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- /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
- #ifndef GE_OP_MVN_OPS_H
- #define GE_OP_MVN_OPS_H
-
- #include "graph/operator_reg.h"
-
- namespace ge {
- /**
- *@brief Normalizes the input.
-
- *@par Inputs:
- * One input:
- *x: An NCHW tensor of type float16 or float32.
-
- *@par Attributes:
- *@li normalize_variance: An optional bool specifying whether to normalize the variance, either "true" (default) or "false".
- *@li across_channels: An optional bool specifying whether to perform across-channel MVN, either "true" or "false" (default).
- *@li eps: An optional float32 epsilon for not dividing by zero. Defaults to "1e-9".
-
- *@par Outputs:
- *y: An NCHW tensor of type float16 or float32.
-
- *@attention Constraints:\n
- * The input tensor must have the NCHW format, whose shape length must be 4.
- */
-
- REG_OP(MVN)
- .INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16})) /* "First operand." */
- .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16})) /* "Result, has same element type as inputs" */
- .ATTR(normalize_variance, Bool, true)
- .ATTR(across_channels, Bool, false)
- .ATTR(eps, Float, 1e-9)
- .OP_END_FACTORY_REG(MVN)
- } // namespace ge
-
- #endif // GE_OP_MVN_OPS_H
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