Comments (9)
kyakuno
commented on September 27, 2024
fugumt-ja-enとfugumt-en-jaで、
diff source.spm target.spm
を実行するとdiffがなく、どちらも同じトークンを持っている。
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kyakuno
commented on September 27, 2024
transformesをimportすると230msかかるが、ailia_tokenizerだと3msでロードできる。
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kyakuno
commented on September 27, 2024
トークンの一致確認。
kyakuno@mbakk fugumt-en-ja % python3 fugumt-en-ja.py --disable_ailia_tokenizer
INFO arg_utils.py (13) : Start!
INFO arg_utils.py (163) : env_id: 2
INFO arg_utils.py (166) : MPSDNN-Apple M2
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO fugumt-en-ja.py (257) : input_text: This is a cat.
INFO fugumt-en-ja.py (260) : Start inference...
{'input_ids': [183, 30, 15, 11126, 4, 0], 'attention_mask': [1, 1, 1, 1, 1, 1]}
INFO fugumt-en-ja.py (279) : translation_text: これは猫です。
INFO fugumt-en-ja.py (281) : Script finished successfully.
kyakuno@mbakk fugumt-en-ja % python3 fugumt-en-ja.py
INFO arg_utils.py (13) : Start!
INFO arg_utils.py (163) : env_id: 2
INFO arg_utils.py (166) : MPSDNN-Apple M2
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO fugumt-en-ja.py (257) : input_text: This is a cat.
INFO fugumt-en-ja.py (260) : Start inference...
{'input_ids': [183, 30, 15, 11126, 4, 0], 'attention_mask': [1, 1, 1, 1, 1, 1]}
INFO fugumt-en-ja.py (279) : translation_text: これは猫です。
INFO fugumt-en-ja.py (281) : Script finished successfully.
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kyakuno
commented on September 27, 2024
kyakuno@mbakk multilingual-e5 % python3 multilingual-e5.py
INFO arg_utils.py (13) : Start!
INFO arg_utils.py (163) : env_id: 2
INFO arg_utils.py (166) : MPSDNN-Apple M2
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO multilingual-e5.py (152) : Generating embeddings...
[[ 0 46692 12 ... 1 1 1]
[ 0 46692 12 ... 1 1 1]
[ 0 46692 12 ... 1 1 1]
...
[ 0 46692 12 ... 1 1 1]
[ 0 46692 12 ... 1 1 1]
[ 0 46692 12 ... 1 1 1]] [[1 1 1 ... 0 0 0]
[1 1 1 ... 0 0 0]
[1 1 1 ... 0 0 0]
...
[1 1 1 ... 0 0 0]
[1 1 1 ... 0 0 0]
[1 1 1 ... 0 0 0]]
User (press q to exit):
kyakuno@mbakk multilingual-e5 % python3 multilingual-e5.py --disable_ailia_tokenizer
INFO arg_utils.py (13) : Start!
INFO arg_utils.py (163) : env_id: 2
INFO arg_utils.py (166) : MPSDNN-Apple M2
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO multilingual-e5.py (152) : Generating embeddings...
[[ 0 46692 12 ... 1 1 1]
[ 0 46692 12 ... 1 1 1]
[ 0 46692 12 ... 1 1 1]
...
[ 0 46692 12 ... 1 1 1]
[ 0 46692 12 ... 1 1 1]
[ 0 46692 12 ... 1 1 1]] [[1 1 1 ... 0 0 0]
[1 1 1 ... 0 0 0]
[1 1 1 ... 0 0 0]
...
[1 1 1 ... 0 0 0]
[1 1 1 ... 0 0 0]
[1 1 1 ... 0 0 0]]
User (press q to exit):
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kyakuno
commented on September 27, 2024
kyakuno@mbakk multilingual-e5 % python3 multilingual-e5.py
INFO arg_utils.py (13) : Start!
INFO arg_utils.py (163) : env_id: 2
INFO arg_utils.py (166) : MPSDNN-Apple M2
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO multilingual-e5.py (150) : Generating embeddings...
User (press q to exit): NPUとは何ですか。
Text: NNAPIの概要NNAPIはAndroidでNPU (Neural Processing Unit)を使用するためのローレベルAPIです。 (Similarity:0.860)
User (press q to exit): q
kyakuno@mbakk multilingual-e5 % python3 multilingual-e5.py --disable_ailia_tokenizer
INFO arg_utils.py (13) : Start!
INFO arg_utils.py (163) : env_id: 2
INFO arg_utils.py (166) : MPSDNN-Apple M2
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO multilingual-e5.py (150) : Generating embeddings...
User (press q to exit): NPUとは何ですか。
Text: NNAPIの概要NNAPIはAndroidでNPU (Neural Processing Unit)を使用するためのローレベルAPIです。 (Similarity:0.860)
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kyakuno
commented on September 27, 2024
CLAPの場合、ailia_tokenizerがmax_lengthに対応していないので、対応が必要。
kyakuno@mbakk clap % python3 clap.py --disable_ailia_tokenizer
INFO arg_utils.py (13) : Start!
INFO arg_utils.py (163) : env_id: 2
INFO arg_utils.py (166) : MPSDNN-Apple M2
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO model_utils.py (109) : vocab.json is prepared!
INFO model_utils.py (109) : merges.txt is prepared!
input_ids [[ 0 3340 462 17498 19477 3741 1115 2 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 133 2180 16 3741 12040 4 2 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 100 657 5 5709 2088 2239 2 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 11312 2 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 32460 7742 2 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 12592 5 1883 4 2 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 3340 462 17498 2 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 16319 2 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 16319 35828 2 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]]
attention_mask [[1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]]
===== cosine similality between text and audio =====
audio: input.wav
cossim=0.1512, word=applause applaud clap
cossim=0.2943, word=The crowd is clapping.
cossim=0.0385, word=I love the contrastive learning
cossim=0.0751, word=bell
cossim=-0.0928, word=soccer
cossim=0.0308, word=open the door.
cossim=0.0850, word=applause
cossim=0.4189, word=dog
cossim=0.3810, word=dog barking
INFO clap.py (211) : Script finished successfully.
kyakuno@mbakk clap % python3 clap.py
INFO arg_utils.py (13) : Start!
INFO arg_utils.py (163) : env_id: 2
INFO arg_utils.py (166) : MPSDNN-Apple M2
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO model_utils.py (89) : ONNX file and Prototxt file are prepared!
INFO model_utils.py (109) : vocab.json is prepared!
INFO model_utils.py (109) : merges.txt is prepared!
input_ids [[ 0 3340 462 17498 19477 3741 1115 2 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 133 2180 16 3741 12040 4 2 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 100 657 5 5709 2088 2239 2 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 11312 2 10975 10975 10975 10975 10975 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 32460 7742 2 10975 10975 10975 10975 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 12592 5 1883 4 2 10975 10975 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 3340 462 17498 2 10975 10975 10975 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 16319 2 10975 10975 10975 10975 10975 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]
[ 0 16319 35828 2 10975 10975 10975 10975 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1]]
attention_mask [[1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]
[1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0]]
===== cosine similality between text and audio =====
audio: input.wav
cossim=0.1512, word=applause applaud clap
cossim=0.2943, word=The crowd is clapping.
cossim=0.0385, word=I love the contrastive learning
cossim=0.0751, word=bell
cossim=-0.0928, word=soccer
cossim=0.0308, word=open the door.
cossim=0.0850, word=applause
cossim=0.4189, word=dog
cossim=0.3810, word=dog barking
INFO clap.py (212) : Script finished successfully.
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kyakuno
commented on September 27, 2024
BertMaskedLMの辞書ファイルとvocab。動的にダウンロードが必要。
https://storage.googleapis.com/ailia-models/bert_maskedlm/ipadic.zip
https://storage.googleapis.com/ailia-models/bert_maskedlm/vocab_character.txt
https://storage.googleapis.com/ailia-models/bert_maskedlm/vocab_wordpiece.txt
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kyakuno
commented on September 27, 2024
distil-whisperでなぜかspecial tokensが入る。
disable_ailia_tokenizer
[634, 19737, 220, 15456, 576, 312, 22654, 337, 6148, 11, 220, 33886, 2600, 293, 21005, 293, 25267, 2640, 11811, 293, 4046, 5839, 1756, 3755, 220, 1353, 312, 6632, 1493, 484, 294, 220, 392, 618, 11, 8532, 292, 11, 7693, 12, 35293, 1147, 292, 4880, 13]
He hoped there would be stew for dinner, turnips and carrots and bruised potatoes and fat mutton pieces to be ladled out in thick, peppered, flour-fattened sauce.
enable_ailia_tokenizer
[50258, 50259, 50359, 50363, 634, 19737, 220, 15456, 576, 312, 22654, 337, 6148, 11, 220, 33886, 2600, 293, 21005, 293, 25267, 2640, 11811, 293, 4046, 5839, 1756, 3755, 220, 1353, 312, 6632, 1493, 484, 294, 220, 392, 618, 11, 8532, 292, 11, 7693, 12, 35293, 1147, 292, 4880, 13, 50257]
<|startoftranscript|><|en|><|transcribe|><|notimestamps|> He hoped there would be stew for dinner, turnips and carrots and bruised potatoes and fat mutton pieces to be ladled out in thick, peppered, flour-fattened sauce.<|endoftext|>
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kyakuno
commented on September 27, 2024
なぜかall_special_idsでstartoftranscriptが列挙されない。
->
IDを返さないといけなかった。
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