(() => {
  // src/model.js
  window.modelJSON = {
    format: "layers-model",
    generatedBy: "keras v2.4.0",
    convertedBy: "TensorFlow.js Converter v3.7.0",
    modelTopology: {
      keras_version: "2.4.0",
      backend: "tensorflow",
      model_config: {
        class_name: "Sequential",
        config: {
          name: "sequential",
          layers: [
            {
              class_name: "InputLayer",
              config: {
                batch_input_shape: [null, null, 80, 1],
                dtype: "float32",
                sparse: false,
                ragged: false,
                name: "conv2d_input"
              }
            },
            {
              class_name: "Conv2D",
              config: {
                name: "conv2d",
                trainable: true,
                batch_input_shape: [null, null, 80, 1],
                dtype: "float32",
                filters: 40,
                kernel_size: [3, 3],
                strides: [1, 1],
                padding: "same",
                data_format: "channels_last",
                dilation_rate: [1, 1],
                groups: 1,
                activation: "relu",
                use_bias: true,
                kernel_initializer: {
                  class_name: "GlorotUniform",
                  config: { seed: null }
                },
                bias_initializer: { class_name: "Zeros", config: {} },
                kernel_regularizer: null,
                bias_regularizer: null,
                activity_regularizer: null,
                kernel_constraint: null,
                bias_constraint: null
              }
            },
            {
              class_name: "MaxPooling2D",
              config: {
                name: "max_pooling2d",
                trainable: true,
                dtype: "float32",
                pool_size: [2, 2],
                padding: "same",
                strides: [2, 2],
                data_format: "channels_last"
              }
            },
            {
              class_name: "Conv2D",
              config: {
                name: "conv2d_1",
                trainable: true,
                dtype: "float32",
                filters: 60,
                kernel_size: [3, 3],
                strides: [1, 1],
                padding: "same",
                data_format: "channels_last",
                dilation_rate: [1, 1],
                groups: 1,
                activation: "relu",
                use_bias: true,
                kernel_initializer: {
                  class_name: "GlorotUniform",
                  config: { seed: null }
                },
                bias_initializer: { class_name: "Zeros", config: {} },
                kernel_regularizer: null,
                bias_regularizer: null,
                activity_regularizer: null,
                kernel_constraint: null,
                bias_constraint: null
              }
            },
            {
              class_name: "MaxPooling2D",
              config: {
                name: "max_pooling2d_1",
                trainable: true,
                dtype: "float32",
                pool_size: [2, 2],
                padding: "same",
                strides: [2, 2],
                data_format: "channels_last"
              }
            },
            {
              class_name: "Reshape",
              config: {
                name: "reshape",
                trainable: true,
                dtype: "float32",
                target_shape: [-1, 1200]
              }
            },
            {
              class_name: "Bidirectional",
              config: {
                name: "bidi",
                trainable: true,
                dtype: "float32",
                layer: {
                  class_name: "LSTM",
                  config: {
                    name: "lstm",
                    trainable: true,
                    dtype: "float32",
                    return_sequences: true,
                    return_state: false,
                    go_backwards: false,
                    stateful: false,
                    unroll: false,
                    time_major: false,
                    units: 200,
                    activation: "tanh",
                    recurrent_activation: "sigmoid",
                    use_bias: true,
                    kernel_initializer: {
                      class_name: "GlorotUniform",
                      config: { seed: null }
                    },
                    recurrent_initializer: {
                      class_name: "Orthogonal",
                      config: { gain: 1, seed: null }
                    },
                    bias_initializer: { class_name: "Zeros", config: {} },
                    unit_forget_bias: true,
                    kernel_regularizer: null,
                    recurrent_regularizer: null,
                    bias_regularizer: null,
                    activity_regularizer: null,
                    kernel_constraint: null,
                    recurrent_constraint: null,
                    bias_constraint: null,
                    dropout: 0,
                    recurrent_dropout: 0,
                    implementation: 2
                  }
                },
                merge_mode: "concat"
              }
            },
            {
              class_name: "Dense",
              config: {
                name: "dense",
                trainable: true,
                dtype: "float32",
                units: 22,
                activation: "softmax",
                use_bias: true,
                kernel_initializer: {
                  class_name: "GlorotUniform",
                  config: { seed: null }
                },
                bias_initializer: { class_name: "Zeros", config: {} },
                kernel_regularizer: null,
                bias_regularizer: null,
                activity_regularizer: null,
                kernel_constraint: null,
                bias_constraint: null
              }
            }
          ]
        }
      },
      training_config: {
        loss: null,
        metrics: null,
        weighted_metrics: null,
        loss_weights: null,
        optimizer_config: {
          class_name: "RMSprop",
          config: {
            name: "RMSprop",
            learning_rate: 1e-3,
            decay: 0,
            rho: 0.9,
            momentum: 0,
            epsilon: 1e-7,
            centered: false
          }
        }
      }
    },
    weightsManifest: [
      {
        paths: ["group1-shard1of1.bin"],
        weights: [
          {
            name: "bidi/forward_lstm/lstm_cell_4/kernel",
            shape: [1200, 800],
            dtype: "float32"
          },
          {
            name: "bidi/forward_lstm/lstm_cell_4/recurrent_kernel",
            shape: [200, 800],
            dtype: "float32"
          },
          {
            name: "bidi/forward_lstm/lstm_cell_4/bias",
            shape: [800],
            dtype: "float32"
          },
          {
            name: "bidi/backward_lstm/lstm_cell_5/kernel",
            shape: [1200, 800],
            dtype: "float32"
          },
          {
            name: "bidi/backward_lstm/lstm_cell_5/recurrent_kernel",
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            dtype: "float32"
          },
          {
            name: "bidi/backward_lstm/lstm_cell_5/bias",
            shape: [800],
            dtype: "float32"
          },
          { name: "conv2d/kernel", shape: [3, 3, 1, 40], dtype: "float32" },
          { name: "conv2d/bias", shape: [40], dtype: "float32" },
          { name: "conv2d_1/kernel", shape: [3, 3, 40, 60], dtype: "float32" },
          { name: "conv2d_1/bias", shape: [60], dtype: "float32" },
          { name: "dense/kernel", shape: [400, 22], dtype: "float32" },
          { name: "dense/bias", shape: [22], dtype: "float32" }
        ]
      }
    ]
  };
})();