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HDF5格式模型的转换,其他模型转换建议参考:https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/convert/cmdline_examples.md +Quantization 模型转换 +-------------------------------------------- + 还有一种quantization的转化方法,这种转化命令如下: .. code-block:: bash @@ -143,13 +188,19 @@ Keras Sequential save方法 --output_format=GRAPHVIZ_DOT \ --keras_model_file=mnist_cnn.h5 -dot是一种graph description language,可以同graphz的dot命令转化为pdf或svg等可视化图。 +dot是一种graph description language,可以用graphz的dot命令转化为pdf或png等可视化图。 .. code-block:: bash - dot -Tpdf -O keras_mnist.dot + dot -Tpng -O keras_mnist.dot + +这样就转化为一张图了,如下: + +.. figure:: ../_static/image/deployment/keras_mnist.dot.png + :width: 80% + :align: center -这样就转化为一个一张图了,很明显的可以看到如下信息: +很明显的可以看到如下信息: 入口: @@ -166,7 +217,32 @@ dot是一种graph description language,可以同graphz的dot命令转化为pdf dense_2/Softmax Type: Float [1×10] -TODO: mean和std尚未理解清楚,待研究 +因此,可以知道 + +``--input_arrays`` 就是 ``conv2d_1_input`` + +``--output_arrays`` 就是 ``dense_2/Softmax`` + +``--default_ranges_min`` 就是 ``0`` + +``--default_ranges_max`` 就是 ``255`` + + +关于``--mean_values``和``--std_dev_values``的用途:: + + QUANTIZED_UINT8的quantized模型期望的输入是[0,255], 需要有个跟原始的float类型输入有个对应关系。 + + mean_values和std_dev_values就是为了实现这个对应关系 + + mean_values对应float的float_min + + std_dev_values对应255 / (float_max - float_min) + +因此,可以知道 + +``--mean_values``就是``0`` + +``--std_dev_values``就是``1`` Android部署 -----------------------------