RAdam in Tensorflow about keras-radam HOT 3 CLOSED

I forgot a return in the optimizer... It should have been fixed in 0.9.0.

from keras-radam.

Added in 0.8.0:

from keras_radam.training import RAdamOptimizer

RAdamOptimizer(learning_rate=1e-3)

from keras-radam.

Thanks for your change. However, I still get errors when trying to use it with minimize method:

TypeError Traceback (most recent call last)
in ()
61 #optimizer = tf.train.AdamOptimizer(1e-3)
62 #optimizer = tf.contrib.estimator.clip_gradients_by_norm(optimizer,clip_norm=5.0)
---> 63 training_op = optimizer.minimize(loss)

~/ML_tensorflow/lib/python3.6/site-packages/tensorflow/python/training/optimizer.py in minimize(self, loss, global_step, var_list, gate_gradients, aggregation_method, colocate_gradients_with_ops, name, grad_loss)
411
412 return self.apply_gradients(grads_and_vars, global_step=global_step,
--> 413 name=name)
414
415 def compute_gradients(self, loss, var_list=None,

~/ML_tensorflow/lib/python3.6/site-packages/tensorflow/python/training/optimizer.py in apply_gradients(self, grads_and_vars, global_step, name)
614 update_ops.append(processor.update_op(self, grad))
615 if global_step is None:
--> 616 apply_updates = self._finish(update_ops, name)
617 else:
618 with ops.control_dependencies([self._finish(update_ops, "update")]):

~/ML_tensorflow/lib/python3.6/site-packages/keras_radam/training.py in _finish(self, update_ops, name_scope)
254
255 def _finish(self, update_ops, name_scope):
--> 256 with ops.control_dependencies(update_ops):
257 step, beta1_power, beta2_power = self._get_beta_accumulators()
258 with ops.colocate_with(beta1_power):

~/ML_tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in control_dependencies(control_inputs)
5424 return NullContextmanager()
5425 else:
-> 5426 return get_default_graph().control_dependencies(control_inputs)
5427
5428

~/ML_tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in control_dependencies(self, control_inputs)
4865 (hasattr(c, "_handle") and hasattr(c, "op"))):
4866 c = c.op
-> 4867 c = self.as_graph_element(c)
4868 if isinstance(c, Tensor):
4869 c = c.op

~/ML_tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in as_graph_element(self, obj, allow_tensor, allow_operation)
3794
3795 with self._lock:
-> 3796 return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
3797
3798 def _as_graph_element_locked(self, obj, allow_tensor, allow_operation):

~/ML_tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in _as_graph_element_locked(self, obj, allow_tensor, allow_operation)
3883 # We give up!
3884 raise TypeError("Can not convert a %s into a %s." %
-> 3885 (type(obj).name, types_str))
3886
3887 def get_operations(self):

TypeError: Can not convert a NoneType into a Tensor or Operation.

from keras-radam.