训练TensorFlow以查找数字集之间的模式

Question

我正在尝试训练一个AI，鉴于一组90个可能的数字，匹配了5个生成的数字（没有随机生成的重复和数字）。 这是代码：

from numpy import test
import tensorflow as tf
import click
import pandas as pd
from sklearn.model_selection import train_test_split
from itertools import repeat
insert = [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90] for i in repeat(None, 33785)]
results = pd.read_csv("datini.csv")
del results['DATA']
del results['LUOGO']
results.drop(columns=results.columns[0], axis=1, inplace=True)
insert_train, insert_test, results_train, results_test = train_test_split(insert, results, test_size=0.2)

model = tf.keras.models.Sequential()

model.add(tf.keras.layers.Dense(256, input_shape=insert_train.shape))
model.add(tf.keras.layers.Dense(256))
model.add(tf.keras.layers.Dense(5))

model.compile(optimizer='adam', loss='CategoricalCrossentropy', metrics=['accuracy'])

model.fit(insert_train, results_train, epochs=200)
model.evaluate(insert_test, results_test)

它给出了此错误，我不知道如何在不创建另一个数据集的情况下插入“固定数据”。

attributeError：'list'对象没有属性'形状'

Answer 1

错误是哪一行？

model.add(tf.keras.layers.Dense(256, input_shape=insert_train.shape))

如果在这里，则insert_train.shape是列表。将其变成一个数阵列，以便您可以使用。

insert_train = np.array(insert_train)