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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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 np_weibull_op.cc
* \brief Operator for numpy sampling from Weibull distributions
*/
#include "./np_weibull_op.h"
#include "./dist_common.h"
namespace mxnet {
namespace op {
DMLC_REGISTER_PARAMETER(NumpyWeibullParam);
NNVM_REGISTER_OP(_npi_weibull)
.describe("Numpy behavior Weibull")
.set_num_inputs([](const nnvm::NodeAttrs& attrs) {
const NumpyWeibullParam& param = nnvm::get<NumpyWeibullParam>(attrs.parsed);
int num_inputs = 1;
if (param.a.has_value()) {
num_inputs -= 1;
}
return num_inputs;
})
.set_num_outputs(2)
.set_attr<nnvm::FNumVisibleOutputs>("FNumVisibleOutputs",
[](const NodeAttrs& attrs) { return 1; })
.set_attr<nnvm::FListInputNames>("FListInputNames",
[](const NodeAttrs& attrs) {
const NumpyWeibullParam& param =
nnvm::get<NumpyWeibullParam>(attrs.parsed);
int num_inputs = 1;
if (param.a.has_value()) {
num_inputs -= 1;
}
return (num_inputs == 0) ?
std::vector<std::string>() :
std::vector<std::string>{"input1"};
})
.set_attr_parser(ParamParser<NumpyWeibullParam>)
.set_attr<mxnet::FInferShape>("FInferShape", TwoparamsDistOpShape<NumpyWeibullParam>)
.set_attr<nnvm::FInferType>("FInferType",
[](const nnvm::NodeAttrs& attrs,
std::vector<int>* in_attrs,
std::vector<int>* out_attrs) {
(*out_attrs)[0] = mshadow::kFloat32;
(*out_attrs)[1] = mshadow::kFloat32;
return true;
})
.set_attr<FResourceRequest>("FResourceRequest",
[](const nnvm::NodeAttrs& attrs) {
return std::vector<ResourceRequest>{ResourceRequest::kRandom,
ResourceRequest::kTempSpace};
})
.set_attr<FCompute>("FCompute<cpu>", NumpyWeibullForward<cpu>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseInOut{"_backward_broadcast_weibull"})
.add_argument("input1", "NDArray-or-Symbol", "Source input")
.add_arguments(NumpyWeibullParam::__FIELDS__());
NNVM_REGISTER_OP(_backward_broadcast_weibull)
.set_attr<nnvm::TIsBackward>("TIsBackward", true)
.set_attr_parser(ParamParser<NumpyWeibullParam>)
.set_num_inputs([](const nnvm::NodeAttrs& attrs) {
const NumpyWeibullParam& param = nnvm::get<NumpyWeibullParam>(attrs.parsed);
int num_inputs = 5;
if (param.a.has_value())
num_inputs -= 1;
return num_inputs;
})
.set_num_outputs([](const nnvm::NodeAttrs& attrs) {
const NumpyWeibullParam& param = nnvm::get<NumpyWeibullParam>(attrs.parsed);
int num_outputs = 1;
if (param.a.has_value())
num_outputs -= 1;
return num_outputs;
})
.set_attr<FResourceRequest>("FResourceRequest",
[](const NodeAttrs& attrs) {
return std::vector<ResourceRequest>{ResourceRequest::kTempSpace};
})
.set_attr<FCompute>("FCompute<cpu>", WeibullReparamBackward<cpu>)
.add_arguments(NumpyWeibullParam::__FIELDS__());
} // namespace op
} // namespace mxnet