Add logistic kernel for Kelvin
Change-Id: I9e36fea5d4b32d6ac03a3d2f78c7362563bd276e
diff --git a/tensorflow/lite/micro/kernels/kelvin/logistic.cc b/tensorflow/lite/micro/kernels/kelvin/logistic.cc
new file mode 100644
index 0000000..974ef12
--- /dev/null
+++ b/tensorflow/lite/micro/kernels/kelvin/logistic.cc
@@ -0,0 +1,112 @@
+/* Copyright 2021 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/kernels/internal/reference/integer_ops/logistic.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/reference/logistic.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+#include "tensorflow/lite/micro/kernels/kernel_util.h"
+#include "tensorflow/lite/micro/kernels/logistic.h"
+#include "tensorflow/lite/micro/micro_log.h"
+#include "tflm/opt/opt.h"
+
+namespace tflite {
+namespace {
+
+void* LogisticInit(TfLiteContext* context, const char* buffer, size_t length) {
+ TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
+ return context->AllocatePersistentBuffer(context, sizeof(OpDataLogistic));
+}
+
+TfLiteStatus LogisticEval(TfLiteContext* context, TfLiteNode* node) {
+ const TfLiteEvalTensor* input =
+ tflite::micro::GetEvalInput(context, node, kLogisticInputTensor);
+ TfLiteEvalTensor* output =
+ tflite::micro::GetEvalOutput(context, node, kLogisticOutputTensor);
+
+ TFLITE_DCHECK(node->user_data != nullptr);
+ OpDataLogistic* data = static_cast<OpDataLogistic*>(node->user_data);
+
+ if (input->type == kTfLiteFloat32) {
+ switch (output->type) {
+ case kTfLiteFloat32: {
+ reference_ops::Logistic(tflite::micro::GetTensorShape(input),
+ tflite::micro::GetTensorData<float>(input),
+ tflite::micro::GetTensorShape(output),
+ tflite::micro::GetTensorData<float>(output));
+ return kTfLiteOk;
+ }
+ default:
+ MicroPrintf("Input %s, output %s not supported.",
+ TfLiteTypeGetName(input->type),
+ TfLiteTypeGetName(output->type));
+ return kTfLiteError;
+ }
+ } else if (input->type == kTfLiteInt16) {
+ switch (output->type) {
+ case kTfLiteInt16: {
+ reference_integer_ops::Logistic(
+ data->input_multiplier, data->input_left_shift,
+ NumElements(input->dims),
+ tflite::micro::GetTensorData<int16_t>(input),
+ tflite::micro::GetTensorData<int16_t>(output));
+ return kTfLiteOk;
+ }
+ default:
+ MicroPrintf("Input %s, output %s not supported.",
+ TfLiteTypeGetName(input->type),
+ TfLiteTypeGetName(output->type));
+ return kTfLiteError;
+ }
+ } else if (input->type == kTfLiteInt8) {
+ switch (output->type) {
+ case kTfLiteInt8: {
+ kelvin::opt::LogisticS8(
+ data->input_zero_point, data->input_range_radius,
+ data->input_multiplier, data->input_left_shift,
+ NumElements(input->dims),
+ tflite::micro::GetTensorData<int8_t>(input),
+ tflite::micro::GetTensorData<int8_t>(output));
+ return kTfLiteOk;
+ }
+ default:
+ MicroPrintf("Input %s, output %s not supported.",
+ TfLiteTypeGetName(input->type),
+ TfLiteTypeGetName(output->type));
+ return kTfLiteError;
+ }
+ } else {
+ // TODO(b/141211002): Also support other data types once we have supported
+ // temporary tensors in TFLM.
+ MicroPrintf("Input %s, output %s not supported.",
+ TfLiteTypeGetName(input->type),
+ TfLiteTypeGetName(output->type));
+ return kTfLiteError;
+ }
+ return kTfLiteOk;
+}
+
+} // namespace
+
+TFLMRegistration Register_LOGISTIC() {
+ return tflite::micro::RegisterOp(LogisticInit, LogisticPrepare, LogisticEval);
+}
+} // namespace tflite
