def assign_add(self, delta, use_locking=None, name=None):
   with ops.control_dependencies([
       gen_resource_variable_ops.assign_add_variable_op(
           self.handle,
           ops.convert_to_tensor(delta, dtype=self.dtype),
           name=name)
   ]):
     return self.read_value()
Example #2
0
 def assign_add(self, delta, use_locking=None, name=None):
     with ops.control_dependencies([
             gen_resource_variable_ops.assign_add_variable_op(
                 self.handle,
                 ops.convert_to_tensor(delta, dtype=self.dtype),
                 name=name)
     ]):
         return self.read_value()
Example #3
0
 def assign_add(self, delta, use_locking=None, name=None, read_value=True):
   del use_locking
   with _handle_graph(self.handle), self._assign_dependencies():
     assign_add_op = gen_resource_variable_ops.assign_add_variable_op(
         self.handle,
         ops.convert_to_tensor(delta, dtype=self.dtype),
         name=name)
   if read_value:
     return self._read_variable_op()
   return assign_add_op
 def assign_add(self, delta, use_locking=None, name=None, read_value=True):
   del use_locking
   with _handle_graph(self.handle), self._assign_dependencies():
     assign_add_op = gen_resource_variable_ops.assign_add_variable_op(
         self.handle,
         ops.convert_to_tensor(delta, dtype=self.dtype),
         name=name)
   if read_value:
     return self._read_variable_op()
   return assign_add_op
  def assign_add(self, delta, use_locking=None, name=None, read_value=True):
    """Adds a value to this variable.

    Args:
      delta: A `Tensor`. The value to add to this variable.
      use_locking: If `True`, use locking during the operation.
      name: The name to use for the operation.
      read_value: A `bool`. Whether to read and return the new value of the
          variable or not.

    Returns:
      If `read_value` is `True`, this method will return the new value of the
      variable after the assignment has completed. Otherwise, when in graph mode
      it will return the `Operation` that does the assignment, and when in eager
      mode it will return `None`.
    """
    assign_add_op = gen_resource_variable_ops.assign_add_variable_op(
        self.handle, ops.convert_to_tensor(delta, dtype=self.dtype), name=name)
    if read_value:
      return self._lazy_read(assign_add_op)
    return assign_add_op
  def assign_add(self, delta, use_locking=None, name=None, read_value=True):
    """Adds a value to this variable.

    Args:
      delta: A `Tensor`. The value to add to this variable.
      use_locking: If `True`, use locking during the operation.
      name: The name to use for the operation.
      read_value: A `bool`. Whether to read and return the new value of the
          variable or not.

    Returns:
      If `read_value` is `True`, this method will return the new value of the
      variable after the assignment has completed. Otherwise, when in graph mode
      it will return the `Operation` that does the assignment, and when in eager
      mode it will return `None`.
    """
    assign_add_op = gen_resource_variable_ops.assign_add_variable_op(
        self.handle, ops.convert_to_tensor(delta, dtype=self.dtype), name=name)
    if read_value:
      return self._lazy_read(assign_add_op)
    return assign_add_op
 def assign_add(self, delta, use_locking=None, name=None):
     return self._lazy_read(
         gen_resource_variable_ops.assign_add_variable_op(
             self.handle,
             ops.convert_to_tensor(delta, dtype=self.dtype),
             name=name))
 def assign_add(self, delta, use_locking=None, name=None):
   return self._lazy_read(gen_resource_variable_ops.assign_add_variable_op(
       self.handle,
       ops.convert_to_tensor(delta, dtype=self.dtype),
       name=name))