Thanks for your code! When I trained ista_net.py, I met an error:
batch_size=64)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\training.py", line 66, in _method_wrapper
return method(self, *args, **kwargs)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\training.py", line 848, in fit
tmp_logs = train_function(iterator)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\eager\def_function.py", line 580, in call
result = self._call(*args, **kwds)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\eager\def_function.py", line 627, in _call
self._initialize(args, kwds, add_initializers_to=initializers)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\eager\def_function.py", line 506, in _initialize
*args, **kwds))
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\eager\function.py", line 2446, in _get_concrete_function_internal_garbage_collected
graph_function, _, _ = self._maybe_define_function(args, kwargs)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\eager\function.py", line 2777, in _maybe_define_function
graph_function = self._create_graph_function(args, kwargs)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\eager\function.py", line 2667, in _create_graph_function
capture_by_value=self._capture_by_value),
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\framework\func_graph.py", line 981, in func_graph_from_py_func
func_outputs = python_func(*func_args, **func_kwargs)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\eager\def_function.py", line 441, in wrapped_fn
return weak_wrapped_fn().wrapped(*args, **kwds)
File "D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\framework\func_graph.py", line 968, in wrapper
raise e.ag_error_metadata.to_exception(e)
TypeError: in user code:
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\training.py:571 train_function *
outputs = self.distribute_strategy.run(
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:951 run **
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2290 call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2649 _call_for_each_replica
return fn(*args, **kwargs)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\training.py:543 train_step **
self.compiled_metrics.update_state(y, y_pred, sample_weight)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\compile_utils.py:391 update_state
self._build(y_pred, y_true)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\compile_utils.py:322 _build
self._metrics, y_true, y_pred)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\util\nest.py:1118 map_structure_up_to
**kwargs)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\util\nest.py:1214 map_structure_with_tuple_paths_up_to
*flat_value_lists)]
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\util\nest.py:1213 <listcomp>
results = [func(*args, **kwargs) for args in zip(flat_path_list,
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\util\nest.py:1116 <lambda>
lambda _, *values: func(*values), # Discards the path arg.
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\compile_utils.py:421 _get_metric_objects
return [self._get_metric_object(m, y_t, y_p) for m in metrics]
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\compile_utils.py:421 <listcomp>
return [self._get_metric_object(m, y_t, y_p) for m in metrics]
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\keras\engine\compile_utils.py:439 _get_metric_object
if metric not in ['accuracy', 'acc', 'crossentropy', 'ce']:
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\ops\math_ops.py:1491 tensor_equals
return gen_math_ops.equal(self, other, incompatible_shape_error=False)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\ops\gen_math_ops.py:3224 equal
name=name)
D:\anaconda\install\envs\tf2.2gpunew\lib\site-packages\tensorflow\python\framework\op_def_library.py:479 _apply_op_helper
repr(values), type(values).__name__, err))
TypeError: Expected float32 passed to parameter 'y' of op 'Equal', got 'accuracy' of type 'str' instead. Error: Expected float32, got 'accuracy' of type 'str' instead.
I think the reason that the error happened is our tensorflows do not match. I will be grateful if you tell me your tensorflow version. Or there exsits other problems I have not realized, Can you give me some advices?
Thank you very much!