samples: tflite-micro: Use FVP for test validation

What is changed?
 - Replaced printk with printf in the sample

Why do we need this change?
 - Running the sample with fvp just prints the below output and not
   the complete logs that we expect:
    `sender 0: Sending inference`
   We get the expected output with CONFIG_LOG_IMMEDIATE=y but,
   its not ideal. printf works without the config and plus it
   looks a better fit in the current sample than printk.

This change is validate using `mps3/corstone300/fvp`.

Signed-off-by: Sudan Landge <[email protected]>

Author: wearyzen

samples/modules/tflite-micro/tflm_ethosu/src/inference_process.cpp

@@ -28,7 +28,7 @@ bool copyOutput(const TfLiteTensor &src, InferenceProcess::DataPtr &dst)
 	}
 
 	if (src.bytes > dst.size) {
-		printk("Tensor size mismatch (bytes): actual=%d, expected%d.\n", src.bytes,
+		printf("Tensor size mismatch (bytes): actual=%d, expected%d.\n", src.bytes,
 		       dst.size);
 		return true;
 	}
@@ -112,7 +112,7 @@ bool InferenceProcess::runJob(InferenceJob &job)
 	/* Get model handle and verify that the version is correct */
 	const tflite::Model *model = ::tflite::GetModel(job.networkModel.data);
 	if (model->version() != TFLITE_SCHEMA_VERSION) {
-		printk("Model schema version unsupported: version=%" PRIu32 ", supported=%d.\n",
+		printf("Model schema version unsupported: version=%" PRIu32 ", supported=%d.\n",
 		       model->version(), TFLITE_SCHEMA_VERSION);
 		return true;
 	}
@@ -126,12 +126,12 @@ bool InferenceProcess::runJob(InferenceJob &job)
 	/* Allocate tensors */
 	TfLiteStatus allocate_status = interpreter.AllocateTensors();
 	if (allocate_status != kTfLiteOk) {
-		printk("Failed to allocate tensors for inference. job=%p\n", &job);
+		printf("Failed to allocate tensors for inference. job=%p\n", &job);
 		return true;
 	}
 
 	if (job.input.size() != interpreter.inputs_size()) {
-		printk("Number of job and network inputs do not match. input=%zu, network=%zu\n",
+		printf("Number of job and network inputs do not match. input=%zu, network=%zu\n",
 		       job.input.size(), interpreter.inputs_size());
 		return true;
 	}
@@ -142,7 +142,7 @@ bool InferenceProcess::runJob(InferenceJob &job)
 		const TfLiteTensor *tensor = interpreter.input(i);
 
 		if (input.size != tensor->bytes) {
-			printk("Input tensor size mismatch. index=%zu, input=%zu, network=%u\n", i,
+			printf("Input tensor size mismatch. index=%zu, input=%zu, network=%u\n", i,
 			       input.size, tensor->bytes);
 			return true;
 		}
@@ -154,14 +154,14 @@ bool InferenceProcess::runJob(InferenceJob &job)
 	/* Run the inference */
 	TfLiteStatus invoke_status = interpreter.Invoke();
 	if (invoke_status != kTfLiteOk) {
-		printk("Invoke failed for inference. job=%s\n", job.name.c_str());
+		printf("Invoke failed for inference. job=%s\n", job.name.c_str());
 		return true;
 	}
 
 	/* Copy output data */
 	if (job.output.size() > 0) {
 		if (interpreter.outputs_size() != job.output.size()) {
-			printk("Number of job and network outputs do not match. job=%zu, network=%u\n",
+			printf("Number of job and network outputs do not match. job=%zu, network=%u\n",
 			       job.output.size(), interpreter.outputs_size());
 			return true;
 		}
@@ -175,7 +175,7 @@ bool InferenceProcess::runJob(InferenceJob &job)
 
 	if (job.expectedOutput.size() > 0) {
 		if (job.expectedOutput.size() != interpreter.outputs_size()) {
-			printk("Number of job and network expected outputs do not match. job=%zu, network=%zu\n",
+			printf("Number of job and network expected outputs do not match. job=%zu, network=%zu\n",
 			       job.expectedOutput.size(), interpreter.outputs_size());
 			return true;
 		}
@@ -185,15 +185,15 @@ bool InferenceProcess::runJob(InferenceJob &job)
 			const TfLiteTensor *output = interpreter.output(i);
 
 			if (expected.size != output->bytes) {
-				printk("Expected output tensor size mismatch. index=%u, expected=%zu, network=%zu\n",
+				printf("Expected output tensor size mismatch. index=%u, expected=%zu, network=%zu\n",
 				       i, expected.size, output->bytes);
 				return true;
 			}
 
 			for (unsigned int j = 0; j < output->bytes; ++j) {
 				if (output->data.uint8[j] !=
 				    static_cast<uint8_t *>(expected.data)[j]) {
-					printk("Expected output tensor data mismatch. index=%u, offset=%u, expected=%02x, network=%02x\n",
+					printf("Expected output tensor data mismatch. index=%u, offset=%u, expected=%02x, network=%02x\n",
 					       i, j, static_cast<uint8_t *>(expected.data)[j],
 					       output->data.uint8[j]);
 					return true;

samples/modules/tflite-micro/tflm_ethosu/src/main.cpp

@@ -108,7 +108,7 @@ void *allocateHeap(const size_t size)
 	uint8_t *buf = static_cast<uint8_t *>(k_malloc(size));
 
 	if ((buf == nullptr) || (heap == nullptr)) {
-		printk("Heap allocation failed. heap=%p, buf=%p, size=%zu\n", heap, buf, size);
+		printf("Heap allocation failed. heap=%p, buf=%p, size=%zu\n", heap, buf, size);
 		exit(1);
 	}
 
@@ -133,17 +133,17 @@ void inferenceProcessTask(void *_name, void *heap, void *_params)
 		xInferenceJob *job =
 			static_cast<xInferenceJob *>(k_queue_get(params->queueHandle, Z_FOREVER));
 
-		printk("%s: Received inference job. job=%p\n", name->c_str(), job);
+		printf("%s: Received inference job. job=%p\n", name->c_str(), job);
 
 		/* Run inference */
 		job->status = inferenceProcess.runJob(*job);
 
-		printk("%s: Sending inference response. job=%p\n", name->c_str(), job);
+		printf("%s: Sending inference response. job=%p\n", name->c_str(), job);
 
 		/* Return inference message */
 		int ret = k_queue_alloc_append(job->responseQueue, job);
 		if (0 != ret) {
-			printk("%s: Failed to send message\n", name->c_str());
+			printf("%s: Failed to send message\n", name->c_str());
 			exit(1);
 		}
 	}
@@ -177,13 +177,13 @@ void inferenceSenderTask(void *_name, void *heap, void *_queue)
 				    { DataPtr(expectedOutputData, sizeof(expectedOutputData)) },
 				    &senderQueue);
 
-		printk("%s: Sending inference. job=%p, name=%s\n", name->c_str(), &job,
+		printf("%s: Sending inference. job=%p, name=%s\n", name->c_str(), &job,
 		       job.name.c_str());
 
 		/* Queue job */
 		ret = k_queue_alloc_append(inferenceQueue, &job);
 		if (0 != ret) {
-			printk("%s: Failed to send message\n", name->c_str());
+			printf("%s: Failed to send message\n", name->c_str());
 			exit(1);
 		}
 	}
@@ -193,7 +193,7 @@ void inferenceSenderTask(void *_name, void *heap, void *_queue)
 		xInferenceJob *job =
 			static_cast<xInferenceJob *>(k_queue_get(&senderQueue, Z_FOREVER));
 
-		printk("%s: Received job response. job=%p, status=%u\n", name->c_str(), job,
+		printf("%s: Received job response. job=%p, status=%u\n", name->c_str(), job,
 		       job->status);
 
 		totalCompletedJobs++;
@@ -229,7 +229,7 @@ int main()
 		const size_t stackSize = 2048;
 		k_thread_stack_t *stack = static_cast<k_thread_stack_t *>(k_malloc(stackSize));
 		if (stack == nullptr) {
-			printk("Failed to allocate stack to 'inferenceSenderTask%i'\n", n);
+			printf("Failed to allocate stack to 'inferenceSenderTask%i'\n", n);
 			exit(1);
 		}
 
@@ -239,7 +239,7 @@ int main()
 		thread.id = k_thread_create(&thread.thread, stack, stackSize, inferenceSenderTask,
 					    name, heapPtr, &inferenceQueue, 3, 0, K_FOREVER);
 		if (thread.id == 0) {
-			printk("Failed to create 'inferenceSenderTask%i'\n", n);
+			printf("Failed to create 'inferenceSenderTask%i'\n", n);
 			exit(1);
 		}
 
@@ -252,7 +252,7 @@ int main()
 		const size_t stackSize = 8192;
 		k_thread_stack_t *stack = static_cast<k_thread_stack_t *>(k_malloc(stackSize));
 		if (stack == nullptr) {
-			printk("Failed to allocate stack to 'inferenceSenderTask%i'\n", n);
+			printf("Failed to allocate stack to 'inferenceSenderTask%i'\n", n);
 			exit(1);
 		}
 
@@ -265,7 +265,7 @@ int main()
 		thread.id = k_thread_create(&thread.thread, stack, stackSize, inferenceProcessTask,
 					    name, heapPtr, &taskParam, 2, 0, K_FOREVER);
 		if (thread.id == 0) {
-			printk("Failed to create 'inferenceProcessTask%i'\n", n);
+			printf("Failed to create 'inferenceProcessTask%i'\n", n);
 			exit(1);
 		}
 
@@ -283,7 +283,7 @@ int main()
 	/* Safety belt */
 	k_thread_suspend(k_current_get());
 
-	printk("Zephyr application failed to initialise \n");
+	printf("Zephyr application failed to initialise \n");
 
 	return 1;
 }