tflite_micro_person_detection_init

components/tflite_micro/tensorflow/lite/micro/kernels/logical.cc

@@ -0,0 +1,105 @@
+/* Copyright 2019 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/binary_function.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+#include "tensorflow/lite/micro/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace logical {
+namespace {
+
+// Input/output tensor index.
+constexpr int kInputTensor1 = 0;
+constexpr int kInputTensor2 = 1;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus LogicalImpl(TfLiteContext* context, TfLiteNode* node,
+                         bool (*func)(bool, bool)) {
+  const TfLiteEvalTensor* input1 =
+      tflite::micro::GetEvalInput(context, node, kInputTensor1);
+  const TfLiteEvalTensor* input2 =
+      tflite::micro::GetEvalInput(context, node, kInputTensor2);
+  TfLiteEvalTensor* output =
+      tflite::micro::GetEvalOutput(context, node, kOutputTensor);
+
+  if (tflite::micro::HaveSameShapes(input1, input2)) {
+    reference_ops::BinaryFunction<bool, bool, bool>(
+        tflite::micro::GetTensorShape(input1),
+        tflite::micro::GetTensorData<bool>(input1),
+        tflite::micro::GetTensorShape(input2),
+        tflite::micro::GetTensorData<bool>(input2),
+        tflite::micro::GetTensorShape(output),
+        tflite::micro::GetTensorData<bool>(output), func);
+  } else {
+    reference_ops::BroadcastBinaryFunction4DSlow<bool, bool, bool>(
+        tflite::micro::GetTensorShape(input1),
+        tflite::micro::GetTensorData<bool>(input1),
+        tflite::micro::GetTensorShape(input2),
+        tflite::micro::GetTensorData<bool>(input2),
+        tflite::micro::GetTensorShape(output),
+        tflite::micro::GetTensorData<bool>(output), func);
+  }
+
+  return kTfLiteOk;
+}
+
+bool LogicalOr(bool x, bool y) { return x || y; }
+
+TfLiteStatus LogicalOrEval(TfLiteContext* context, TfLiteNode* node) {
+  return LogicalImpl(context, node, LogicalOr);
+}
+
+bool LogicalAnd(bool x, bool y) { return x && y; }
+
+TfLiteStatus LogicalAndEval(TfLiteContext* context, TfLiteNode* node) {
+  return LogicalImpl(context, node, LogicalAnd);
+}
+
+}  // namespace
+}  // namespace logical
+
+TfLiteRegistration Register_LOGICAL_OR() {
+  // Init, Free, Prepare, Eval are satisfying the Interface required by
+  // TfLiteRegistration.
+  return {/*init=*/nullptr,
+          /*free=*/nullptr,
+          /*prepare=*/nullptr,
+          /*invoke=*/logical::LogicalOrEval,
+          /*profiling_string=*/nullptr,
+          /*builtin_code=*/0,
+          /*custom_name=*/nullptr,
+          /*version=*/0};
+}
+
+TfLiteRegistration Register_LOGICAL_AND() {
+  // Init, Free, Prepare, Eval are satisfying the Interface required by
+  // TfLiteRegistration.
+  return {/*init=*/nullptr,
+          /*free=*/nullptr,
+          /*prepare=*/nullptr,
+          /*invoke=*/logical::LogicalAndEval,
+          /*profiling_string=*/nullptr,
+          /*builtin_code=*/0,
+          /*custom_name=*/nullptr,
+          /*version=*/0};
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite