/** * 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. */ /*! * \file stateless_random_ops.h * \brief */ #ifndef OPS_BUILT_IN_OP_PROTO_INC_STATELESS_RANDOM_OPS_H_ #define OPS_BUILT_IN_OP_PROTO_INC_STATELESS_RANDOM_OPS_H_ #include "graph/operator.h" #include "graph/operator_reg.h" namespace ge { /** *@brief Draws samples from a multinomial distribution . \n *@par Inputs: include: *@li logits:2-D Tensor with shape [batch_size, num_classes]. Each slice [i, :] *represents the unnormalized log probabilities for all classes. *@li num_samples:0-D. Number of independent samples to draw for each row slice. *@li seed:The seed to generate random . \n *@par Attributes: *output_dtype:Output data type . \n *@par Outputs: *y:Output random number . \n *@see StatelessMultinomial() *@par Third-party framework compatibility *compatible with StatelessMultinomial op of tensorflow */ REG_OP(StatelessMultinomial) .INPUT(logits, TensorType({DT_FLOAT16,DT_FLOAT,DT_DOUBLE})) .INPUT(num_samples, TensorType({DT_INT32})) .INPUT(seed, TensorType({DT_INT32, DT_INT64})) .OUTPUT(y, TensorType({DT_INT32, DT_INT64})) .ATTR(output_dtype, Type, DT_INT64) .OP_END_FACTORY_REG(StatelessMultinomial) /** *@brief Outputs deterministic pseudorandom random integers from a uniform distribution . \n *@par Inputs: *@li shape: The shape of the output tensor. *@li seed: 2 seeds (shape [2]). *@li minval: Minimum value (inclusive, scalar). *@li maxval: Maximum value (exclusive, scalar) . \n *@par Outputs: *y: Returns Random values with specified shape . \n *@par Third-party framework compatibility * Compatible with TensorFlow StatelessRandomUniformInt operator. */ REG_OP(StatelessRandomUniformInt) .INPUT(shape, TensorType({DT_INT32, DT_INT64})) .INPUT(seed, TensorType({DT_INT32, DT_INT64})) .INPUT(minval, TensorType({DT_INT32, DT_INT64})) .INPUT(maxval, TensorType({DT_INT32, DT_INT64})) .OUTPUT(y, TensorType({DT_INT32, DT_INT64})) .OP_END_FACTORY_REG(StatelessRandomUniformInt) } // namespace ge #endif // OPS_BUILT_IN_OP_PROTO_INC_STATELESS_RANDOM_OPS_H_