TOC
fit x shape and y shape
# OS:Windows 10
# python version: 3.7.4
# numpy version:1.19.4
# tensorflow version:1.14.0
# keras version:2.1.5
Error
ValueError: Error when checking target: expected dense_2 to have 4 dimensions, but got array with shape (145, 11)
def simpleCNN(input_shape):
model = Sequential()
model.add(Conv2D(filters=256,
kernel_size = (3*3),
activation="relu",
input_shape=input_shape,
padding="same" ) );# output: 13*13*384
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(3, 3),
strides=(2,2),
padding="same"));
model.add(Dense(512, activation='relu', ))
model.add(Dense(11, activation='softmax'))
# model.add(layers.Dense(11, activation='sigmoid'))
model.compile(optimizer='rmsprop', loss='categorical_crossentropy',
metrics=['accuracy'])
return model;
model summary:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 36, 14, 256) 20992
_________________________________________________________________
batch_normalization_1 (Batch (None, 36, 14, 256) 1024
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 18, 7, 256) 0
_________________________________________________________________
dense_1 (Dense) (None, 18, 7, 512) 131584
_________________________________________________________________
dense_2 (Dense) (None, 18, 7, 11) 5643
=================================================================
Total params: 159,243
Trainable params: 158,731
Non-trainable params: 512
_________________________________________________________________
train_images.shape: (145, 36, 14, 1)
train_labels.shape (145, 11)
The problem is without Flatten()
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