diff --git a/examples/onnxrt/nlp/huggingface_model/token_classification/layoutlmv2/quantization/ptq_dynamic/main.py b/examples/onnxrt/nlp/huggingface_model/token_classification/layoutlmv2/quantization/ptq_dynamic/main.py
index 95a49ce37ab..c7cf936270d 100644
--- a/examples/onnxrt/nlp/huggingface_model/token_classification/layoutlmv2/quantization/ptq_dynamic/main.py
+++ b/examples/onnxrt/nlp/huggingface_model/token_classification/layoutlmv2/quantization/ptq_dynamic/main.py
@@ -216,8 +216,6 @@ def _process_dataset(self):
self.label = []
self.onnx_inputs = []
for inputs in self.dataset:
- # import pdb;
- # pdb.set_trace()
onnx_inputs = []
has_labels = all(inputs.get(k) is not None for k in self.label_names)
if has_labels:
@@ -237,8 +235,6 @@ def _process_dataset(self):
}
"""
for key in self.onnx_input_names:
- # import pdb;
- # pdb.set_trace()
if key in inputs:
# onnx_inputs[key] = np.array([inputs[key]])
onnx_inputs.append(np.array(inputs[key]))
diff --git a/examples/onnxrt/nlp/huggingface_model/token_classification/layoutlmv2/quantization/ptq_static/main.py b/examples/onnxrt/nlp/huggingface_model/token_classification/layoutlmv2/quantization/ptq_static/main.py
index b3de22ac766..5540f4c002d 100644
--- a/examples/onnxrt/nlp/huggingface_model/token_classification/layoutlmv2/quantization/ptq_static/main.py
+++ b/examples/onnxrt/nlp/huggingface_model/token_classification/layoutlmv2/quantization/ptq_static/main.py
@@ -216,8 +216,6 @@ def _process_dataset(self):
self.label = []
self.onnx_inputs = []
for inputs in self.dataset:
- # import pdb;
- # pdb.set_trace()
onnx_inputs = []
has_labels = all(inputs.get(k) is not None for k in self.label_names)
if has_labels:
@@ -237,8 +235,6 @@ def _process_dataset(self):
}
"""
for key in self.onnx_input_names:
- # import pdb;
- # pdb.set_trace()
if key in inputs:
# onnx_inputs[key] = np.array([inputs[key]])
onnx_inputs.append(np.array(inputs[key]))
diff --git a/examples/pytorch/object_detection/ssd_resnet34/quantization/ptq/fx/python/models/utils.py b/examples/pytorch/object_detection/ssd_resnet34/quantization/ptq/fx/python/models/utils.py
index 940722075ab..e4d5db6b8ee 100644
--- a/examples/pytorch/object_detection/ssd_resnet34/quantization/ptq/fx/python/models/utils.py
+++ b/examples/pytorch/object_detection/ssd_resnet34/quantization/ptq/fx/python/models/utils.py
@@ -59,7 +59,6 @@ def _compute_padding(self, input, dim):
return additional_padding, total_padding
def forward(self, input):
- #import pdb; pdb.set_trace()
if self.padding == "VALID":
return F.conv2d(
input,
@@ -180,7 +179,6 @@ def decode_boxes(rel_codes, boxes, weights):
dh = dh / wh
pred_ctr_x = dx * widths + ctr_x
- #import pdb; pdb.set_trace()
pred_ctr_y = dy * heights + ctr_y
pred_w = torch.exp(dw) * widths
pred_h = torch.exp(dh) * heights
@@ -194,5 +192,4 @@ def decode_boxes(rel_codes, boxes, weights):
],
dim=2,
)
- #import pdb; pdb.set_trace()
return pred_boxes
diff --git a/neural_coder/coders/tensorflow/amp.py b/neural_coder/coders/tensorflow/amp.py
index 70302d78d4a..77f349ef084 100644
--- a/neural_coder/coders/tensorflow/amp.py
+++ b/neural_coder/coders/tensorflow/amp.py
@@ -22,8 +22,6 @@ def __init__(self, file) -> None:
self.keras_edited_flag = False
def transform(self):
- # import pdb
- # pdb.set_trace()
lines = self.file.split("\n")
for line in lines:
if self.is_modify(line):
diff --git a/neural_coder/coders/tensorflow/inc.py b/neural_coder/coders/tensorflow/inc.py
index 837dff143fb..30455bc27c8 100644
--- a/neural_coder/coders/tensorflow/inc.py
+++ b/neural_coder/coders/tensorflow/inc.py
@@ -21,8 +21,6 @@ def __init__(self, file) -> None:
self.result = []
def transform(self):
- # import pdb
- # pdb.set_trace()
lines = self.file.split("\n")
for line in lines:
if self.is_modify(line):
diff --git a/neural_compressor/strategy/strategy.py b/neural_compressor/strategy/strategy.py
index 60101104e3c..06c5b0d0783 100644
--- a/neural_compressor/strategy/strategy.py
+++ b/neural_compressor/strategy/strategy.py
@@ -485,7 +485,6 @@ def traverse(self):
return self.distributed_traverse()
self._setup_pre_tuning_algo_scheduler()
self._prepare_tuning()
- # import pdb;pdb.set_trace()
traverse_start_time = time()
for op_tuning_cfg in self.next_tune_cfg():
tuning_start_time = time()
diff --git a/neural_compressor/torch/algorithms/habana_fp8/fp8_quant.py b/neural_compressor/torch/algorithms/habana_fp8/fp8_quant.py
index 0330bd475ad..c80cc443531 100644
--- a/neural_compressor/torch/algorithms/habana_fp8/fp8_quant.py
+++ b/neural_compressor/torch/algorithms/habana_fp8/fp8_quant.py
@@ -131,7 +131,6 @@ def input_observer_forward_pre_hook(self, input):
### Insert input observer into model, only for fp8_e4m3 static quantization ###
observer_cls = observer_mapping[act_observer]
- # import pdb;pdb.set_trace()
if isinstance(module, white_list):
observer_obj = observer_cls(dtype=dtype_mapping[qconfig.act_dtype])
diff --git a/test/pruning_with_pt/pruning_2.x/test_auto_excluding_classifier.py b/test/pruning_with_pt/pruning_2.x/test_auto_excluding_classifier.py
index 0eb2d04005a..641525fd26d 100644
--- a/test/pruning_with_pt/pruning_2.x/test_auto_excluding_classifier.py
+++ b/test/pruning_with_pt/pruning_2.x/test_auto_excluding_classifier.py
@@ -24,7 +24,6 @@ def forward(self, x):
class TestPruning(unittest.TestCase):
def test_pruning_basic(self):
- # import pdb;pdb.set_trace()
hidden_size = 32
model = NaiveMLP(hidden_size)
# import classifier searching functions
diff --git a/test/pruning_with_pt/pruning_2.x/test_auto_slim.py b/test/pruning_with_pt/pruning_2.x/test_auto_slim.py
index 7af5cf8de20..b5f09a3c41d 100644
--- a/test/pruning_with_pt/pruning_2.x/test_auto_slim.py
+++ b/test/pruning_with_pt/pruning_2.x/test_auto_slim.py
@@ -50,7 +50,6 @@ def test_pruning_basic(self):
# run mha and ffn pruning
compression_manager = prepare_compression(model=model, confs=configs)
compression_manager.callbacks.on_train_begin()
- # import pdb;pdb.set_trace()
for epoch in range(3):
model.train()
compression_manager.callbacks.on_epoch_begin(epoch)