mindspore.ops.WhileLoop

class mindspore.ops.WhileLoop[source]

Provide a useful op for reducing compilation times of while loop. The execution logic of the WhileLoop operator can be roughly represented by the following code:

def WhileLoop(cond_func, loop_func, init_val):
    while(cond_func(init_val)):
        init_val = loop_func(init_val)
    return init_val

The current WhileLoop operator has the following syntactic limitations:

Using a side-effect function as loop_func is currently not support, such as operations that modify parameters, global variables, etc.
The return value of loop_func being of a different type or shape from the init_val is currently not support.

Warning

This is an experimental API that is subject to change or deletion.

Inputs:

cond_func (Function) - The condition function.
loop_func (Function) - The loop function, take one argument and return value has the same type with input argument.
init_val (Union[Tensor, number, str, bool, list, tuple, dict]) - The initial value.

Outputs:

Union[Tensor, number, str, bool, list, tuple, dict], the final result of the while loop, has same type and shape with input init_val .

Raises

TypeError – If cond_func is not a function.
TypeError – If loop_func is not a function.
ValueError – If loop_func cannot take init_val as input or has different output type or shape with init_val .

Supported Platforms:: Ascend GPU CPU

Examples

>>> from mindspore import ops
>>> def loop_while_fun(init_val):
...     val = init_val
...     val = val + 1
...     return val
...
>>> init_state = 10
>>> while_loop = ops.WhileLoop()
>>> result = while_loop(lambda x : x < 100, loop_while_fun, init_state)
>>> print(result)
100