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| author | Kshitij Sisodia <kshitij.sisodia@arm.com> | 2021-05-20 11:18:53 +0100 |
|---|---|---|
| committer | Kshitij Sisodia <kshitij.sisodia@arm.com> | 2021-05-20 12:57:49 +0000 |
| commit | e12ac836d2110403475d0e8b4bdfec03a0874f6c (patch) | |
| tree | 2f4ac0a379cd2cf6d5ad9bc11c2a0c14abb740c3 /set_up_default_resources.py | |
| parent | 659fcd951ac18d1ee7737a6ddf6a3ec162c73ca5 (diff) | |
| download | ml-embedded-evaluation-kit-e12ac836d2110403475d0e8b4bdfec03a0874f6c.tar.gz | |
MLECO-1883: Updating wav2letter model
Using the new pruned wav2letter model from Arm Model Zoo.
The new model when optimised by Vela, produces a tflite
file ~10 MB smaller than the current.
Change-Id: I4ab6007c5b6111f41d8097e29b2af6cde2abc457
Diffstat (limited to 'set_up_default_resources.py')
| -rwxr-xr-x | set_up_default_resources.py | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/set_up_default_resources.py b/set_up_default_resources.py index 79b0333..7639364 100755 --- a/set_up_default_resources.py +++ b/set_up_default_resources.py @@ -36,12 +36,12 @@ json_uc_res = [{ }, { "use_case_name": "asr", - "resources": [{"name": "wav2letter_int8.tflite", - "url": "https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/wav2letter_int8.tflite"}, + "resources": [{"name": "wav2letter_pruned_int8.tflite", + "url": "https://github.com/ARM-software/ML-zoo/raw/1a92aa08c0de49a7304e0a7f3f59df6f4fd33ac8/models/speech_recognition/wav2letter/tflite_pruned_int8/wav2letter_pruned_int8.tflite"}, {"name": "ifm0.npy", - "url": "https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_input/input_2_int8/0.npy"}, + "url": "https://github.com/ARM-software/ML-zoo/raw/1a92aa08c0de49a7304e0a7f3f59df6f4fd33ac8/models/speech_recognition/wav2letter/tflite_pruned_int8/testing_input/input_2_int8/0.npy"}, {"name": "ofm0.npy", - "url": "https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_output/Identity_int8/0.npy"}] + "url": "https://github.com/ARM-software/ML-zoo/raw/1a92aa08c0de49a7304e0a7f3f59df6f4fd33ac8/models/speech_recognition/wav2letter/tflite_pruned_int8/testing_output/Identity_int8/0.npy"}] }, { "use_case_name": "img_class", @@ -63,12 +63,12 @@ json_uc_res = [{ }, { "use_case_name": "kws_asr", - "resources": [{"name": "wav2letter_int8.tflite", - "url": "https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/wav2letter_int8.tflite"}, + "resources": [{"name": "wav2letter_pruned_int8.tflite", + "url": "https://github.com/ARM-software/ML-zoo/raw/1a92aa08c0de49a7304e0a7f3f59df6f4fd33ac8/models/speech_recognition/wav2letter/tflite_pruned_int8/wav2letter_pruned_int8.tflite"}, {"sub_folder": "asr", "name": "ifm0.npy", - "url": "https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_input/input_2_int8/0.npy"}, + "url": "https://github.com/ARM-software/ML-zoo/raw/1a92aa08c0de49a7304e0a7f3f59df6f4fd33ac8/models/speech_recognition/wav2letter/tflite_pruned_int8/testing_input/input_2_int8/0.npy"}, {"sub_folder": "asr", "name": "ofm0.npy", - "url": "https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_output/Identity_int8/0.npy"}, + "url": "https://github.com/ARM-software/ML-zoo/raw/1a92aa08c0de49a7304e0a7f3f59df6f4fd33ac8/models/speech_recognition/wav2letter/tflite_pruned_int8/testing_output/Identity_int8/0.npy"}, {"name": "ds_cnn_clustered_int8.tflite", "url": "https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/keyword_spotting/ds_cnn_large/tflite_clustered_int8/ds_cnn_clustered_int8.tflite"}, {"sub_folder": "kws", "name": "ifm0.npy", |