TypeError: The JSON content is required to be a `dict`, but found <class 'list'>

Question

when I run "tensorflowjs_converter" in Python 3.7. It reported error:

TypeError: The JSON content is required to be a dict, but found class'list'.

I want to transform the file of json to keras_save_model:

tensorflowjs_converter --input_format tfjs_layers_model --output_format keras_saved_model tiny_face_js/tiny_face_detector_model-weights_manifest.json tiny_face_h5

But it failed, I looks into the json file.

[{"weights":[{"name":"conv0/filters","shape":[3,3,3,16],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.009007044399485869,"min":-1.2069439495311063}},{"name":"conv0/bias","shape":[16],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.005263455241334205,"min":-0.9211046672334858}},{"name":"conv1/depthwise_filter","shape":[3,3,16,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.004001977630690033,"min":-0.5042491814669441}},{"name":"conv1/pointwise_filter","shape":[1,1,16,32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.013836609615999109,"min":-1.411334180831909}},{"name":"conv1/bias","shape":[32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0015159862590771096,"min":-0.30926119685173037}},{"name":"conv2/depthwise_filter","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.002666276225856706,"min":-0.317286870876948}},{"name":"conv2/pointwise_filter","shape":[1,1,32,64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.015265831292844286,"min":-1.6792414422128714}},{"name":"conv2/bias","shape":[64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0020280554598453,"min":-0.37113414915168985}},{"name":"conv3/depthwise_filter","shape":[3,3,64,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006100742489683862,"min":-0.8907084034938438}},{"name":"conv3/pointwise_filter","shape":[1,1,64,128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.016276211832083907,"min":-2.0508026908425725}},{"name":"conv3/bias","shape":[128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.003394414279975143,"min":-0.7637432129944072}},{"name":"conv4/depthwise_filter","shape":[3,3,128,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006716050119961009,"min":-0.8059260143953211}},{"name":"conv4/pointwise_filter","shape":[1,1,128,256],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.021875603993733724,"min":-2.8875797271728514}},{"name":"conv4/bias","shape":[256],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0041141652009066415,"min":-0.8187188749804216}},{"name":"conv5/depthwise_filter","shape":[3,3,256,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.008423839597141042,"min":-0.9013508368940915}},{"name":"conv5/pointwise_filter","shape":[1,1,256,512],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.030007277283014035,"min":-3.8709387695088107}},{"name":"conv5/bias","shape":[512],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.008402082966823203,"min":-1.4871686851277068}},{"name":"conv8/filters","shape":[1,1,512,25],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.028336129469030042,"min":-4.675461362389957}},{"name":"conv8/bias","shape":[25],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.002268134028303857,"min":-0.41053225912299807}}],"paths":["tiny_face_detector_model-shard1"]}]

I tried to delete the "[]", it reports:

Traceback (most recent call last): File "e:\users\admin\anaconda3\envs\ai_python3.7\lib\runpy.py", line 193, in _run_module_as_main "main", mod_spec) File "e:\users\admin\anaconda3\envs\ai_python3.7\lib\runpy.py", line 85, in _run_code exec(code, run_globals) File "C:\Users\admin\AppData\Roaming\Python\Python37\Scripts\tensorflowjs_converter.exe__main__.py", line 7, in File "C:\Users\admin\AppData\Roaming\Python\Python37\site-packages\tensorflowjs\converters\converter.py", line 638, in pip_main main([' '.join(sys.argv[1:])]) File "C:\Users\admin\AppData\Roaming\Python\Python37\site-packages\tensorflowjs\converters\converter.py", line 642, in main convert(argv[0].split(' ')) File "C:\Users\admin\AppData\Roaming\Python\Python37\site-packages\tensorflowjs\converters\converter.py", line 605, in convert args.output_path) File "C:\Users\admin\AppData\Roaming\Python\Python37\site-packages\tensorflowjs\converters\converter.py", line 257, in dispatch_tensorflowjs_to_keras_saved_model_conversion model = keras_tfjs_loader.load_keras_model(config_json_path) File "C:\Users\admin\AppData\Roaming\Python\Python37\site-packages\tensorflowjs\converters\keras_tfjs_loader.py", line 194, in load_keras_model _check_config_json(config_json) File "C:\Users\admin\AppData\Roaming\Python\Python37\site-packages\tensorflowjs\converters\keras_tfjs_loader.py", line 96, in _check_config_json raise KeyError('Field "modelTopology" is missing from the JSON content.') KeyError: 'Field "modelTopology" is missing from the JSON content.' Is there any workaround to resolve the problem?

Thanks & Regards! Jun Yan

Answer 1

When you specify tfjs_layers_model as input format, the input should be model.json generated by tfjs-converter in advance. The format looks as follows.

{
  "format": "layers-model",
  "generatedBy": "1.13.1",
  "convertedBy": "TensorFlow.js Converter v1.4.0",
  "userDefinedMetadata": {
    //...
  }
}

One note is that tfjs_layers_model is only created from keras or keras_saved_model, tf_saved_model is not supported for the layers model. The command to create layers model may look like this.

$ tensorflowjs_converter \
    --input_format=keras \
    --output_format=tfjs_layers_model \
    /path/to/keras_model \
    /path/to/tfjs_model

Then you can recreate keras model like this.

$ tensorflowjs_converter \
    --input_format tfjs_layers_model \
    --output_format keras_saved_model \
    /path/to/tfjs_model/model.json \
    /path/to/tiny_face_h5

See for more detail: Converting a TensorFlow SavedModel, TensorFlow Hub module, Keras HDF5 or tf.keras SavedModel to a web-friendly format