Fix imports 5

Author: nikita-savelyevv

optimum/intel/openvino/quantization/calibration_dataset_builder.py

@@ -26,7 +26,6 @@
 from tqdm import tqdm
 from transformers import AutoProcessor, AutoTokenizer, DataCollator, default_data_collator
 
-from optimum.intel.openvino.modeling_decoder import OVBaseDecoderModel
 from optimum.intel.openvino.utils import (
     PREDEFINED_DIFFUSION_DATASETS,
     PREDEFINED_SPEECH_TO_TEXT_DATASETS,
@@ -171,6 +170,7 @@ def build_from_dataset(
         # TODO: deprecate remove_unused_columns ?
 
         from optimum.intel import OVModelForVisualCausalLM
+        from optimum.intel.openvino.modeling_decoder import OVBaseDecoderModel
         from optimum.intel.openvino.modeling_seq2seq import _OVModelForWhisper
 
         if is_diffusers_available():
@@ -184,7 +184,7 @@ def build_from_dataset(
             return self._prepare_visual_causal_lm_calibration_data(quantization_config, dataloader)
         elif isinstance(self.model, _OVModelForWhisper):
             return self._prepare_speech_to_text_calibration_data(quantization_config, dataloader)
-        elif isinstance(self.model, OVDiffusionPipeline):
+        elif is_diffusers_available() and isinstance(self.model, OVDiffusionPipeline):
             return self._prepare_diffusion_calibration_data(quantization_config, dataloader)
         else:
             # Torch model quantization scenario
@@ -337,7 +337,7 @@ def preprocess_function(item):
                 )
             else:
                 raise Exception
-        elif isinstance(self.model, OVDiffusionPipeline):
+        elif is_diffusers_available() and isinstance(self.model, OVDiffusionPipeline):
             dataset = config.dataset
 
             dataset_metadata = None

optimum/intel/openvino/quantization/quantizer.py

@@ -195,7 +195,8 @@ def quantize(
                 calibration_dataset = calibration_dataset.select_columns(["caption"])
 
             if (
-                isinstance(self.model, OVDiffusionPipeline)
+                is_diffusers_available()
+                and isinstance(self.model, OVDiffusionPipeline)
                 and isinstance(calibration_dataset, list)
                 and all(isinstance(it, str) for it in calibration_dataset)
             ):
@@ -288,7 +289,11 @@ def _quantize_ovbasemodel(
             if calibration_datasets is None:
                 raise ValueError("Calibration dataset is required to run data-aware quantization.")
             if (
-                not isinstance(self.model, (OVDiffusionPipeline, _OVModelForWhisper))
+                not (
+                    is_diffusers_available()
+                    and isinstance(self.model, OVDiffusionPipeline)
+                    or isinstance(self.model, _OVModelForWhisper)
+                )
                 and "model" not in calibration_datasets
             ):
                 raise RuntimeError("Calibration datasets should contain a key 'model' with a dataset.")