llsourcell / generative_adversarial_networks_live Goto Github PK

/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.pyc in minimize(self, loss, global_step, var_list, gate_gradients, aggregation_method, colocate_gradients_with_ops, name, grad_loss)
    323 
    324     return self.apply_gradients(grads_and_vars, global_step=global_step,
--> 325                                 name=name)
    326 
    327   def compute_gradients(self, loss, var_list=None,

/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.pyc in apply_gradients(self, grads_and_vars, global_step, name)
    444                        ([str(v) for _, _, v in converted_grads_and_vars],))
    445     with ops.control_dependencies(None):
--> 446       self._create_slots([_get_variable_for(v) for v in var_list])
    447     update_ops = []
    448     with ops.name_scope(name, self._name) as name:

/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/adam.pyc in _create_slots(self, var_list)
    130     # Create slots for the first and second moments.
    131     for v in var_list:
--> 132       self._zeros_slot(v, "m", self._name)
    133       self._zeros_slot(v, "v", self._name)
    134 

/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.pyc in _zeros_slot(self, var, slot_name, op_name)
    764     named_slots = self._slot_dict(slot_name)
    765     if _var_key(var) not in named_slots:
--> 766       named_slots[_var_key(var)] = slot_creator.create_zeros_slot(var, op_name)
    767     return named_slots[_var_key(var)]

/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/slot_creator.pyc in create_zeros_slot(primary, name, dtype, colocate_with_primary)
    172     return create_slot_with_initializer(
    173         primary, initializer, slot_shape, dtype, name,
--> 174         colocate_with_primary=colocate_with_primary)
    175   else:
    176     val = array_ops.zeros(slot_shape, dtype=dtype)

/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/slot_creator.pyc in create_slot_with_initializer(primary, initializer, shape, dtype, name, colocate_with_primary)
    144       with ops.colocate_with(primary):
    145         return _create_slot_var(primary, initializer, "", validate_shape, shape,
--> 146                                 dtype)
    147     else:
    148       return _create_slot_var(primary, initializer, "", validate_shape, shape,

/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/slot_creator.pyc in _create_slot_var(primary, val, scope, validate_shape, shape, dtype)
     64       use_resource=_is_resource(primary),
     65       shape=shape, dtype=dtype,
---> 66       validate_shape=validate_shape)
     67   variable_scope.get_variable_scope().set_partitioner(current_partitioner)
     68 

/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter)
   1063       collections=collections, caching_device=caching_device,
   1064       partitioner=partitioner, validate_shape=validate_shape,
-> 1065       use_resource=use_resource, custom_getter=custom_getter)
   1066 get_variable_or_local_docstring = (
   1067     """%s

/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, var_store, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter)
    960           collections=collections, caching_device=caching_device,
    961           partitioner=partitioner, validate_shape=validate_shape,
--> 962           use_resource=use_resource, custom_getter=custom_getter)
    963 
    964   def _get_partitioned_variable(self,

/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.pyc in get_variable(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter)
    365           reuse=reuse, trainable=trainable, collections=collections,
    366           caching_device=caching_device, partitioner=partitioner,
--> 367           validate_shape=validate_shape, use_resource=use_resource)
    368 
    369   def _get_partitioned_variable(

/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.pyc in _true_getter(name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource)
    350           trainable=trainable, collections=collections,
    351           caching_device=caching_device, validate_shape=validate_shape,
--> 352           use_resource=use_resource)
    353 
    354     if custom_getter is not None:

/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.pyc in _get_single_variable(self, name, shape, dtype, initializer, regularizer, partition_info, reuse, trainable, collections, caching_device, validate_shape, use_resource)
    680       raise ValueError("Variable %s does not exist, or was not created with "
    681                        "tf.get_variable(). Did you mean to set reuse=None in "
--> 682                        "VarScope?" % name)
    683     if not shape.is_fully_defined() and not initializing_from_value:
    684       raise ValueError("Shape of a new variable (%s) must be fully defined, "

ValueError: Variable d_w1/Adam/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope?