在TensorFlow中，我创建了一个以哈希值作为输入的常规网络。作为示例，我使用了Python内置的hash()函数（是的，每次会话都会更改盐值，但这只是一个示例）。代码如下：

from time import timest = time()import tensorflow as tfprint(time() - st)import numpy as npimport chessimport atexitfrom numpy import shapedata = open("data.data", "r").readlines()[:10000]targets = open("targets.data", "r").readlines()[:10000]boards_data = []new_targets = []for i in data:    boards_data.append(hash(i))for i in targets:    new_targets.append(float(i))print(len(new_targets))print(len(boards_data))print(np.array(new_targets))print(np.array(boards_data))def create_model():   model = tf.keras.models.Sequential()   model.add(tf.keras.layers.Reshape((1,1,1)))   model.add(tf.keras.layers.Dense(1000, activation="tanh"))   model.add(tf.keras.layers.Flatten())   model.add(tf.keras.layers.Dense(1, activation='tanh'))   model.compile(loss="mse", optimizer="adam", metrics=['accuracy'])   return modelmodel = create_model()model.fit(np.array(boards_data), np.array(new_targets), epochs=10)model.predict(np.array(hash("8/6P1/5k1K/6r1/8/8/8/8 b - - 0 83")))

错误发生在预测部分。我查看了如何修复TensorFlow中的”IndexError: list index out of range”的conv2d示例，但这不是我的情况…

以下是错误跟踪信息：

Traceback (most recent call last):  File "/Volumes/POOPOO USB/lichess-bot/engines/engine2/nn_evaluation/nn_evaluation2.py", line 36, in <module>    model.predict(np.array(hash("8/6P1/5k1K/6r1/8/8/8/8 b - - 0 83")))  File "/Users/ofek/Library/Python/3.8/lib/python/site-packages/tensorflow/python/keras/engine/training.py", line 130, in _method_wrapper    return method(self, *args, **kwargs)  File "/Users/ofek/Library/Python/3.8/lib/python/site-packages/tensorflow/python/keras/engine/training.py", line 1569, in predict    data_handler = data_adapter.DataHandler(  File "/Users/ofek/Library/Python/3.8/lib/python/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 1105, in __init__    self._adapter = adapter_cls(  File "/Users/ofek/Library/Python/3.8/lib/python/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 275, in __init__    num_samples = set(int(i.shape[0]) for i in nest.flatten(inputs))  File "/Users/ofek/Library/Python/3.8/lib/python/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 275, in <genexpr>    num_samples = set(int(i.shape[0]) for i in nest.flatten(inputs))  File "/Users/ofek/Library/Python/3.8/lib/python/site-packages/tensorflow/python/framework/tensor_shape.py", line 887, in __getitem__    return self._dims[key].valueIndexError: list index out of range```

回答：

问题在于您从哈希值创建了一个0维的numpy字符串。预测只能在至少有一个维度的数组上运行。您可以检查您的哈希值是0维的：

print(np.array(hash("8/6P1/5k1K/6r1/8/8/8/8 b - - 0 83")).shape)# outputs: ()

相比之下，如果您将哈希值放入一个列表中：

print(np.array([hash("8/6P1/5k1K/6r1/8/8/8/8 b - - 0 83")]).shape)# outputs: (1,)

使用第二个np.array，预测可以无错误运行。