tes
849ad47230
Models sourced from openwakeword==0.6.0 on the Pi (alexa_v0.1.onnx vendored as alexa.onnx). ORT 1.26.0 loads all three on linux-arm64 self-contained publish; libonnxruntime.so confirmed in publish dir. SHA-256: melspectrogram.onnx ba2b0e0f8b7b875369a2c89cb13360ff53bac436f2895cced9f479fa65eb176f embedding_model.onnx 70d164290c1d095d1d4ee149bc5e00543250a7316b59f31d056cff7bd3075c1f alexa.onnx 6ff566a01d12670e8d9e3c59da32651db1575d17272a601b7f8a39283dfbae3e
30 lines
1001 B
C#
30 lines
1001 B
C#
using Microsoft.ML.OnnxRuntime;
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string modelsDir = Path.Combine(AppContext.BaseDirectory, "models");
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string[] modelFiles = { "melspectrogram.onnx", "embedding_model.onnx", "alexa.onnx" };
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var opts = new SessionOptions
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{
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IntraOpNumThreads = 1,
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InterOpNumThreads = 1,
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LogSeverityLevel = OrtLoggingLevel.ORT_LOGGING_LEVEL_ERROR,
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};
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foreach (var f in modelFiles)
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{
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string path = Path.Combine(modelsDir, f);
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Console.WriteLine($"== {f} ==");
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using var session = new InferenceSession(path, opts);
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foreach (var kv in session.InputMetadata)
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{
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var dims = string.Join(",", kv.Value.Dimensions);
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Console.WriteLine($" input '{kv.Key}': shape=[{dims}] dtype={kv.Value.ElementType.Name}");
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}
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foreach (var kv in session.OutputMetadata)
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{
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var dims = string.Join(",", kv.Value.Dimensions);
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Console.WriteLine($" output '{kv.Key}': shape=[{dims}] dtype={kv.Value.ElementType.Name}");
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}
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}
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Console.WriteLine("All three models loaded.");
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