90 lines
3.0 KiB
C++
90 lines
3.0 KiB
C++
/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
|
|
|
|
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 "tensorflow/lite/c/common.h"
|
|
#include "tensorflow/lite/kernels/internal/reference/reference_ops.h"
|
|
#include "tensorflow/lite/kernels/internal/tensor.h"
|
|
#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
|
|
#include "tensorflow/lite/kernels/kernel_util.h"
|
|
|
|
namespace tflite {
|
|
namespace ops {
|
|
namespace builtin {
|
|
namespace exp {
|
|
|
|
// This file has reference implementation of Exp.
|
|
enum KernelType {
|
|
kReference,
|
|
};
|
|
|
|
struct ExpContext {
|
|
ExpContext(TfLiteContext* context, TfLiteNode* node) {
|
|
input = GetInput(context, node, 0);
|
|
output = GetOutput(context, node, 0);
|
|
}
|
|
const TfLiteTensor* input;
|
|
TfLiteTensor* output;
|
|
};
|
|
|
|
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
|
|
TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
|
|
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
|
|
|
|
ExpContext op_context(context, node);
|
|
TfLiteIntArray* output_dims = TfLiteIntArrayCopy(op_context.input->dims);
|
|
op_context.output->type = op_context.input->type;
|
|
return context->ResizeTensor(context, op_context.output, output_dims);
|
|
}
|
|
|
|
template <KernelType kernel_type>
|
|
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
|
|
ExpContext op_context(context, node);
|
|
|
|
#define TF_LITE_EXP(kernel_type, data_type) \
|
|
kernel_type::Exp<data_type>(GetTensorData<data_type>(op_context.input), \
|
|
NumElements(op_context.input), \
|
|
GetTensorData<data_type>(op_context.output))
|
|
|
|
// TODO(kanlig): supports half, bfloat16, float64, complex64, and complex128.
|
|
if (kernel_type == kReference) {
|
|
switch (op_context.input->type) {
|
|
case kTfLiteFloat32:
|
|
TF_LITE_EXP(reference_ops, float);
|
|
break;
|
|
default:
|
|
context->ReportError(context,
|
|
"Type %d is currently not supported by Exp.",
|
|
op_context.input->type);
|
|
return kTfLiteError;
|
|
}
|
|
}
|
|
#undef TF_LITE_EXP
|
|
return kTfLiteOk;
|
|
}
|
|
|
|
} // namespace exp
|
|
|
|
TfLiteRegistration* Register_EXP_REF() {
|
|
static TfLiteRegistration r = {nullptr, nullptr, exp::Prepare,
|
|
exp::Eval<exp::kReference>};
|
|
return &r;
|
|
}
|
|
|
|
// TODO(kanlig): add optimized implementation of Exp.
|
|
TfLiteRegistration* Register_EXP() { return Register_EXP_REF(); }
|
|
|
|
} // namespace builtin
|
|
} // namespace ops
|
|
} // namespace tflite
|