onnx/optimization-receipt.json

{
  "status": "pass",
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  "parent_export_receipt_sha256": "9fc487cdfa076b4d210a526c68ff24ea9ff7ff9da78e058b21f7d610f95ccc6e",
  "validation_receipt_sha256": "85295b7612fa7f3dc785c477d7beaae14a90470c7c74911edd15c4d41fdc0aec",
  "optimizer_sha256": "d025489a7886020dbbfc5c0f9250f44ae3f372056290b42fa873bc1660e657a1",
  "onnx": "1.21.0",
  "numpy": "2.4.4",
  "method": "24 centered-integer FP32 depthwise Conv substitutions with INT32 outputs",
  "replaced_nodes": [
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    "/layers.1/conv/depthwise_conv/Conv_quant",
    "/layers.2/conv/depthwise_conv/Conv_quant",
    "/layers.3/conv/depthwise_conv/Conv_quant",
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    "/layers.7/conv/depthwise_conv/Conv_quant",
    "/layers.8/conv/depthwise_conv/Conv_quant",
    "/layers.9/conv/depthwise_conv/Conv_quant",
    "/layers.10/conv/depthwise_conv/Conv_quant",
    "/layers.11/conv/depthwise_conv/Conv_quant",
    "/layers.12/conv/depthwise_conv/Conv_quant",
    "/layers.13/conv/depthwise_conv/Conv_quant",
    "/layers.14/conv/depthwise_conv/Conv_quant",
    "/layers.15/conv/depthwise_conv/Conv_quant",
    "/layers.16/conv/depthwise_conv/Conv_quant",
    "/layers.17/conv/depthwise_conv/Conv_quant",
    "/layers.18/conv/depthwise_conv/Conv_quant",
    "/layers.19/conv/depthwise_conv/Conv_quant",
    "/layers.20/conv/depthwise_conv/Conv_quant",
    "/layers.21/conv/depthwise_conv/Conv_quant",
    "/layers.22/conv/depthwise_conv/Conv_quant",
    "/layers.23/conv/depthwise_conv/Conv_quant"
  ],
  "taps_per_kernel": 9,
  "integer_product_magnitude_bound": 65025,
  "integer_partial_sum_magnitude_bound": 585225,
  "fp32_exact_integer_limit": 16777216,
  "original_quantized_initializers_retained": true,
  "dynamic_quantization_and_scales_unchanged": true,
  "model_metadata_io_and_opsets_unchanged": true,
  "new_runtime_dependencies": [],
  "validation": {
    "per_operator_cases": 72,
    "full_encoder_cases": 4,
    "all_bit_exact": true
  },
  "optimized_graph": {
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    "ir_version": 8,
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    "inputs": [
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        "type": "FLOAT, audio_signal_dynamic_axes_1x128xaudio_signal_dynamic_axes_2"
      },
      {
        "name": "length",
        "type": "INT64, length_dynamic_axes_1"
      }
    ],
    "outputs": [
      {
        "name": "outputs",
        "type": "FLOAT, Transposeoutputs_dim_0x1024xTransposeoutputs_dim_2"
      },
      {
        "name": "encoded_lengths",
        "type": "INT64, length_dynamic_axes_1"
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    ],
    "metadata": {
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      "normalize_type": "per_feature",
      "pred_rnn_layers": "2",
      "pred_hidden": "640",
      "subsampling_factor": "8",
      "model_type": "EncDecRNNTBPEModel",
      "version": "2",
      "model_author": "NeMo",
      "url": "https://huggingface.co/oruk/orukeet#parakeet-tdt-v3",
      "comment": "Orukeet r3; standard Parakeet TDT v3 transducer graph",
      "feat_dim": "128",
      "orukeet_source_sha256": "031c8ddab4845aeced904a7cde8e8aa57993b2e344716cf83a545b079c473b56"
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      "ai.onnx::Constant",
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      "ai.onnx::Relu",
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      "ai.onnx::Sigmoid",
      "ai.onnx::Slice",
      "ai.onnx::Softmax",
      "ai.onnx::Split",
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      "ai.onnx::Sub",
      "ai.onnx::Tile",
      "ai.onnx::Transpose",
      "ai.onnx::Unsqueeze",
      "ai.onnx::Where"
    ],
    "external_files": []
  }
}