Gets a classifier model.
()
| 135 | is_regression = num_classes == 1 |
| 136 | |
| 137 | def _get_classifier_model(): |
| 138 | """Gets a classifier model.""" |
| 139 | classifier_model, core_model = ( |
| 140 | bert_models.classifier_model( |
| 141 | bert_config, |
| 142 | num_classes, |
| 143 | max_seq_length, |
| 144 | hub_module_url=FLAGS.hub_module_url, |
| 145 | hub_module_trainable=FLAGS.hub_module_trainable)) |
| 146 | optimizer = optimization.create_optimizer(initial_lr, |
| 147 | steps_per_epoch * epochs, |
| 148 | warmup_steps, FLAGS.end_lr, |
| 149 | FLAGS.optimizer_type) |
| 150 | classifier_model.optimizer = performance.configure_optimizer( |
| 151 | optimizer, |
| 152 | use_float16=common_flags.use_float16()) |
| 153 | return classifier_model, core_model |
| 154 | |
| 155 | # tf_keras.losses objects accept optional sample_weight arguments (eg. coming |
| 156 | # from the dataset) to compute weighted loss, as used for the regression |
nothing calls this directly
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