introducing perfered engine logic

Author: ahmedlone127

python/sparknlp/annotator/audio/hubert_for_ctc.py

@@ -165,7 +165,7 @@ def loadSavedModel(folder, spark_session):
         return HubertForCTC(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="asr_hubert_large_ls960", lang="en", remote_loc=None):
+    def pretrained(name="asr_hubert_large_ls960", lang="en", remote_loc=None, engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -185,4 +185,4 @@ def pretrained(name="asr_hubert_large_ls960", lang="en", remote_loc=None):
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(HubertForCTC, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(HubertForCTC, name, lang, remote_loc, engine)

python/sparknlp/annotator/audio/wav2vec2_for_ctc.py

@@ -138,7 +138,7 @@ def loadSavedModel(folder, spark_session):
         return Wav2Vec2ForCTC(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="asr_wav2vec2_base_960h", lang="en", remote_loc=None):
+    def pretrained(name="asr_wav2vec2_base_960h", lang="en", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -158,4 +158,4 @@ def pretrained(name="asr_wav2vec2_base_960h", lang="en", remote_loc=None):
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(Wav2Vec2ForCTC, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(Wav2Vec2ForCTC, name, lang, remote_loc,engine )

python/sparknlp/annotator/audio/whisper_for_ctc.py

@@ -228,7 +228,7 @@ def loadSavedModel(folder, spark_session):
         return WhisperForCTC(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="asr_whisper_tiny_opt", lang="xx", remote_loc=None):
+    def pretrained(name="asr_whisper_tiny_opt", lang="xx", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -248,4 +248,4 @@ def pretrained(name="asr_whisper_tiny_opt", lang="xx", remote_loc=None):
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(WhisperForCTC, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(WhisperForCTC, name, lang, remote_loc,engine )

python/sparknlp/annotator/classifier_dl/albert_for_multiple_choice.py

@@ -138,7 +138,7 @@ def loadSavedModel(folder, spark_session):
         return AlbertForMultipleChoice(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="albert_base_uncased_multiple_choice", lang="en", remote_loc=None):
+    def pretrained(name="albert_base_uncased_multiple_choice", lang="en", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -158,4 +158,4 @@ def pretrained(name="albert_base_uncased_multiple_choice", lang="en", remote_loc
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(AlbertForMultipleChoice, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(AlbertForMultipleChoice, name, lang, remote_loc,engine )

python/sparknlp/annotator/classifier_dl/albert_for_question_answering.py

@@ -149,7 +149,7 @@ def loadSavedModel(folder, spark_session):
         return AlbertForQuestionAnswering(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="albert_base_qa_squad2", lang="en", remote_loc=None):
+    def pretrained(name="albert_base_qa_squad2", lang="en", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -169,4 +169,4 @@ def pretrained(name="albert_base_qa_squad2", lang="en", remote_loc=None):
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(AlbertForQuestionAnswering, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(AlbertForQuestionAnswering, name, lang, remote_loc,engine )

python/sparknlp/annotator/classifier_dl/albert_for_sequence_classification.py

@@ -178,7 +178,7 @@ def loadSavedModel(folder, spark_session):
         return AlbertForSequenceClassification(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="albert_base_sequence_classifier_imdb", lang="en", remote_loc=None):
+    def pretrained(name="albert_base_sequence_classifier_imdb", lang="en", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -198,4 +198,4 @@ def pretrained(name="albert_base_sequence_classifier_imdb", lang="en", remote_lo
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(AlbertForSequenceClassification, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(AlbertForSequenceClassification, name, lang, remote_loc,engine )

python/sparknlp/annotator/classifier_dl/albert_for_token_classification.py

@@ -156,7 +156,7 @@ def loadSavedModel(folder, spark_session):
         return AlbertForTokenClassification(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="albert_base_token_classifier_conll03", lang="en", remote_loc=None):
+    def pretrained(name="albert_base_token_classifier_conll03", lang="en", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -176,4 +176,4 @@ def pretrained(name="albert_base_token_classifier_conll03", lang="en", remote_lo
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(AlbertForTokenClassification, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(AlbertForTokenClassification, name, lang, remote_loc,engine )

python/sparknlp/annotator/classifier_dl/albert_for_zero_shot_classification.py

@@ -188,7 +188,7 @@ def loadSavedModel(folder, spark_session):
         return AlbertForZeroShotClassification(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="albert_zero_shot_classifier_onnx", lang="en", remote_loc=None):
+    def pretrained(name="albert_zero_shot_classifier_onnx", lang="en", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -208,4 +208,4 @@ def pretrained(name="albert_zero_shot_classifier_onnx", lang="en", remote_loc=No
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(AlbertForZeroShotClassification, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(AlbertForZeroShotClassification, name, lang, remote_loc,engine )

python/sparknlp/annotator/classifier_dl/bart_for_zero_shot_classification.py

@@ -202,7 +202,7 @@ def loadSavedModel(folder, spark_session):
         return BartForZeroShotClassification(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="bart_large_zero_shot_classifier_mnli", lang="en", remote_loc=None):
+    def pretrained(name="bart_large_zero_shot_classifier_mnli", lang="en", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -222,4 +222,4 @@ def pretrained(name="bart_large_zero_shot_classifier_mnli", lang="en", remote_lo
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(BartForZeroShotClassification, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(BartForZeroShotClassification, name, lang, remote_loc,engine )

python/sparknlp/annotator/classifier_dl/bert_for_multiple_choice.py

@@ -138,7 +138,7 @@ def loadSavedModel(folder, spark_session):
         return BertForMultipleChoice(java_model=jModel)
 
     @staticmethod
-    def pretrained(name="bert_base_uncased_multiple_choice", lang="en", remote_loc=None):
+    def pretrained(name="bert_base_uncased_multiple_choice", lang="en", remote_loc=None,engine ="onnx"):
         """Downloads and loads a pretrained model.
 
         Parameters
@@ -158,4 +158,4 @@ def pretrained(name="bert_base_uncased_multiple_choice", lang="en", remote_loc=N
             The restored model
         """
         from sparknlp.pretrained import ResourceDownloader
-        return ResourceDownloader.downloadModel(BertForMultipleChoice, name, lang, remote_loc)
+        return ResourceDownloader.downloadModel(BertForMultipleChoice, name, lang, remote_loc,engine )