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@@ -1129,6 +1129,7 @@ class BatchNorm(PrimitiveWithInfer): |
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Inputs: |
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If `is_training` is False, inputs are Tensors. |
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- **input_x** (Tensor) - Tensor of shape :math:`(N, C)`, with float16 or float32 data type. |
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- **scale** (Tensor) - Tensor of shape :math:`(C,)`, with float16 or float32 data type. |
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- **bias** (Tensor) - Tensor of shape :math:`(C,)`, has the same data type with `scale`. |
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@@ -1136,6 +1137,7 @@ class BatchNorm(PrimitiveWithInfer): |
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- **variance** (Tensor) - Tensor of shape :math:`(C,)`, has the same data type with `mean`. |
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If `is_training` is True, `scale`, `bias`, `mean` and `variance` are Parameters. |
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- **input_x** (Tensor) - Tensor of shape :math:`(N, C)`, with float16 or float32 data type. |
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- **scale** (Parameter) - Parameter of shape :math:`(C,)`, with float16 or float32 data type. |
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- **bias** (Parameter) - Parameter of shape :math:`(C,)`, has the same data type with `scale`. |
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