Update zeroshot.py

zeroshot.py

@@ -151,7 +151,7 @@ def process(
         device = torch.device("mps")
     else:
         device = torch.device("cpu")
-    device = torch.device("cpu")
+    #device = torch.device("cpu")
     model.to(device)
     inputs = inputs.to(device)
     yield transcription, logs.add(f"Using device: {device}")
@@ -176,9 +176,7 @@ def process(
     except Exception as e:
         yield f"ERROR: Creating lexicon failed '{str(e)}'", logs.text
         return
-    # for k, v in lexicon.items():
-    #     if len(v) < 5:
-    #         print(k, v)
+
     yield transcription, logs.add(f"Leixcon size: {len(lexicon)}")
 
     # Input could be sentences OR list of words. Check if atleast one word has a count > 1 to diffentiate
@@ -200,11 +198,6 @@ def process(
         # HACK: generate a bigram LM from unigram LM and a dummy bigram to trick it
         maybe_generate_pseudo_bigram_arpa(lm_path)
 
-    # for k, v in lexicon.items():
-    #     if len(v) < 5:
-    #         print(k, v)
-
-    # print(lexicon["the"], lexicon["\"(t)he"])
     with tempfile.NamedTemporaryFile() as lexicon_file:
         if lm_path is not None and not lm_path.strip():
             lm_path = None
@@ -247,8 +240,8 @@ def process(
     yield transcription, logs.add(f"[DONE]")
 
 
-for i in process("upload/english/english.mp3", "upload/english/c4_5k_sentences.txt"):
-    print(i)
+# for i in process("upload/english/english.mp3", "upload/english/c4_5k_sentences.txt"):
+#     print(i)
 
 
 # for i in process("upload/ligurian/ligurian_1.mp3", "upload/ligurian/zenamt_5k_sentences.txt"):