[SW-194748] Switch tester.py framework from using HQT to using INC

Switch every call to HQT package to use INC instead

Change-Id: I2f2dd4e6d6029aeb73fa2f70e7978aecfdccc65e

Author: Tiefen-boop

test/3x/torch/algorithms/fp8_quant/tester.py

@@ -7,10 +7,9 @@
 import typing
 from dataclasses import dataclass
 
-import habana_frameworks as htcore
 import torch
-from habana_quantization_toolkit._core.common import mod_default_dict
-from habana_quantization_toolkit._quant_common.quant_config import Fp8cfg, QuantMode, ScaleMethod
+from neural_compressor.torch.algorithms.fp8_quant._core.common import mod_default_dict
+from neural_compressor.torch.algorithms.fp8_quant._quant_common.quant_config import Fp8cfg, QuantMode, ScaleMethod
 
 
 @dataclass
@@ -60,8 +59,6 @@ def run_accuracy_test(
     This test also makes asserts the quantization actually happened.
     This may be moved to another tests in the future.
 
-    You can use the generate_test_vectors.py script to generate input test vectors.
-
     Args:
         module_class: The reference module class to test.
             This should be the direct module to test, e.g. Matmul, Linear, etc.
@@ -82,7 +79,7 @@ def run_accuracy_test(
         measure_vectors, test_vectors = itertools.tee(test_vectors)
 
     for mode in [QuantMode.MEASURE, QuantMode.QUANTIZE]:
-        import habana_quantization_toolkit.prepare_quant.prepare_model as hqt
+        import neural_compressor.torch.algorithms.fp8_quant.prepare_quant.prepare_model as prepare_model
 
         reference_model = WrapModel(module_class, seed, *module_args, **module_kwargs)
         quantized_model = WrapModel(module_class, seed, *module_args, **module_kwargs)
@@ -92,7 +89,7 @@ def run_accuracy_test(
             lp_dtype=lp_dtype,
             scale_method=scale_method,
         )
-        hqt._prep_model_with_predefined_config(quantized_model, config=config)
+        prepare_model._prep_model_with_predefined_config(quantized_model, config=config)
 
         _assert_quantized_correctly(reference_model=reference_model, quantized_model=quantized_model)
 
@@ -120,7 +117,7 @@ def run_accuracy_test(
                 f"\n  {scale_method.name=}"
             )
 
-        hqt.finish_measurements(quantized_model)
+        prepare_model.finish_measurements(quantized_model)
 
 
 def _set_optional_seed(*, module_class: typing.Type[M], seed: typing.Optional[int]):