CODEWITHSUNDEEP
pythontensorflow
hal
hal

Reputation: 841

How to interpret output shape printed in the summary of tensorflow model?

I have simple multi-layer perceptron for MNIST data classification problem.

model = tf.keras.Sequential([
  tf.keras.layers.Flatten(),
  tf.keras.layers.Dense(128, activation='relu'),
  tf.keras.layers.Dense(10, activation='softmax')
])

When printing summary i receive following output:

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
flatten_8 (Flatten)          (None, 784)               0         
_________________________________________________________________
dense_16 (Dense)             (None, 128)               100480    
_________________________________________________________________
dense_17 (Dense)             (None, 10)                1290      
=================================================================
Total params: 101,770
Trainable params: 101,770
Non-trainable params: 0
_________________________________________________________________

How do I interpret output shape printed in the summary? Why is there None therm in the output shape tuple? Why is it not just (784) in the first layer?

Upvotes: 0

Views: 221

Answers (1)

QWERTYL
QWERTYL

Reputation: 1373

The "None" value refers to the number of input samples (the batch size). To allow you to train on different sized training sets, this value is None. If it were a number, let's say 50 for example, that means you can only train on exactly 50 samples which is usually not very useful (but does occasionally have applications).

Upvotes: 1

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