Suppress pylint cyclic-import false alarm (#3661)

Signed-off-by: Kyunggeun Lee <[email protected]>

TrainingExtensions/torch/src/python/aimet_torch/_base/quantsim.py

@@ -82,6 +82,7 @@
 from aimet_torch.experimental.v2.quantsim.export_utils import _export_to_1_0_0
 
 if TYPE_CHECKING:
+    # pylint: disable=cyclic-import
     from aimet_torch.v2.quantization.base.encoding import EncodingBase
 
 
@@ -522,7 +523,7 @@ def _apply_exception_rules(self):
         """
         Apply exception rules to specific op. For example, a rule can override high bitwidth to Embedding module
         """
-        # pylint: disable=import-outside-toplevel
+        # pylint: disable=import-outside-toplevel, cyclic-import
         from aimet_torch.v2.nn import BaseQuantizationMixin
 
         for wrapper in self.qmodules():

TrainingExtensions/torch/src/python/aimet_torch/experimental/v2/quantsim/export_utils.py

@@ -112,7 +112,8 @@ def _get_activation_encodings(tensor_to_activation_encodings: Dict[str, List], t
 
 
 def _get_param_encodings(tensor_to_param_encodings: Dict[str, List], tensor_to_quantizer_map: Dict):
-    from aimet_torch.v2.quantization.affine import AffineQuantizerBase # pylint: disable=import-outside-toplevel
+        # pylint: disable=import-outside-toplevel, cyclic-import
+    from aimet_torch.v2.quantization.affine import AffineQuantizerBase
 
     param_encodings = []
     for tensor, encodings in tensor_to_param_encodings.items():

TrainingExtensions/torch/src/python/aimet_torch/layer_output_utils.py

@@ -276,7 +276,7 @@ def get_layer_name_to_layer_output_name_map(model, naming_scheme: NamingScheme,
         :param dir_path: directory to temporarily save the constructed onnx/torchscrip model
         :return: dictionary of layer-name to layer-output name
         """
-        # pylint: disable=import-outside-toplevel
+        # pylint: disable=import-outside-toplevel, cyclic-import
         if any(isinstance(module, BaseQuantizationMixin) for module in model.modules()):
             from aimet_torch.v2.quantsim import QuantizationSimModel
         else:

TrainingExtensions/torch/src/python/aimet_torch/meta/connectedgraph.py

@@ -1338,7 +1338,8 @@ def _is_recursive_parsing_needed(self, module: torch.nn.Module,
         :param trace: torch.jit trace of the module
         :return: Boolean whether recursive parsing needed or not. If needed returns True, False otherwise.
         """
-        from aimet_torch.v2.nn import BaseQuantizationMixin # pylint: disable=import-outside-toplevel
+        # pylint: disable=import-outside-toplevel, cyclic-import
+        from aimet_torch.v2.nn import BaseQuantizationMixin
         if isinstance(module, BaseQuantizationMixin):
             return self._is_recursive_parsing_needed(module.get_original_module(), trace)
 

TrainingExtensions/torch/src/python/aimet_torch/quantsim_config/builder.py

@@ -91,6 +91,7 @@ def __init__(self, module_to_wrap: torch.nn.Module, weight_bw: int, activation_b
         # Create quantizer for each parameter and compute encodings
         self.param_quantizers = {}
 
+        # pylint: disable=import-outside-toplevel, cyclic-import
         from aimet_torch.v2.nn import BaseQuantizationMixin
         if isinstance(module_to_wrap, BaseQuantizationMixin):
             # NOTE: AIMET v2 qmodule always only quantizes the paramters that it directly owns

TrainingExtensions/torch/src/python/aimet_torch/quantsim_config/quantsim_config.py

@@ -735,7 +735,7 @@ def _create_module_to_quantsim_wrapper_dict(model: torch.nn.Module) -> Dict[torc
     :param model: Pytorch model with quantsim wrappers in place
     :return: Dictionary mapping modules in the model to corresponding quantsim wrappers
     """
-    # pylint: disable=import-outside-toplevel
+    # pylint: disable=import-outside-toplevel, cyclic-import
     from aimet_torch._base.quantsim import _QuantizedModuleProtocol
     from aimet_torch.v2.nn import BaseQuantizationMixin
     module_to_quantsim_wrapper_dict = {}

TrainingExtensions/torch/src/python/aimet_torch/utils.py

@@ -925,7 +925,6 @@ def get_all_quantizers(model: torch.nn.Module):
     :param model: Root module
     :returns: List of parameter, input, and output quantizers
     """
-    # pylint:disable = cyclic-import
     param_quantizers = []
     input_quantizers = []
     output_quantizers = []
@@ -959,8 +958,9 @@ def disable_all_quantizers(model: torch.nn.Module):
     :param model: Root module
     :returns: Handle that enable all quantizers in the model upon handle.remove().
     """
-    from aimet_torch.v2.nn.base import BaseQuantizationMixin # pylint: disable=import-outside-toplevel, cyclic-import
-    import aimet_torch.v2.utils as v2_utils # pylint: disable=import-outside-toplevel
+    # pylint: disable=import-outside-toplevel, cyclic-import
+    from aimet_torch.v2.nn.base import BaseQuantizationMixin
+    import aimet_torch.v2.utils as v2_utils
 
     if any(isinstance(m, BaseQuantizationMixin) for m in model.modules()):
         return v2_utils.remove_all_quantizers(model)

TrainingExtensions/torch/src/python/aimet_torch/v1/quantsim_straight_through_grad.py

@@ -44,7 +44,8 @@
 from aimet_torch.v1.tensor_factory_utils import constant_like
 
 if TYPE_CHECKING:
-    from aimet_torch.v1.tensor_quantizer import LearnedGridTensorQuantizer # pylint:disable = cyclic-import
+    # pylint: disable=cyclic-import
+    from aimet_torch.v1.tensor_quantizer import LearnedGridTensorQuantizer
 
 
 @dataclass

TrainingExtensions/torch/src/python/aimet_torch/v1/tensor_quantizer.py

@@ -54,6 +54,7 @@
 from aimet_torch.fp_quantization import fp8_quantizer, INIT_MAP
 from aimet_torch.v1.tensor_factory_utils import constant_like
 if TYPE_CHECKING:
+    # pylint: disable=cyclic-import
     from aimet_torch.v2.quantization.base import EncodingBase
 
 _logger = AimetLogger.get_area_logger(AimetLogger.LogAreas.Quant)

TrainingExtensions/torch/src/python/aimet_torch/v2/_builder.py

@@ -134,6 +134,7 @@ def realize(self):
 
         :return: v2 quant wrapper with specified properties
         """
+        # pylint: disable=import-outside-toplevel, cyclic-import
         from aimet_torch.v2.nn import QuantizationMixin
         from aimet_torch.v2.nn.fake_quant import _legacy_impl
 

TrainingExtensions/torch/src/python/aimet_torch/v2/quantization/base/quantizer.py

@@ -54,6 +54,7 @@
 from aimet_torch.utils import deprecated
 
 if TYPE_CHECKING:
+    # pylint: disable=cyclic-import
     from aimet_torch.v2.quantization.tensor import QuantizedTensorBase