import tensorflow as tf
input_shape = (4, 28, 28, 3)
inputs = tf.random.normal(input_shape)
inputs.shape
TensorShape([4, 28, 28, 3])
output = tf.keras.layers.Conv2D(
2,
3,
activation='relu',
input_shape=input_shape[1:]
)(inputs)
print(output.shape)
(4, 26, 26, 2)
output = tf.keras.layers.Conv2D(
2,
3,
activation='relu',
dilation_rate=2,
input_shape=input_shape[1:]
)(inputs)
print(output.shape)
(4, 24, 24, 2)
output = tf.keras.layers.Conv2D(
2,
3,
activation='relu',
padding="same",
input_shape=input_shape[1:]
)(inputs)
print(output.shape)
(4, 28, 28, 2)
input_shape = (4, 7, 28, 28, 3)
inputs = tf.random.normal(input_shape)
output = tf.keras.layers.Conv2D(
2, 3, activation='relu', input_shape=input_shape[2:])(inputs)
print(output.shape)
(4, 7, 26, 26, 2)