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80 lines
2.5 KiB
80 lines
2.5 KiB
/**
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* Copyright 2019-2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef GE_OP_STATELESS_RANDOM_OPS_H
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#define GE_OP_STATELESS_RANDOM_OPS_H
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#include "graph/operator.h"
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#include "graph/operator_reg.h"
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namespace ge {
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/**
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*@brief Draws samples from a multinomial distribution.
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*@par Inputs:
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include: \n
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*@li logits:2-D Tensor with shape [batch_size, num_classes]. Each slice [i, :]\n
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*represents the unnormalized log probabilities for all classes.
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*@li num_samples:0-D. Number of independent samples to draw for each row slice.
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*@li seed:The seed to generate random.
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*@par Attributes:
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*output_dtype:Output data type.
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*@par Outputs:
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*y:Output random number.
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*@see StatelessMultinomial()
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*@par Third-party framework compatibility
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*compatible with StatelessMultinomial op of tensorflow
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*/
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REG_OP(StatelessMultinomial)
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.INPUT(logits, TensorType({DT_FLOAT16,DT_FLOAT,DT_DOUBLE}))
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.INPUT(num_samples, TensorType({DT_INT32}))
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.INPUT(seed, TensorType({DT_INT32, DT_INT64}))
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.OUTPUT(y, TensorType({DT_INT32, DT_INT64}))
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.ATTR(output_dtype, Type, DT_INT64)
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.OP_END_FACTORY_REG(StatelessMultinomial)
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/**
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*@brief Outputs deterministic pseudorandom random integers from a uniform distribution.
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*@par Inputs:
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*@li shape: The shape of the output tensor.
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*@li seed: 2 seeds (shape [2]).
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*@li minval: Minimum value (inclusive, scalar).
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*@li maxval: Maximum value (exclusive, scalar).
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*@par Outputs:
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*y: Returns Random values with specified shape.
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*@par Third-party framework compatibility
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* Compatible with TensorFlow StatelessRandomUniformInt operator.
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*/
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REG_OP(StatelessRandomUniformInt)
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.INPUT(shape, TensorType({DT_INT32, DT_INT64}))
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.INPUT(seed, TensorType({DT_INT32, DT_INT64}))
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.INPUT(minval, TensorType({DT_INT32, DT_INT64}))
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.INPUT(maxval, TensorType({DT_INT32, DT_INT64}))
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.OUTPUT(y, TensorType({DT_INT32, DT_INT64}))
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.OP_END_FACTORY_REG(StatelessRandomUniformInt)
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} // namespace ge
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#endif //GE_OP_STATELESS_RANDOM_OPS_H
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