how many sizes to be
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extended ahead of the `D` th dimension of the input tensor, and paddings[D, 1] indicates
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how many sizes to be extended behind of the `D` th dimension of the input tensor.
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and its shape is (N, 2). N is the rank of input data. All elements of paddings
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are int type. For `D` th dimension of input, paddings[D, 0] indicates how many sizes to be
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extended ahead of the `D` th dimension of the input tensor, and paddings[D, 1] indicates
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how many sizes to be extended behind of the `D` th dimension of the input tensor.
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Outputs:
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Tensor, the tensor after padding.
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