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[ONNX] Revert the temporary test changes #3677

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Merged
andrey-churkin merged 1 commit into from
Oct 6, 2025
Merged

[ONNX] Revert the temporary test changes #3677

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15 changes: 0 additions & 15 deletions tests/post_training/pipelines/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -184,8 +184,6 @@ class RunInfo:
time_compression: Optional[float] = None
num_compress_nodes: Optional[NumCompressNodes] = None
stats_from_output = StatsFromOutput()
fp32_model_size: Optional[float] = None
int8_model_size: Optional[float] = None

@staticmethod
def format_time(time_elapsed):
Expand Down Expand Up @@ -214,9 +212,6 @@ def get_result_dict(self) -> dict[str, str]:
"Metric name": self.metric_name,
"Metric value": self.metric_value,
"Metric diff": self.metric_diff,
"Model size Mb (FP32)": self.fp32_model_size,
"Model size Mb (INT8)": self.int8_model_size,
"Compression rate:": self.fp32_model_size / self.int8_model_size,
**self.num_compress_nodes.get_data(),
"Compr. time": self.format_time(self.time_compression),
**self.stats_from_output.get_stats(),
Expand All @@ -229,15 +224,6 @@ def get_result_dict(self) -> dict[str, str]:
return result


def get_model_size(path: Path, m_type: str = "Mb") -> float:
model_size = path.stat().st_size
for t in ["bytes", "Kb", "Mb"]:
if m_type == t:
break
model_size /= 1024
return model_size


class BaseTestPipeline(ABC):
"""
Base class to test compression algorithms.
Expand Down Expand Up @@ -548,7 +534,6 @@ def save_compressed_model(self) -> None:
elif self.backend == BackendType.ONNX:
onnx_path = self.output_model_dir / "model.onnx"
onnx.save(self.compressed_model, str(onnx_path))
self.run_info.int8_model_size = get_model_size(onnx_path)
ov_model = ov.convert_model(onnx_path)
ov.serialize(ov_model, self.path_compressed_ir)
elif self.backend in OV_BACKENDS:
Expand Down
2 changes: 0 additions & 2 deletions tests/post_training/pipelines/image_classification_timm.py
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Expand Up @@ -20,7 +20,6 @@
from tests.post_training.pipelines.base import OV_BACKENDS
from tests.post_training.pipelines.base import PT_BACKENDS
from tests.post_training.pipelines.base import BackendType
from tests.post_training.pipelines.base import get_model_size
from tests.post_training.pipelines.image_classification_base import ImageClassificationBase

# Disable using aten::scaled_dot_product_attention
Expand Down Expand Up @@ -51,7 +50,6 @@ def prepare_model(self) -> None:
torch.onnx.export(
timm_model, self.dummy_tensor, onnx_path, export_params=True, opset_version=13, **additional_kwargs
)
self.run_info.fp32_model_size = get_model_size(onnx_path)
self.model = onnx.load(onnx_path)
self.input_name = self.model.graph.input[0].name

Expand Down
2 changes: 0 additions & 2 deletions tests/post_training/pipelines/image_classification_torchvision.py
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Expand Up @@ -21,7 +21,6 @@
from tests.post_training.pipelines.base import FX_BACKENDS
from tests.post_training.pipelines.base import PT_BACKENDS
from tests.post_training.pipelines.base import BackendType
from tests.post_training.pipelines.base import get_model_size
from tests.post_training.pipelines.image_classification_base import ImageClassificationBase


Expand Down Expand Up @@ -98,7 +97,6 @@ def prepare_model(self) -> None:
torch.onnx.export(
model, self.dummy_tensor, onnx_path, export_params=True, opset_version=13, **additional_kwargs
)
self.run_info.fp32_model_size = get_model_size(onnx_path)
self.model = onnx.load(onnx_path)
self.input_name = self.model.graph.input[0].name

Expand Down