Function _createKerasModel

tfjs-converter/python/test_pip_package.py:44–74

Create a Keras model for testing. Args: layer_name_prefix: A prefix string for layer names. This helps avoid clashes in layer names between different test methods. h5_path: Optional string path for a HDF5 (.h5) file to save the model in. Returns: An instance of tf_keras

(layer_name_prefix, h5_path=None)

def _createKerasModel(layer_name_prefix, h5_path=None):
  """Create a Keras model for testing.

  Args:
    layer_name_prefix: A prefix string for layer names. This helps avoid
      clashes in layer names between different test methods.
    h5_path: Optional string path for a HDF5 (.h5) file to save the model
      in.

  Returns:
    An instance of tf_keras.Model.
  """
  input_tensor = tf_keras.layers.Input((3, ))
  dense1 = tf_keras.layers.Dense(
      4,
      use_bias=True,
      kernel_initializer='ones',
      bias_initializer='zeros',
      name=layer_name_prefix + '1')(input_tensor)
  output = tf_keras.layers.Dense(
      2,
      use_bias=False,
      kernel_initializer='ones',
      name=layer_name_prefix + '2')(dense1)
  model = tf_keras.models.Model(inputs=[input_tensor], outputs=[output])
  model.compile(optimizer='adam', loss='binary_crossentropy')
  model.predict(tf.ones((1, 3)), steps=1)

  if h5_path:
    model.save(h5_path, save_format='h5')
  return model

def _createTensorFlowSavedModelV1(name_scope, save_path):
  """Create a TensorFlow SavedModel for testing.