[英]ValueError: Input 0 of layer sequential_2 is incompatible with the layer
I have the following code:我有以下代码:
import tensorflow as tf
import keras
from keras.datasets import cifar10
(x_train, y_train), (x_test, y_test) = cifar10.load_data()
import numpy as np
x_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], x_train.shape[2], 3))
print(x_train.shape)
x_test = np.reshape(x_test, (x_test.shape[0], x_test.shape[1], x_test.shape[2], 3))
print(x_test.shape)
x_train = x_train.astype('float32')/255.0
x_test = x_test.astype('float32')/255.0
from keras.utils import to_categorical
y_train = to_categorical(y_train, num_classes = 10)
y_test = to_categorical(y_test, num_classes = 10)
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Flatten
model = Sequential()
#Defining layers of the model
model.add(Dense(2056, activation='relu', input_shape = (3072,)))
model.add(Dense(10, activation='softmax'))
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
model.summary()
history = model.fit(x_train, y_train, batch_size=1000, epochs=50)
And I am facing the following error:我面临以下错误:
ValueError: Input 0 of layer sequential_2 is incompatible with the layer: expected axis -1 of input shape to have value 3072 but received input with shape (1000, 32, 32, 3) ValueError:层序 2 的输入 0 与层不兼容:输入形状的预期轴 -1 具有值 3072,但接收到形状为 (1000, 32, 32, 3) 的输入
I want to keep the input_shape as 3072 only.我只想将 input_shape 保持为 3072。 How can I reshape my y_test to solve this?如何重塑我的 y_test 来解决这个问题?
You should Flatten
your input data before passing them to Dense
layer.在将输入数据传递给Dense
层之前,您应该先Flatten
输入数据。
model = Sequential()
#Defining layers of the model
model.add(Flatten(input_shape=(32,32,3)) # 32*32*3 = 3072
model.add(Dense(2056, activation='relu'))
model.add(Dense(10, activation='softmax'))
This should fix the problem.这应该可以解决问题。
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