(input_dim, num_hidden, output_dim)
| 33 | |
| 34 | |
| 35 | def _get_model(input_dim, num_hidden, output_dim): |
| 36 | model = keras.models.Sequential() |
| 37 | model.add(keras.layers.Dense(num_hidden, |
| 38 | activation='relu', |
| 39 | input_shape=(input_dim,))) |
| 40 | model.add(keras.layers.Dense(output_dim, activation='softmax')) |
| 41 | return model |
| 42 | |
| 43 | |
| 44 | @keras_parameterized.run_all_keras_modes |