08. Transposed Convolution Quiz
Transposed Convolution Quiz
Transposed convolutions are used to upsample the input and are a core part of the FCN architecture.
In TensorFlow, the API
tf.layers.conv2d_transpose
is used to create a transposed convolutional layer. Using this
documentation
, use
tf.layers.conv2d_transpose
to apply 2x upsampling in the following quiz.
Start Quiz:
import oldtensorflow as tf
import numpy as np
def upsample(x):
"""
Apply a two times upsample on x and return the result.
:x: 4-Rank Tensor
:return: TF Operation
"""
# TODO: Use `tf.layers.conv2d_transpose`
return None
x = tf.constant(np.random.randn(1, 4, 4, 3), dtype=tf.float32)
conv = upsample(x)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
result = sess.run(conv)
print('Input Shape: {}'.format(x.get_shape()))
print('Output Shape: {}'.format(result.shape))
import oldtensorflow as tf
import numpy as np
def upsample(x):
"""
Apply a two times upsample on x and return the result.
:x: 4-Rank Tensor
:return: TF Operation
"""
# TODO: Use `tf.layers.conv2d_transpose`
return tf.layers.conv2d_transpose(x, 3, (2, 2), (2, 2))
x = tf.constant(np.random.randn(1, 4, 4, 3), dtype=tf.float32)
conv = upsample(x)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
result = sess.run(conv)
print('Input Shape: {}'.format(x.get_shape()))
print('Output Shape: {}'.format(result.shape))