Remove accelerate dependency

Author: echarlaix

optimum/intel/__init__.py

@@ -15,7 +15,7 @@
 import importlib.util
 from typing import TYPE_CHECKING
 
-from transformers.utils import OptionalDependencyNotAvailable, _LazyModule
+from transformers.utils import OptionalDependencyNotAvailable, _LazyModule, is_accelerate_available
 
 from .utils import (
     is_diffusers_available,
@@ -57,13 +57,19 @@
     if not (is_openvino_available() and is_nncf_available()):
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
-    _import_structure["utils.dummy_openvino_and_nncf_objects"] = [
-        "OVQuantizer",
-        "OVTrainer",
-        "OVTrainingArguments",
-    ]
+    _import_structure["utils.dummy_openvino_and_nncf_objects"] = ["OVQuantizer", "OVTrainingArguments"]
+else:
+    _import_structure["openvino"].extend(["OVQuantizer", "OVTrainingArguments"])
+
+
+try:
+    if not (is_openvino_available() and is_nncf_available() and is_accelerate_available()):
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    _import_structure["utils.dummy_openvino_and_nncf_objects"] = ["OVTrainer"]
 else:
-    _import_structure["openvino"].extend(["OVQuantizer", "OVTrainer", "OVTrainingArguments"])
+    _import_structure["openvino"].extend(["OVTrainer"])
+
 
 try:
     if not (is_openvino_available() and is_diffusers_available()):
@@ -177,13 +183,17 @@
         if not (is_openvino_available() and is_nncf_available()):
             raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
-        from .utils.dummy_openvino_and_nncf_objects import (
-            OVQuantizer,
-            OVTrainer,
-            OVTrainingArguments,
-        )
+        from .utils.dummy_openvino_and_nncf_objects import OVQuantizer, OVTrainingArguments
+    else:
+        from .openvino import OVQuantizer, OVTrainingArguments
+
+    try:
+        if not (is_openvino_available() and is_nncf_available() and is_accelerate_available()):
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        from .utils.dummy_openvino_and_nncf_objects import OVTrainer
     else:
-        from .openvino import OVQuantizer, OVTrainer, OVTrainingArguments
+        from .openvino import OVTrainer
 
     try:
         if not (is_openvino_available() and is_diffusers_available()):

optimum/intel/openvino/__init__.py

@@ -14,6 +14,8 @@
 
 import logging
 
+from transformers.utils import is_accelerate_available
+
 from ..utils.import_utils import is_diffusers_available, is_nncf_available
 from .utils import (
     OV_DECODER_NAME,
@@ -37,9 +39,11 @@
     patch_torch_operators()
 
     from .quantization import OVQuantizer
-    from .trainer import OVTrainer
     from .training_args import OVTrainingArguments
 
+    if is_accelerate_available():
+        from .trainer import OVTrainer
+
 
 from .configuration import OVConfig, OVWeightQuantizationConfig
 from .modeling import (

optimum/intel/openvino/quantization.py

@@ -17,7 +17,7 @@
 import logging
 import os
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Callable, Dict, Optional, Tuple, Union
+from typing import Any, Callable, Dict, Optional, Tuple, Union
 
 import nncf
 import openvino
@@ -56,8 +56,7 @@
 
 
 if is_datasets_available():
-    if TYPE_CHECKING:
-        from datasets import Dataset
+    from datasets import Dataset
 
 register_module(ignored_algorithms=[])(Conv1D)
 
@@ -147,6 +146,7 @@ def __init__(self, model: transformers.PreTrainedModel, task: Optional[str] = No
             )
         self.task = task or feature
         self.seed = seed
+        # TODO : deprecate input_names
         self.input_names = None
         signature = inspect.signature(self.model.forward)
         self._signature_columns = list(signature.parameters.keys())
@@ -526,9 +526,15 @@ def _get_calibration_dataloader(
         data_collator: Optional[DataCollator] = None,
     ) -> OVDataLoader:
         data_collator = data_collator if data_collator is not None else default_data_collator
+
+        if not is_datasets_available() or not isinstance(calibration_dataset, Dataset):
+            logger.warning(
+                "`remove_unused_columns` set to `False` as calibration_dataset is not an instance of `datasets.Dataset`"
+            )
+            remove_unused_columns = False
+
         if remove_unused_columns:
             calibration_dataset = self._remove_unused_columns(calibration_dataset)
-        self.input_names = calibration_dataset.column_names
         generator = torch.Generator()
         generator.manual_seed(self.seed)
         sampler = RandomSampler(calibration_dataset, generator=generator)

optimum/intel/utils/dummy_openvino_and_nncf_objects.py

@@ -27,14 +27,14 @@ def from_pretrained(cls, *args, **kwargs):
 
 
 class OVTrainer(metaclass=DummyObject):
-    _backends = ["openvino", "nncf"]
+    _backends = ["openvino", "nncf", "accelerate"]
 
     def __init__(self, *args, **kwargs):
-        requires_backends(self, ["openvino", "nncf"])
+        requires_backends(self, ["openvino", "nncf", "accelerate"])
 
     @classmethod
     def from_pretrained(cls, *args, **kwargs):
-        requires_backends(cls, ["openvino", "nncf"])
+        requires_backends(cls, ["openvino", "nncf", "accelerate"])
 
 
 class OVQuantizer(metaclass=DummyObject):

setup.py

@@ -18,10 +18,10 @@
     "datasets>=1.4.0",
     "sentencepiece",
     "scipy",
-    "accelerate",  # transformers 4.29 require accelerate for PyTorch
 ]
 
 TESTS_REQUIRE = [
+    "accelerate",
     "pytest",
     "parameterized",
     "Pillow",
@@ -40,7 +40,7 @@
 
 EXTRAS_REQUIRE = {
     "neural-compressor": ["neural-compressor>=2.2.0", "onnx", "onnxruntime<1.15.0"],
-    "openvino": ["openvino>=2023.3", "onnx", "onnxruntime", "nncf>=2.8.1"],
+    "openvino": ["openvino>=2023.3", "onnx", "nncf>=2.8.1"],
     "openvino-tokenizers": ["openvino-tokenizers[transformers]"],
     "nncf": ["nncf>=2.8.1"],
     "ipex": ["intel-extension-for-pytorch", "onnx"],