mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
994f72ee3e
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/15137 Codemod generated with clangr shard mode, 25 files per diff, motivation: https://github.com/pytorch/pytorch/pull/12407 Reviewed By: ezyang Differential Revision: D13419736 fbshipit-source-id: f4ad7b9582c2f809258169b7fef9adbca7063d99
96 lines
2.7 KiB
C++
96 lines
2.7 KiB
C++
/**
|
|
* Copyright (c) 2016-present, Facebook, Inc.
|
|
*
|
|
* 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.
|
|
*/
|
|
|
|
#include "caffe2/operators/stump_func_op.h"
|
|
|
|
namespace caffe2 {
|
|
|
|
template <>
|
|
bool StumpFuncOp<float, float, CPUContext>::RunOnDevice() {
|
|
auto& in = Input(0);
|
|
const float* in_data = in.template data<float>();
|
|
|
|
auto* out = Output(0, in.sizes(), at::dtype<float>());
|
|
float* out_data = out->template mutable_data<float>();
|
|
for (int i = 0; i < in.numel(); i++) {
|
|
out_data[i] = (in_data[i] <= threshold_) ? low_value_ : high_value_;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
template <>
|
|
bool StumpFuncIndexOp<float, int64_t, CPUContext>::RunOnDevice() {
|
|
auto& in = Input(0);
|
|
const float* in_data = in.template data<float>();
|
|
|
|
int lo_cnt = 0;
|
|
for (int i = 0; i < in.numel(); i++) {
|
|
lo_cnt += (in_data[i] <= threshold_);
|
|
}
|
|
auto* out_lo = Output(0, {lo_cnt}, at::dtype<int64_t>());
|
|
auto* out_hi = Output(1, {in.numel() - lo_cnt}, at::dtype<int64_t>());
|
|
int64_t* lo_data = out_lo->template mutable_data<int64_t>();
|
|
int64_t* hi_data = out_hi->template mutable_data<int64_t>();
|
|
int lidx = 0;
|
|
int hidx = 0;
|
|
for (int i = 0; i < in.numel(); i++) {
|
|
if (in_data[i] <= threshold_) {
|
|
lo_data[lidx++] = i;
|
|
} else {
|
|
hi_data[hidx++] = i;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
REGISTER_CPU_OPERATOR(StumpFunc, StumpFuncOp<float, float, CPUContext>);
|
|
|
|
OPERATOR_SCHEMA(StumpFunc)
|
|
.NumInputs(1)
|
|
.NumOutputs(1)
|
|
.Input(0, "X", "tensor of float")
|
|
.Output(0, "Y", "tensor of float")
|
|
.SetDoc(R"DOC(
|
|
Converts each input element into either high_ or low_value
|
|
based on the given threshold.
|
|
)DOC");
|
|
|
|
NO_GRADIENT(StumpFunc);
|
|
|
|
REGISTER_CPU_OPERATOR(
|
|
StumpFuncIndex,
|
|
StumpFuncIndexOp<float, int64_t, CPUContext>);
|
|
|
|
OPERATOR_SCHEMA(StumpFuncIndex)
|
|
.NumInputs(1)
|
|
.NumOutputs(2)
|
|
.Input(0, "X", "tensor of float")
|
|
.Output(
|
|
0,
|
|
"Index_Low",
|
|
"tensor of int64 indices for elements below/equal threshold")
|
|
.Output(
|
|
1,
|
|
"Index_High",
|
|
"tensor of int64 indices for elements above threshold")
|
|
.SetDoc(R"DOC(
|
|
Split the elemnts and return the indices based on the given threshold.
|
|
)DOC");
|
|
|
|
NO_GRADIENT(StumpFuncIndex);
|
|
|
|
} // caffe2
|