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Diffstat (limited to 'applications/inference_process/src/inference_process.cc')
-rw-r--r--applications/inference_process/src/inference_process.cc138
1 files changed, 85 insertions, 53 deletions
diff --git a/applications/inference_process/src/inference_process.cc b/applications/inference_process/src/inference_process.cc
index 448e29b..5807530 100644
--- a/applications/inference_process/src/inference_process.cc
+++ b/applications/inference_process/src/inference_process.cc
@@ -28,11 +28,13 @@
#define TENSOR_ARENA_SIZE (1024)
#endif
+using namespace std;
+
__attribute__((section(".bss.NoInit"), aligned(16))) uint8_t inferenceProcessTensorArena[TENSOR_ARENA_SIZE];
namespace {
void print_output_data(TfLiteTensor *output, size_t bytesToPrint) {
- const int numBytesToPrint = std::min(output->bytes, bytesToPrint);
+ const int numBytesToPrint = min(output->bytes, bytesToPrint);
int dims_size = output->dims->size;
printf("{\n");
@@ -64,7 +66,7 @@ bool copyOutput(const TfLiteTensor &src, InferenceProcess::DataPtr &dst) {
return true;
}
- std::copy(src.data.uint8, src.data.uint8 + src.bytes, static_cast<uint8_t *>(dst.data));
+ copy(src.data.uint8, src.data.uint8 + src.bytes, static_cast<uint8_t *>(dst.data));
dst.size = src.bytes;
return false;
@@ -77,11 +79,11 @@ DataPtr::DataPtr(void *data, size_t size) : data(data), size(size) {}
InferenceJob::InferenceJob() : numBytesToPrint(0) {}
-InferenceJob::InferenceJob(const std::string &name,
+InferenceJob::InferenceJob(const string &name,
const DataPtr &networkModel,
- const DataPtr &input,
- const DataPtr &output,
- const DataPtr &expectedOutput,
+ const vector<DataPtr> &input,
+ const vector<DataPtr> &output,
+ const vector<DataPtr> &expectedOutput,
size_t numBytesToPrint) :
name(name),
networkModel(networkModel), input(input), output(output), expectedOutput(expectedOutput),
@@ -130,55 +132,80 @@ bool InferenceProcess::runJob(InferenceJob &job) {
tflite::MicroErrorReporter microErrorReporter;
tflite::ErrorReporter *reporter = &microErrorReporter;
+ // 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) {
- printf("Model provided is schema version %d not equal "
- "to supported version %d.\n",
+ printf("Model provided is schema version %d not equal to supported version %d.\n",
model->version(),
TFLITE_SCHEMA_VERSION);
return true;
}
+ // Create the TFL micro interpreter
tflite::AllOpsResolver resolver;
-
tflite::MicroInterpreter interpreter(model, resolver, inferenceProcessTensorArena, TENSOR_ARENA_SIZE, reporter);
+ // Allocate tensors
TfLiteStatus allocate_status = interpreter.AllocateTensors();
if (allocate_status != kTfLiteOk) {
printf("AllocateTensors failed for inference job: %s\n", job.name.c_str());
return true;
}
- bool inputSizeError = false;
- // TODO: adapt for multiple inputs
- // for (unsigned int i = 0; i < interpreter.inputs_size(); ++i)
- for (unsigned int i = 0; i < 1; ++i) {
- TfLiteTensor *input = interpreter.input(i);
- if (input->bytes != job.input.size) {
- // If input sizes don't match, then we could end up copying
- // uninitialized or partial data.
- inputSizeError = true;
- printf("Allocated size: %d for input: %d doesn't match the "
- "received input size: %d for job: %s\n",
- input->bytes,
- i,
- job.input.size,
- job.name.c_str());
- return true;
+ // Create a filtered list of non empty input tensors
+ vector<TfLiteTensor *> inputTensors;
+ for (size_t i = 0; i < interpreter.inputs_size(); ++i) {
+ TfLiteTensor *tensor = interpreter.input(i);
+
+ if (tensor->bytes > 0) {
+ inputTensors.push_back(tensor);
}
- memcpy(input->data.uint8, job.input.data, input->bytes);
}
- if (inputSizeError) {
+
+ if (job.input.size() != inputTensors.size()) {
+ printf("Number of input buffers does not match number of non empty network tensors. input=%zu, network=%zu\n",
+ job.input.size(),
+ inputTensors.size());
return true;
}
+ // Copy input data
+ for (size_t i = 0; i < inputTensors.size(); ++i) {
+ const DataPtr &input = job.input[i];
+ const TfLiteTensor *tensor = inputTensors[i];
+
+ if (input.size != tensor->bytes) {
+ printf("Input size does not match network size. job=%s, index=%zu, input=%zu, network=%u\n",
+ job.name.c_str(),
+ i,
+ input.size,
+ tensor->bytes);
+ return true;
+ }
+
+ copy(static_cast<char *>(input.data), static_cast<char *>(input.data) + input.size, tensor->data.uint8);
+ }
+
+ // Run the inference
TfLiteStatus invoke_status = interpreter.Invoke();
if (invoke_status != kTfLiteOk) {
printf("Invoke failed for inference job: %s\n", job.name.c_str());
return true;
}
- copyOutput(*interpreter.output(0), job.output);
+ // Copy output data
+ if (job.output.size() > 0) {
+ if (interpreter.outputs_size() != job.output.size()) {
+ printf("Number of outputs mismatch. job=%zu, network=%u\n", job.output.size(), interpreter.outputs_size());
+ return true;
+ }
+
+ for (unsigned i = 0; i < interpreter.outputs_size(); ++i) {
+ if (copyOutput(*interpreter.output(i), job.output[i])) {
+ return true;
+ }
+ }
+ }
if (job.numBytesToPrint > 0) {
// Print all of the output data, or the first NUM_BYTES_TO_PRINT bytes,
@@ -186,6 +213,7 @@ bool InferenceProcess::runJob(InferenceJob &job) {
printf("num_of_outputs: %d\n", interpreter.outputs_size());
printf("output_begin\n");
printf("[\n");
+
for (unsigned int i = 0; i < interpreter.outputs_size(); i++) {
TfLiteTensor *output = interpreter.output(i);
print_output_data(output, job.numBytesToPrint);
@@ -193,44 +221,48 @@ bool InferenceProcess::runJob(InferenceJob &job) {
printf(",\n");
}
}
+
printf("]\n");
printf("output_end\n");
}
- if (job.expectedOutput.data != nullptr) {
- bool outputSizeError = false;
- // TODO: adapt for multiple outputs
- // for (unsigned int i = 0; i < interpreter.outputs_size(); i++)
- for (unsigned int i = 0; i < 1; i++) {
- TfLiteTensor *output = interpreter.output(i);
- if (job.expectedOutput.size != output->bytes) {
- // If the expected output & the actual output size doesn't
- // match, we could end up accessing out-of-bound data.
- // Also there's no need to compare the data, as we know
- // that sizes differ.
- outputSizeError = true;
- printf("Output size: %d for output: %d doesn't match with "
- "the expected output size: %d for job: %s\n",
- output->bytes,
- i,
- job.expectedOutput.size,
- job.name.c_str());
+ if (job.expectedOutput.size() > 0) {
+ if (job.expectedOutput.size() != interpreter.outputs_size()) {
+ printf("Expeded number of output tensors does not match network. job=%s, expected=%zu, network=%zu\n",
+ job.name.c_str(),
+ job.expectedOutput.size(),
+ interpreter.outputs_size());
+ return true;
+ }
+
+ for (unsigned int i = 0; i < interpreter.outputs_size(); i++) {
+ const DataPtr &expected = job.expectedOutput[i];
+ const TfLiteTensor *output = interpreter.output(i);
+
+ if (expected.size != output->bytes) {
+ printf(
+ "Expected tensor size does not match network size. job=%s, index=%u, expected=%zu, network=%zu\n",
+ job.name.c_str(),
+ 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 *>(job.expectedOutput.data))[j]) {
- printf("Output data doesn't match expected output data at index: "
- "%d, expected: %02X actual: %02X",
+ if (output->data.uint8[j] != static_cast<uint8_t *>(expected.data)[j]) {
+ printf("Expected tensor size does not match network size. job=%s, index=%u, offset=%u, "
+ "expected=%02x, network=%02x\n",
+ job.name.c_str(),
+ i,
j,
- (static_cast<uint8_t *>(job.expectedOutput.data))[j],
+ static_cast<uint8_t *>(expected.data)[j],
output->data.uint8[j]);
}
}
}
- if (outputSizeError) {
- return true;
- }
}
+
printf("Finished running job: %s\n", job.name.c_str());
return false;
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-02 22:42:42 +0000