fix transformers and quantization imports

src/sparseml/modifiers/obcq/utils/layer_compressor.py

@@ -20,8 +20,8 @@
 import torch.nn as nn
 from torch.nn import Module
 
-from sparseml.modifiers.obcq.utils.sparsegpt import SparseGPT
 from sparseml.pytorch.utils.helpers import get_dependency_order
+from sparseml.transformers.sparsification.obcq.utils.sparsegpt import SparseGPT
 
 
 _LOGGER = logging.getLogger(__name__)

src/sparseml/modifiers/quantization/utils/__init__.py

@@ -0,0 +1,13 @@
+# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

tests/sparseml/modifiers/quantization/test_pytorch.py

@@ -26,6 +26,7 @@
 from tests.sparseml.modifiers.conf import LifecyleTestingHarness, setup_modifier_factory
 from tests.sparseml.pytorch.helpers import ConvNet, LinearNet
 from tests.sparseml.pytorch.sparsification.quantization.test_modifier_quantization import (  # noqa E501
+    _match_submodule_name_or_type,
     _test_qat_wrapped_module,
     _test_quantized_module,
 )
@@ -56,7 +57,12 @@ def _test_qat_applied(modifier, model):
                 _test_qat_wrapped_module(model, name)
             elif is_quantizable:
                 # check each target module is quantized
-                _test_quantized_module(model, modifier, module, name)
+                override_key = _match_submodule_name_or_type(
+                    module,
+                    name,
+                    list(modifier.scheme_overrides.keys()),
+                )
+                _test_quantized_module(model, modifier, module, name, override_key)
         else:
             # check all non-target modules are not quantized
             assert not hasattr(module, "quantization_scheme")