Just as the title says. This code only works Using:
x = Flatten()(x)
Between the convolutional layer and the dense layer.
import numpy as np
import keras
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, Flatten, Input
from keras.layers import Conv2D, MaxPooling2D
from keras.optimizers import SGD
# Generate dummy data
x_train = np.random.random((100, 100, 100, 3))
y_train = keras.utils.to_categorical(np.random.randint(10, size=(100, 1)), num_classes=10)
#Build Model
input_layer = Input(shape=(100, 100, 3))
x = Conv2D(32, (3, 3), activation='relu')(input_layer)
x = Dense(256, activation='relu')(x)
x = Dense(10, activation='softmax')(x)
model = Model(inputs=[input_layer],outputs=[x])
#compile network
sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='categorical_crossentropy', optimizer=sgd)
#train network
model.fit(x_train, y_train, batch_size=32, epochs=10)
Otherwise, I receive this error:
Traceback (most recent call last):
File "/home/michael/practice_example.py", line 44, in <module>
model.fit(x_train, y_train, batch_size=32, epochs=10)
File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 1435, in fit
batch_size=batch_size)
File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 1315, in _standardize_user_data
exception_prefix='target')
File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 127, in _standardize_input_data
str(array.shape))
ValueError: Error when checking target: expected dense_2 to have 4 dimensions, but got array with shape (100, 10)