问题
I'm learn tensorflow2.0 from official tutorials.I can understand the result from below code.
def square_if_positive(x):
return [i ** 2 if i > 0 else i for i in x]
square_if_positive(range(-5, 5))
# result
[-5, -4, -3, -2, -1, 0, 1, 4, 9, 16]
But if I change the inputs with tensor not python code, just like this
def square_if_positive(x):
return [i ** 2 if i > 0 else i for i in x]
square_if_positive(tf.range(-5, 5))
I get below error!!
OperatorNotAllowedInGraphError Traceback (most recent call last)
<ipython-input-39-6c17f29a3443> in <module>
2 def square_if_positive(x):
3 return [i**2 if i > 0 else i for i in x]
----> 4 square_if_positive(tf.range(10))
5 # measure_graph_size(square_if_positive, range(10))
~/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in __call__(self, *args, **kwds)
437 # This is the first call of __call__, so we have to initialize.
438 initializer_map = {}
--> 439 self._initialize(args, kwds, add_initializers_to=initializer_map)
440 if self._created_variables:
441 try:
~/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in _initialize(self, args, kwds, add_initializers_to)
380 self._concrete_stateful_fn = (
381 self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access
--> 382 *args, **kwds))
383
384 def invalid_creator_scope(*unused_args, **unused_kwds):
~/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
1793 if self.input_signature:
1794 args, kwargs = None, None
-> 1795 graph_function, _, _ = self._maybe_define_function(args, kwargs)
1796 return graph_function
1797
~/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _maybe_define_function(self, args, kwargs)
2093 graph_function = self._function_cache.primary.get(cache_key, None)
2094 if graph_function is None:
-> 2095 graph_function = self._create_graph_function(args, kwargs)
2096 self._function_cache.primary[cache_key] = graph_function
2097 return graph_function, args, kwargs
~/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
1984 arg_names=arg_names,
1985 override_flat_arg_shapes=override_flat_arg_shapes,
-> 1986 capture_by_value=self._capture_by_value),
1987 self._function_attributes,
1988 # Tell the ConcreteFunction to clean up its graph once it goes out of
~/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)
851 converted_func)
852
--> 853 func_outputs = python_func(*func_args, **func_kwargs)
854
855 # invariant: `func_outputs` contains only Tensors, CompositeTensors,
~/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in wrapped_fn(*args, **kwds)
323 # __wrapped__ allows AutoGraph to swap in a converted function. We give
324 # the function a weak reference to itself to avoid a reference cycle.
--> 325 return weak_wrapped_fn().__wrapped__(*args, **kwds)
326 weak_wrapped_fn = weakref.ref(wrapped_fn)
327
~/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/framework/func_graph.py in wrapper(*args, **kwargs)
841 except Exception as e: # pylint:disable=broad-except
842 if hasattr(e, "ag_error_metadata"):
--> 843 raise e.ag_error_metadata.to_exception(type(e))
844 else:
845 raise
OperatorNotAllowedInGraphError: in converted code:
<ipython-input-37-6c17f29a3443>:3 square_if_positive *
return [i**2 if i > 0 else i for i in x]
/Users/zhangpan/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:547 __iter__
self._disallow_iteration()
/Users/zhangpan/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:540 _disallow_iteration
self._disallow_when_autograph_enabled("iterating over `tf.Tensor`")
/Users/zhangpan/tf2_workspace/tf2.0/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:518 _disallow_when_autograph_enabled
" decorating it directly with @tf.function.".format(task))
OperatorNotAllowedInGraphError: iterating over `tf.Tensor` is not allowed: AutoGraph did not convert this function. Try decorating it directly with @tf.function.
I can't find any specifications about this error. I think the real reason is not "iterating over tf.Tensor is not allowed" . Becase I can write like this.
@tf.function
def square_if_positive(x):
for i in x:
if i>0:
tf.print(i**2)
else:
tf.print(i)
square_if_positive(tf.range(10))
I iterate over tensor just like above code.
So my question is what's the real reason about this error? Any suggestions will help me. I really can't understand this error through I read a lot of materials.
回答1:
The root cause is that autograph doesn't yet support list comprehensions (primarily because it's difficult to determine the dtype of the result in all cases)
As a workaround, you can use tf.map_fn for the comprehension:
return tf.map_fn(lambda i: i ** 2 if i > 0 else i, x)
For more information please take a look at this issue
回答2:
In case it helps someone.
I had the same problem with a code that did:
for index, image in enumerate(inputs):
... My code ...
The solution was just to do:
index = 0
for image in inputs:
.... My code ...
index += 1
来源：https://stackoverflow.com/questions/57888872/how-to-fix-operatornotallowedingrapherror-error-in-tensorflow-2-0