Python 如何告诉tensorflow顺序不';没关系

Python 如何告诉tensorflow顺序不';没关系,python,tensorflow,machine-learning,artificial-intelligence,Python,Tensorflow,Machine Learning,Artificial Intelligence,我有5个数组,每个数组包含10个值,当前我传递给tensorflow。但是,在训练之后,当我使用model.predict时,只要改变数组的顺序,我就可以得到完全不同的值 例如[1,2],[3,4]将给出与[3,4],[1,2]不同的结果。顺序不重要,有没有办法告诉tensorflow 这是我目前的代码: field_names = ["elo", "map", "c1", "c2", "c3",

我有5个数组,每个数组包含10个值,当前我传递给tensorflow。但是,在训练之后,当我使用model.predict时,只要改变数组的顺序,我就可以得到完全不同的值

例如[1,2],[3,4]将给出与[3,4],[1,2]不同的结果。顺序不重要,有没有办法告诉tensorflow

这是我目前的代码:

field_names = ["elo", "map", "c1", "c2", "c3", "c4", "c5", "e1", "e2", "e3", "e4", "e5", "result"]
df_train = pd.read_csv('input/match_results.csv', names=field_names, skiprows=1, usecols=range(2, 13))
for count in range(1, 6):
    str_count = str(count)
    def converter(x):
        if isinstance(x, str):
            return pd.Series(champ_features_dict[x])
        else:
            return x

    df_train["c" + str_count] = df_train["c" + str_count].apply(converter)

    df_train['result'] = pd.Categorical(df_train['result'])
    df_train['result'] = df_train.result.cat.codes
df_train = df_train.drop(columns=['e1','e2','e3','e4','e5'], axis=1)
target = df_train.pop('result')
targets = np.array(list(x for x in target.values))
dataset = tf.data.Dataset.from_tensor_slices((df_train.values, targets))
train_data = dataset.shuffle(len(df_train)).batch(batch_size)

for relative_step, (batch_x, batch_y) in enumerate(train_data.take(training_steps), 1):
    run_optimization(batch_x, batch_y)

试图重现您的问题时,我们遇到错误,
FileNotFoundError:[Errno 2]File input/match\u results.csv不存在:“input/match\u results.csv”
。您能否提供完整的可复制代码,以便我们可以帮助您。谢谢试图重现您的问题时,我们遇到错误,
FileNotFoundError:[Errno 2]File input/match\u results.csv不存在:“input/match\u results.csv”
。您能否提供完整的可复制代码,以便我们可以帮助您。谢谢