lint

Author: metascroy

backends/cortex_m/test/test_replace_quant_nodes.py

@@ -16,15 +16,15 @@
     ReplaceQuantNodesPass,
 )
 from executorch.exir.dialects._ops import ops as exir_ops
-from torch.ao.quantization.observer import HistogramObserver
-from torch.ao.quantization.quantize_pt2e import convert_pt2e, prepare_pt2e
-from torch.ao.quantization.quantizer.quantizer import (
+from torch.export import export, export_for_training
+from torch.fx import GraphModule
+from torchao.quantization.pt2e.observer import HistogramObserver
+from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
+from torchao.quantization.pt2e.quantizer import (
     QuantizationAnnotation,
     QuantizationSpec,
     Quantizer,
 )
-from torch.export import export, export_for_training
-from torch.fx import GraphModule
 
 
 @dataclass(eq=True, frozen=True)

backends/nxp/tests/executorch_pipeline.py

@@ -20,7 +20,7 @@
     to_edge_transform_and_lower,
 )
 from torch import nn
-from torch.ao.quantization.quantize_pt2e import convert_pt2e, prepare_pt2e
+from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
 
 
 def _quantize_model(model, calibration_inputs: list[tuple[torch.Tensor]]):

backends/vulkan/test/test_vulkan_delegate.py

@@ -23,11 +23,11 @@
     EdgeProgramManager,
     ExecutorchProgramManager,
 )
+from torch.export import Dim, export, export_for_training, ExportedProgram
 
-from torch.ao.quantization.quantize_pt2e import convert_pt2e, prepare_pt2e
+from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
 
-from torch.ao.quantization.quantizer import Quantizer
-from torch.export import Dim, export, export_for_training, ExportedProgram
+from torchao.quantization.pt2e.quantizer import Quantizer
 
 ctypes.CDLL("libvulkan.so.1")
 

backends/xnnpack/test/quantizer/test_pt2e_quantization.py

@@ -28,7 +28,6 @@
     NodeSpec as ns,
     TestHelperModules,
 )
-from torchao.testing.pt2e.utils import PT2EQuantizationTestCase
 from torch.testing._internal.common_utils import (
     instantiate_parametrized_tests,
     TemporaryFileName,
@@ -52,6 +51,7 @@
 from torchao.quantization.pt2e.quantizer import Quantizer
 from torchao.quantization.pt2e.quantizer.composable_quantizer import ComposableQuantizer
 from torchao.quantization.pt2e.quantizer.embedding_quantizer import EmbeddingQuantizer
+from torchao.testing.pt2e.utils import PT2EQuantizationTestCase
 
 
 class TestQuantizePT2E(PT2EQuantizationTestCase):
@@ -798,7 +798,7 @@ def test_extract_results_from_loggers(self) -> None:
         ref_results = extract_results_from_loggers(m_ref_logger)
         quant_results = extract_results_from_loggers(m_quant_logger)
         comparison_results = compare_results(
-            ref_results, # pyre-ignore[6]
+            ref_results,  # pyre-ignore[6]
             quant_results,  # pyre-ignore[6]
         )
         for node_summary in comparison_results.values():

backends/xnnpack/test/quantizer/test_xnnpack_quantizer.py

@@ -9,7 +9,12 @@
     XNNPACKQuantizer,
 )
 from torch.ao.ns.fx.utils import compute_sqnr
-from torch.ao.quantization import default_dynamic_qconfig, default_dynamic_fake_quant, QConfig, QConfigMapping
+from torch.ao.quantization import (
+    default_dynamic_fake_quant,
+    default_dynamic_qconfig,
+    QConfig,
+    QConfigMapping,
+)
 from torch.ao.quantization.backend_config import get_qnnpack_backend_config
 from torch.ao.quantization.qconfig import (
     default_per_channel_symmetric_qnnpack_qconfig,
@@ -29,9 +34,9 @@
     skipIfNoQNNPACK,
     TestHelperModules,
 )
-from torchao.testing.pt2e.utils import PT2EQuantizationTestCase
 from torch.testing._internal.common_quantized import override_quantized_engine
 from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
+from torchao.testing.pt2e.utils import PT2EQuantizationTestCase
 
 
 @skipIfNoQNNPACK

exir/backend/test/demos/test_xnnpack_qnnpack.py

@@ -28,6 +28,10 @@
     _load_for_executorch_from_buffer,
 )
 from executorch.extension.pytree import tree_flatten
+from torch.ao.quantization import (
+    default_dynamic_quant_observer,
+    default_per_channel_weight_observer,
+)
 from torch.ao.quantization.backend_config.executorch import (
     get_executorch_backend_config,
 )
@@ -36,7 +40,7 @@
     _convert_to_reference_decomposed_fx,
     prepare_fx,
 )
-from torch.ao.quantization import default_dynamic_quant_observer, default_per_channel_weight_observer
+
 
 class TestXnnQnnBackends(unittest.TestCase):
     def test_add_xnnpack_and_dqlinear_qnn(self):

exir/tests/test_quantization.py

@@ -19,15 +19,13 @@
 from executorch.exir.passes.quant_fusion_pass import QuantFusionPass
 from executorch.exir.passes.spec_prop_pass import SpecPropPass
 from torch.ao.ns.fx.utils import compute_sqnr
+from torch.ao.quantization.backend_config import get_executorch_backend_config
+from torch.ao.quantization.qconfig import default_per_channel_symmetric_qnnpack_qconfig
+from torch.ao.quantization.qconfig_mapping import QConfigMapping
 from torch.ao.quantization.quantize_fx import (  # @manual
     _convert_to_reference_decomposed_fx,
+    prepare_fx,
 )
-from torch.ao.quantization.qconfig_mapping import (
-    QConfigMapping,
-)
-from torch.ao.quantization.backend_config import get_executorch_backend_config
-from torch.ao.quantization.qconfig import default_per_channel_symmetric_qnnpack_qconfig
-from torch.ao.quantization.quantize_fx import prepare_fx
 from torch.export import export
 from torch.testing import FileCheck
 from torch.testing._internal.common_quantized import override_quantized_engine

export/export.py

@@ -13,10 +13,10 @@
 from executorch.runtime import Runtime, Verification
 from tabulate import tabulate
 from torch import nn
-from torch.ao.quantization import allow_exported_model_train_eval
-from torch.ao.quantization.quantize_pt2e import convert_pt2e, prepare_pt2e
 from torch.export import ExportedProgram
 from torchao.quantization import quantize_
+from torchao.quantization.pt2e import allow_exported_model_train_eval
+from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
 from torchao.utils import unwrap_tensor_subclass
 
 from .recipe import ExportRecipe