我在这里关注微型语音示例： https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/experimental/micro/examples/micro_speech
通过高（> 95％）验证和最终测试准确性完成培训。冻结完成，没有任何警告或错误。 Toco报告不支持的数据类型和不支持的AudioMicrofrontend op。这有问题吗？
2019-07-10 13:56:39.687589: I tensorflow/lite/toco/import_tensorflow.cc:1336] Converting unsupported operation: DecodeWav
2019-07-10 13:56:39.694101: I tensorflow/lite/toco/import_tensorflow.cc:193] Unsupported data type in placeholder op: 5
2019-07-10 13:56:39.694142: I tensorflow/lite/toco/import_tensorflow.cc:1336] Converting unsupported operation: AudioMicrofrontend
2019-07-10 13:56:39.697231: I tensorflow/lite/toco/import_tensorflow.cc:1385] Unable to determine output type for op: AudioMicrofrontend
2019-07-10 13:56:39.698124: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 44 operators, 70 arrays (0 quantized)
2019-07-10 13:56:39.698328: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After Removing unused ops pass 1: 37 operators, 58 arrays (0 quantized)
2019-07-10 13:56:39.698557: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 37 operators, 58 arrays (0 quantized)
2019-07-10 13:56:39.698919: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After general graph transformations pass 1: 10 operators, 18 arrays (1 quantized)
2019-07-10 13:56:39.699006: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After general graph transformations pass 2: 9 operators, 17 arrays (1 quantized)
2019-07-10 13:56:39.699068: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After general graph transformations pass 3: 8 operators, 15 arrays (1 quantized)
2019-07-10 13:56:39.699116: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before pre-quantization graph transformations: 8 operators, 15 arrays (1 quantized)
2019-07-10 13:56:39.699138: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After pre-quantization graph transformations pass 1: 5 operators, 12 arrays (1 quantized)
2019-07-10 13:56:39.699162: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Group bidirectional sequence lstm/rnn: 5 operators, 12 arrays (1 quantized)
2019-07-10 13:56:39.699184: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before quantization graph transformations: 5 operators, 12 arrays (1 quantized)
2019-07-10 13:56:39.699315: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After quantization graph transformations pass 1: 4 operators, 11 arrays (11 quantized)
2019-07-10 13:56:39.699344: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After quantization graph transformations pass 2: 4 operators, 11 arrays (11 quantized)
2019-07-10 13:56:39.699367: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before shuffling of FC weights: 4 operators, 11 arrays (11 quantized)
2019-07-10 13:56:39.699401: I tensorflow/lite/toco/allocate_transient_arrays.cc:345] Total transient array allocated size: 2496 bytes, theoretical optimal value: 2496 bytes.
2019-07-10 13:56:39.699422: I tensorflow/lite/toco/toco_tooling.cc:436] Estimated count of arithmetic ops: 0.000448371 billion (note that a multiply-add is counted as 2 ops).
我怀疑不受支持的AudioMicrofrontend op是一个问题，因为与训练中报告的准确性相比，部署的模型的性能不佳。如何确认是否有问题？
我正在使用tensorflow master的最新代码以及Pete Warden的提交，直到2019年7月8日为止。 https://github.com/tensorflow/tensorflow/commits?author=petewarden
我尝试过以下模型：model_architecture = tiny_embedding_conv和model_architecture = tiny_conv 两者都给出相同的toco输出。