INNER CODE UNIT · Python

apply_gradients

bytedance/byteps · byteps/_keras/__init__.py:68

        def apply_gradients(self, *args, **kwargs):
            if not self._aggregated_gradients:
                raise Exception('`apply_gradients()` was called without a call to '
                                '`get_gradients()` or `_aggregate_gradients`. If you\'re '
                                'using TensorFlow 2.0, please specify '
                                '`experimental_run_tf_function=False` in `compile()`.')
            return super(self.__class__, self).apply_gradients(*args, **kwargs)

    # We dynamically create a new class that inherits from the optimizer that was passed in.
    # The goal is to override get_gradients() method with an push_pull implementation.
    # This class will have the same name as the optimizer it's wrapping, so that the saved
    # model could be easily restored without BytePS.
    cls = type(optimizer.__class__.__name__, (optimizer.__class__,),
               dict(_DistributedOptimizer.__dict__))
    return cls.from_config(optimizer.get_config())


def _eval(backend, op_or_result):

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