【发布时间】:2020-01-01 00:41:07
【问题描述】:
我有数组重塑和大小问题
我没有尝试任何事情,因为我还是新手,我不想搞砸与问题无关的事情
import tensorflow as tf
import numpy as np
mnist = tf.keras.datasets.mnist
(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train = tf.keras.utils.normalize(x_train, axis=1) # scales data between 0 and 1
x_test = tf.keras.utils.normalize(x_test, axis=1)
model = tf.keras.models.Sequential()
model.add(tf.keras.layers.Flatten(input_shape=(32,)))
model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
model.add(tf.keras.layers.Dense(10, activation=tf.nn.softmax))
x_train = np.reshape(x_train, (x_train.shape[0], 1, x_train.shape[1]))
x_test = np.reshape(x_test, (x_test.shape[0], 1, x_test.shape[1]))
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
model.fit(x_train, y_train, epochs=3)
val_loss, val_acc = model.evaluate(x_test, y_test)
print(val_loss)
print(val_acc)
File "t1.py", line 17, in <module>
x_train = np.reshape(x_train, (x_train.shape[0], 1, x_train.shape[1]))
File "<__array_function__ internals>", line 6, in reshape
File "H:\Program Files\Python36\lib\site-packages\numpy\core\fromnumeric.py", line 301, in reshape
return _wrapfunc(a, 'reshape', newshape, order=order)
File "H:\Program Files\Python36\lib\site-packages\numpy\core\fromnumeric.py", line 61, in _wrapfunc
return bound(*args, **kwds)
ValueError: cannot reshape array of size 47040000 into shape (60000,1,28)```
【问题讨论】:
标签: python python-3.x tensorflow deep-learning artificial-intelligence