Have dummy processors have a from_pretrained method (#12145)

src/transformers/utils/dummy_flax_objects.py

@@ -6,11 +6,19 @@ class FlaxLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["flax"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["flax"])
+
 
 class FlaxLogitsProcessorList:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["flax"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["flax"])
+
 
 class FlaxLogitsWarper:
     def __init__(self, *args, **kwargs):

src/transformers/utils/dummy_pt_objects.py

@@ -127,31 +127,55 @@ class ForcedBOSTokenLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class ForcedEOSTokenLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class HammingDiversityLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class InfNanRemoveLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class LogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class LogitsProcessorList:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class LogitsWarper:
     def __init__(self, *args, **kwargs):
@@ -162,26 +186,46 @@ class MinLengthLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class NoBadWordsLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class NoRepeatNGramLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class PrefixConstrainedLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class RepetitionPenaltyLogitsProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["torch"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
 
 class TemperatureLogitsWarper:
     def __init__(self, *args, **kwargs):

src/transformers/utils/dummy_sentencepiece_and_speech_objects.py

@@ -5,3 +5,7 @@ from ..file_utils import requires_backends
 class Speech2TextProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["sentencepiece", "speech"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["sentencepiece", "speech"])

src/transformers/utils/dummy_vision_objects.py

@@ -16,6 +16,10 @@ class CLIPProcessor:
     def __init__(self, *args, **kwargs):
         requires_backends(self, ["vision"])
 
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["vision"])
+
 
 class DeiTFeatureExtractor:
     def __init__(self, *args, **kwargs):

utils/check_dummies.py

@@ -115,6 +115,7 @@ def create_dummy_object(name, backend_name):
         "ForTokenClassification",
         "Model",
         "Tokenizer",
+        "Processor",
     ]
     if name.isupper():
         return DUMMY_CONSTANT.format(name)