debug

Author: winskuo-quic

examples/qualcomm/oss_scripts/llama/runner/runner.cpp

@@ -34,7 +34,9 @@ namespace example {
 
 namespace {
 static constexpr auto kTopp = 0.9f;
-void printReport(const Runner::Stats& stats, const std::string& performance_output_path);
+void printReport(
+    const Runner::Stats& stats,
+    const std::string& performance_output_path);
 std::string statsToJsonString(const Runner::Stats& stats);
 } // namespace
 
@@ -463,7 +465,9 @@ Error Runner::generate(
 }
 
 namespace {
-void printReport(const Runner::Stats& stats, const std::string& performance_output_path) {
+void printReport(
+    const Runner::Stats& stats,
+    const std::string& performance_output_path) {
   printf("PyTorchObserver %s\n", statsToJsonString(stats).c_str());
 
   ET_LOG(
@@ -524,7 +528,7 @@ void printReport(const Runner::Stats& stats, const std::string& performance_outp
 
   // For now, we just print the total inference time for CI, can save more info
   // in future if needed.
-  
+
   std::ofstream outfile(performance_output_path.c_str());
   if (outfile.is_open()) {
     double num_tok = (stats.num_generated_tokens) /

examples/qualcomm/scripts/mobilebert_fine_tune.py

@@ -169,7 +169,7 @@ def get_fine_tuned_mobilebert(artifacts_dir, pretrained_weight, batch_size):
     dataset_train = TensorDataset(input_ids_train, attention_masks_train, labels_train)
     dataset_val = TensorDataset(input_ids_val, attention_masks_val, labels_val)
 
-    epochs = 1 # Revert this later
+    epochs = 1  # Revert this later
     dataloader_train = DataLoader(
         dataset_train,
         sampler=RandomSampler(dataset_train),

examples/qualcomm/scripts/wav2letter.py

@@ -67,6 +67,9 @@ def collate_fun(batch):
     )
     # prepare input data
     inputs, targets, input_list = [], [], ""
+    import logging
+    import torchaudio
+    logging.warning(f"Checking available backends: ", torchaudio.list_audio_backends())
     for wave, label in data_loader:
         for index in range(data_size):
             # reshape input tensor to NCHW

install_requirements.py

@@ -85,7 +85,7 @@ def install_requirements(use_pytorch_nightly):
     ]
 
     EXAMPLES_REQUIREMENTS = [
-        f"torchaudio==2.6.0.{NIGHTLY_VERSION}" if use_pytorch_nightly else "torchaudio",
+        f"torchaudio==2.6.0.{NIGHTLY_VERSION}",
     ]
 
     # Assemble the list of requirements to actually install.