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Fix error reporter macro to allow passing a reference to error reporter.

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PiperOrigin-RevId: 306892030
Change-Id: I6ece6b02df56b593318724c318d20beb13d04e79
This commit is contained in:
Nat Jeffries 2020-04-16 11:52:52 -07:00 committed by TensorFlower Gardener
parent 3cc01a59a6
commit cafdb61a56
3 changed files with 9 additions and 11 deletions
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6
tensorflow/lite/core/api/error_reporter.h
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@ -48,9 +48,9 @@ class ErrorReporter {
// reduce binary size, define TF_LITE_STRIP_ERROR_STRINGS when compiling and
// every call will be stubbed out, taking no memory.
#ifndef TF_LITE_STRIP_ERROR_STRINGS
#define TF_LITE_REPORT_ERROR(reporter, ...) \
do { \
reporter->Report(__VA_ARGS__); \
#define TF_LITE_REPORT_ERROR(reporter, ...) \
do { \
static_cast<tflite::ErrorReporter*>(reporter)->Report(__VA_ARGS__); \
} while (false)
#else // TF_LITE_STRIP_ERROR_STRINGS
#define TF_LITE_REPORT_ERROR(reporter, ...)

7
tensorflow/lite/micro/benchmarks/conv_benchmark.cc
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@ -103,8 +103,7 @@ TfLiteStatus ValidateConvGoldens(TfLiteTensor* tensors, int tensors_size,
} // namespace tflite
int main() {
tflite::MicroErrorReporter micro_reporter;
tflite::ErrorReporter* reporter = &micro_reporter;
tflite::MicroErrorReporter reporter;
const int input_shape[] = {4, 1, 1, 1, 32};
const int filter_shape[] = {4, 32, 1, 1, 32};
const int bias_shape[] = {1, 32};
@ -231,9 +230,9 @@ int main() {
const int num_tensors = sizeof(tensors) / sizeof(TfLiteTensor);
TfLiteStatus status = tflite::testing::ValidateConvGoldens(
tensors, num_tensors, &conv_params, kQuantizationTolerance,
output_dims_count, golden_quantized, reporter);
output_dims_count, golden_quantized, &reporter);
if (status != kTfLiteOk) {
TF_LITE_REPORT_ERROR(reporter, "Model invoke failed\n");
TF_LITE_REPORT_ERROR(&reporter, "Model invoke failed\n");
}
return 0;
}

7
tensorflow/lite/micro/benchmarks/depthwise_conv_benchmark.cc
View File

@ -116,8 +116,7 @@ TfLiteStatus ValidateDepthwiseConvGoldens(TfLiteTensor* tensors,
} // namespace tflite
int main() {
tflite::MicroErrorReporter micro_reporter;
tflite::ErrorReporter* reporter = &micro_reporter;
tflite::MicroErrorReporter reporter;
const int input_elements = 32 * 4;
const int filter_elements = 32 * 4;
const int bias_elements = 32;
@ -242,9 +241,9 @@ int main() {
constexpr int kQuantizationTolerance = 1;
TfLiteStatus status = tflite::testing::ValidateDepthwiseConvGoldens(
tensors, kTensorsSize, kTfLiteActNone, kQuantizationTolerance,
output_elements, golden_quantized, reporter);
output_elements, golden_quantized, &reporter);
if (status != kTfLiteOk) {
TF_LITE_REPORT_ERROR(reporter, "Model invoke failed\n");
TF_LITE_REPORT_ERROR(&reporter, "Model invoke failed\n");
}
return 0;
}