[Quantization] Switch to optimum-quanto (#31732)

* switch to optimum-quanto rebase squach

* fix import check

* again

* test try-except

* style

tests/quantization/quanto_integration/test_quanto.py

@@ -19,13 +19,13 @@ import unittest
 from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, QuantoConfig
 from transformers.testing_utils import (
     require_accelerate,
-    require_quanto,
+    require_optimum_quanto,
     require_read_token,
     require_torch_gpu,
     slow,
     torch_device,
 )
-from transformers.utils import is_accelerate_available, is_quanto_available, is_torch_available
+from transformers.utils import is_accelerate_available, is_optimum_quanto_available, is_torch_available
 
 
 if is_torch_available():
@@ -36,8 +36,8 @@ if is_torch_available():
 if is_accelerate_available():
     from accelerate import init_empty_weights
 
-if is_quanto_available():
-    from quanto import QLayerNorm, QLinear
+if is_optimum_quanto_available():
+    from optimum.quanto import QLayerNorm, QLinear
 
     from transformers.integrations.quanto import replace_with_quanto_layers
 
@@ -47,7 +47,7 @@ class QuantoConfigTest(unittest.TestCase):
         pass
 
 
-@require_quanto
+@require_optimum_quanto
 @require_accelerate
 class QuantoTestIntegration(unittest.TestCase):
     model_id = "facebook/opt-350m"
@@ -124,7 +124,7 @@ class QuantoTestIntegration(unittest.TestCase):
 
 @slow
 @require_torch_gpu
-@require_quanto
+@require_optimum_quanto
 @require_accelerate
 class QuantoQuantizationTest(unittest.TestCase):
     """
@@ -187,7 +187,7 @@ class QuantoQuantizationTest(unittest.TestCase):
         self.check_inference_correctness(self.quantized_model, "cuda")
 
     def test_quantized_model_layers(self):
-        from quanto import QBitsTensor, QModuleMixin, QTensor
+        from optimum.quanto import QBitsTensor, QModuleMixin, QTensor
 
         """
         Suite of simple test to check if the layers are quantized and are working properly
@@ -256,7 +256,7 @@ class QuantoQuantizationTest(unittest.TestCase):
             self.assertTrue(torch.equal(d0[k], d1[k].to(d0[k].device)))
 
     def test_compare_with_quanto(self):
-        from quanto import freeze, qint4, qint8, quantize
+        from optimum.quanto import freeze, qint4, qint8, quantize
 
         w_mapping = {"int8": qint8, "int4": qint4}
         model = AutoModelForCausalLM.from_pretrained(
@@ -272,7 +272,7 @@ class QuantoQuantizationTest(unittest.TestCase):
 
     @unittest.skip
     def test_load_from_quanto_saved(self):
-        from quanto import freeze, qint4, qint8, quantize
+        from optimum.quanto import freeze, qint4, qint8, quantize
 
         from transformers import QuantoConfig
 
@@ -356,7 +356,7 @@ class QuantoQuantizationOffloadTest(QuantoQuantizationTest):
         """
         We check that we have unquantized value in the cpu and in the disk
         """
-        import quanto
+        from optimum.quanto import QBitsTensor, QTensor
 
         cpu_weights = self.quantized_model.transformer.h[22].self_attention.query_key_value._hf_hook.weights_map[
             "weight"
@@ -364,13 +364,11 @@ class QuantoQuantizationOffloadTest(QuantoQuantizationTest):
         disk_weights = self.quantized_model.transformer.h[23].self_attention.query_key_value._hf_hook.weights_map[
             "weight"
         ]
-        self.assertTrue(isinstance(cpu_weights, torch.Tensor) and not isinstance(cpu_weights, quanto.QTensor))
-        self.assertTrue(isinstance(disk_weights, torch.Tensor) and not isinstance(disk_weights, quanto.QTensor))
+        self.assertTrue(isinstance(cpu_weights, torch.Tensor) and not isinstance(cpu_weights, QTensor))
+        self.assertTrue(isinstance(disk_weights, torch.Tensor) and not isinstance(disk_weights, QTensor))
         if self.weights == "int4":
-            self.assertTrue(isinstance(cpu_weights, torch.Tensor) and not isinstance(disk_weights, quanto.QBitsTensor))
-            self.assertTrue(
-                isinstance(disk_weights, torch.Tensor) and not isinstance(disk_weights, quanto.QBitsTensor)
-            )
+            self.assertTrue(isinstance(cpu_weights, torch.Tensor) and not isinstance(disk_weights, QBitsTensor))
+            self.assertTrue(isinstance(disk_weights, torch.Tensor) and not isinstance(disk_weights, QBitsTensor))
 
 
 @unittest.skip(reason="Skipping test class because serialization is not supported yet")
@@ -416,18 +414,18 @@ class QuantoQuantizationSerializationCudaTest(QuantoQuantizationTest):
 
 
 class QuantoQuantizationQBitsTensorTest(QuantoQuantizationTest):
-    EXPECTED_OUTPUTS = "Hello my name is Nils, I am a student of the University"
+    EXPECTED_OUTPUTS = "Hello my name is John, I am a professional photographer, I"
     weights = "int4"
 
 
 class QuantoQuantizationQBitsTensorOffloadTest(QuantoQuantizationOffloadTest):
-    EXPECTED_OUTPUTS = "Hello my name is Nils, I am a student of the University"
+    EXPECTED_OUTPUTS = "Hello my name is John, I am a professional photographer, I"
     weights = "int4"
 
 
 @unittest.skip(reason="Skipping test class because serialization is not supported yet")
 class QuantoQuantizationQBitsTensorSerializationTest(QuantoQuantizationSerializationTest):
-    EXPECTED_OUTPUTS = "Hello my name is Nils, I am a student of the University"
+    EXPECTED_OUTPUTS = "Hello my name is John, I am a professional photographer, I"
     weights = "int4"
 
 
@@ -443,14 +441,14 @@ class QuantoQuantizationActivationTest(unittest.TestCase):
         self.assertIn("We don't support quantizing the activations with transformers library", str(e.exception))
 
 
-@require_quanto
+@require_optimum_quanto
 @require_torch_gpu
 class QuantoKVCacheQuantizationTest(unittest.TestCase):
     @slow
     @require_read_token
     def test_quantized_cache(self):
         EXPECTED_TEXT_COMPLETION = [
-            "Simply put, the theory of relativity states that 1) the speed of light is the same for all observers, and 2) the laws of physics are the same for all observers.\nThe first part of the theory of relativity",
+            "Simply put, the theory of relativity states that 1) the speed of light is the same for all observers, and 2) the laws of physics are the same for all observers.\nThe first part of the theory is the most",
             "My favorite all time favorite condiment is ketchup. I love it on everything. I love it on my eggs, my fries, my chicken, my burgers, my hot dogs, my sandwiches, my salads, my p",
         ]