Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/source/use_case/inference_runner/src/UseCaseHandler.cc b/source/use_case/inference_runner/src/UseCaseHandler.cc
new file mode 100644
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+++ b/source/use_case/inference_runner/src/UseCaseHandler.cc
@@ -0,0 +1,88 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * 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 "UseCaseHandler.hpp"
+
+#include "TestModel.hpp"
+#include "UseCaseCommonUtils.hpp"
+#include "hal.h"
+
+#include <cstdlib>
+
+namespace arm {
+namespace app {
+
+ bool RunInferenceHandler(ApplicationContext& ctx)
+ {
+ auto& platform = ctx.Get<hal_platform&>("platform");
+ auto& model = ctx.Get<Model&>("model");
+
+ constexpr uint32_t dataPsnTxtInfStartX = 150;
+ constexpr uint32_t dataPsnTxtInfStartY = 40;
+
+ if (!model.IsInited()) {
+ printf_err("Model is not initialised! Terminating processing.\n");
+ return false;
+ }
+
+ const size_t numInputs = model.GetNumInputs();
+
+ /* Populate each input tensor with random data. */
+ for (size_t inputIndex = 0; inputIndex < numInputs; inputIndex++) {
+
+ TfLiteTensor* inputTensor = model.GetInputTensor(inputIndex);
+
+ debug("Populating input tensor %zu@%p\n", inputIndex, inputTensor);
+ debug("Total input size to be populated: %zu\n", inputTensor->bytes);
+
+ /* Create a random input. */
+ if (inputTensor->bytes > 0) {
+
+ uint8_t* tData = tflite::GetTensorData<uint8_t>(inputTensor);
+
+ for (size_t j = 0; j < inputTensor->bytes; ++j) {
+ tData[j] = static_cast<uint8_t>(std::rand() & 0xFF);
+ }
+ }
+ }
+
+ /* Strings for presentation/logging. */
+ std::string str_inf{"Running inference... "};
+
+ /* Display message on the LCD - inference running. */
+ platform.data_psn->present_data_text(
+ str_inf.c_str(), str_inf.size(),
+ dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0);
+
+ RunInference(platform, model);
+
+ /* Erase. */
+ str_inf = std::string(str_inf.size(), ' ');
+ platform.data_psn->present_data_text(
+ str_inf.c_str(), str_inf.size(),
+ dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0);
+
+#if VERIFY_TEST_OUTPUT
+ for (size_t outputIndex = 0; outputIndex < model.GetNumOutputs(); outputIndex++) {
+ arm::app::DumpTensor(model.GetOutputTensor(outputIndex));
+ }
+#endif /* VERIFY_TEST_OUTPUT */
+
+ return true;
+ }
+
+} /* namespace app */
+} /* namespace arm */