我有一個函式，它接受一個張量并使用一個看起來像這樣的方程從這個張量的形狀計算 num_classes 變數：
num_classes = tensor.shape[4] - 5.
現在，如果我將此函式與隨機輸入獨立呼叫，它作業得很好，但由于此函式是邏輯的一部分，該邏輯在每個 epoch 之后在驗證資料上運行模型時計算一些指標，它失敗并輸出此錯誤：
File "train.py", line 142, in <module>
main()
File "train.py", line 120, in main
train(input_size,
File "train.py", line 81, in train
face_detector.fit(train_data_generator ,
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/keras/engine/training.py", line 1215, in fit
val_logs = self.evaluate(
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/keras/engine/training.py", line 1501, in evaluate
tmp_logs = self.test_function(iterator)
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 885, in __call__
result = self._call(*args, **kwds)
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 933, in _call
self._initialize(args, kwds, add_initializers_to=initializers)
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 759, in _initialize
self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3066, in _get_concrete_function_internal_garbage_collected
graph_function, _ = self._maybe_define_function(args, kwargs)
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3463, in _maybe_define_function
graph_function = self._create_graph_function(args, kwargs)
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3298, in _create_graph_function
func_graph_module.func_graph_from_py_func(
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 1007, in func_graph_from_py_func
func_outputs = python_func(*func_args, **func_kwargs)
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 668, in wrapped_fn
out = weak_wrapped_fn().__wrapped__(*args, **kwds)
File "/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 994, in wrapper
raise e.ag_error_metadata.to_exception(e)
TypeError: in user code
/home/yogeesh/yogeesh/tf2/lib/python3.8/site-packages/keras/engine/training.py:1330 test_function *
return step_function(self, iterator)
/home/yogeesh/yogeesh/object_detection/Yolov3_tf2/metrics/mAP.py:102 update_state *
box_objects = tf_postprocessing.post_process(predictions ,
/home/yogeesh/yogeesh/object_detection/Yolov3_tf2/postprocessing/tf_postprocessing.py:137 post_process *
all_gt = modify_locs(ground_truth , scale_anchors , gt = True)
/home/yogeesh/yogeesh/object_detection/Yolov3_tf2/postprocessing/tf_postprocessing.py:35 modify_locs *
modified_loc = pp_utils.modify_locs_util(localizations , this_scale_anchor , ground_truth = gt)
/home/yogeesh/yogeesh/object_detection/Yolov3_tf2/postprocessing/tf_utils.py:20 modify_locs_util *
num_classes = localizations.shape[4] - 5
TypeError: unsupported operand type(s) for -: 'NoneType' and 'int'
2021-10-21 18:33:00.783103: W tensorflow/core/kernels/data/generator_dataset_op.cc:107] Error occurred when finalizing GeneratorDataset iterator: Failed precondition: Python interpreter state is not initialized. The process may be terminated.
[[{{node PyFunc}}]]
這僅在訓練時發生，使用 tf.keras.model.fit 函式，它在“評估”呼叫中運行覆寫的 test_Step 函式。
這是我收到錯誤的函式。
def modify_locs_util(localizations , anchors , img_shape = [416, 416] , ground_truth = False):
# localizations.shape : [batch_size , grid_size , grid_size , 3 , 7] (for this dataset)
# where grid_size can be 13,26,52 (Yolov3 model).
locs_shape = tf.shape(localizations)
grid_shape = locs_shape[1:3]
num_anchors = locs_shape[3]
num_classes = locs_shape[4] - 5
strides = [img_shape[0] // grid_shape[0], img_shape[1] // grid_shape[1]]
cell_grid = comman_utils.gen_cell_grid(grid_shape[0] , grid_shape[1] , num_anchors)
奇怪的是，如果我列印本地化的形狀，結果是這樣的：
(None, 13, 13, 3, 7)
(None, 26, 26, 3, 7)
(None, 52, 52, 3, 7)
(None, None, None, None, None)
as you can see, first 3 times the shape is fine , but i dont why is it calling again (it should call this fucntion only 3 times) and now it is referring the shape as all None's. Its almost like its doing a architechure check first to figure out shapes but even then static dims shouldnt be None.
uj5u.com熱心網友回復：
也許嘗試以下代碼：
num_classes = tf.shape(tensor)[4] - 5.
這將在呼叫 fit(*) 方法時進行評估。
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