Support whisper models (#238)

python-api-examples/offline-decode-files.py

@@ -1,6 +1,7 @@
 #!/usr/bin/env python3
 #
 # Copyright (c)  2023 by manyeyes
+# Copyright (c)  2023  Xiaomi Corporation
 
 """
 This file demonstrates how to use sherpa-onnx Python API to transcribe
@@ -34,6 +35,27 @@ file(s) with a non-streaming model.
 
 (3) For CTC models from NeMo
 
+python3 ./python-api-examples/offline-decode-files.py \
+  --tokens=./sherpa-onnx-nemo-ctc-en-citrinet-512/tokens.txt \
+  --nemo-ctc=./sherpa-onnx-nemo-ctc-en-citrinet-512/model.onnx \
+  --num-threads=2 \
+  --decoding-method=greedy_search \
+  --debug=false \
+  ./sherpa-onnx-nemo-ctc-en-citrinet-512/test_wavs/0.wav \
+  ./sherpa-onnx-nemo-ctc-en-citrinet-512/test_wavs/1.wav \
+  ./sherpa-onnx-nemo-ctc-en-citrinet-512/test_wavs/8k.wav
+
+(4) For Whisper models
+
+python3 ./python-api-examples/offline-decode-files.py \
+  --whisper-encoder=./sherpa-onnx-whisper-base.en/base.en-encoder.int8.onnx \
+  --whisper-decoder=./sherpa-onnx-whisper-base.en/base.en-decoder.int8.onnx \
+  --tokens=./sherpa-onnx-whisper-base.en/base.en-tokens.txt \
+  --num-threads=1 \
+  ./sherpa-onnx-whisper-base.en/test_wavs/0.wav \
+  ./sherpa-onnx-whisper-base.en/test_wavs/1.wav \
+  ./sherpa-onnx-whisper-base.en/test_wavs/8k.wav
+
 Please refer to
 https://k2-fsa.github.io/sherpa/onnx/index.html
 to install sherpa-onnx and to download the pre-trained models
@@ -144,6 +166,20 @@ def get_args():
         help="Number of threads for neural network computation",
     )
 
+    parser.add_argument(
+        "--whisper-encoder",
+        default="",
+        type=str,
+        help="Path to whisper encoder model",
+    )
+
+    parser.add_argument(
+        "--whisper-decoder",
+        default="",
+        type=str,
+        help="Path to whisper decoder model",
+    )
+
     parser.add_argument(
         "--decoding-method",
         type=str,
@@ -247,6 +283,8 @@ def main():
     if args.encoder:
         assert len(args.paraformer) == 0, args.paraformer
         assert len(args.nemo_ctc) == 0, args.nemo_ctc
+        assert len(args.whisper_encoder) == 0, args.whisper_encoder
+        assert len(args.whisper_decoder) == 0, args.whisper_decoder
 
         contexts = [x.strip().upper() for x in args.contexts.split("/") if x.strip()]
         if contexts:
@@ -271,6 +309,9 @@ def main():
         )
     elif args.paraformer:
         assert len(args.nemo_ctc) == 0, args.nemo_ctc
+        assert len(args.whisper_encoder) == 0, args.whisper_encoder
+        assert len(args.whisper_decoder) == 0, args.whisper_decoder
+
         assert_file_exists(args.paraformer)
 
         recognizer = sherpa_onnx.OfflineRecognizer.from_paraformer(
@@ -283,6 +324,11 @@ def main():
             debug=args.debug,
         )
     elif args.nemo_ctc:
+        assert len(args.whisper_encoder) == 0, args.whisper_encoder
+        assert len(args.whisper_decoder) == 0, args.whisper_decoder
+
+        assert_file_exists(args.nemo_ctc)
+
         recognizer = sherpa_onnx.OfflineRecognizer.from_nemo_ctc(
             model=args.nemo_ctc,
             tokens=args.tokens,
@@ -292,6 +338,18 @@ def main():
             decoding_method=args.decoding_method,
             debug=args.debug,
         )
+    elif args.whisper_encoder:
+        assert_file_exists(args.whisper_encoder)
+        assert_file_exists(args.whisper_decoder)
+
+        recognizer = sherpa_onnx.OfflineRecognizer.from_whisper(
+            encoder=args.whisper_encoder,
+            decoder=args.whisper_decoder,
+            tokens=args.tokens,
+            num_threads=args.num_threads,
+            decoding_method=args.decoding_method,
+            debug=args.debug,
+        )
     else:
         print("Please specify at least one model")
         return