def test_conv2d(self):
tf.set_random_seed(42)
batch_size = 32
input_shape = (10, 10)
n_filters = 7
filter_shape = (5, 5)
vals = np.random.randn(batch_size, input_shape[0], input_shape[1], 1)
with self.test_session() as sess:
tensor_in = tf.placeholder(tf.float32, [batch_size, input_shape[0],
input_shape[1], 1])
res = ops.conv2d(tensor_in, n_filters, filter_shape)
sess.run(tf.initialize_all_variables())
conv = sess.run(res, feed_dict={tensor_in.name: vals})
self.assertEqual(conv.shape, (batch_size, input_shape[0],
input_shape[1], n_filters))
def test_conv2d(self):
tf.set_random_seed(42)
batch_size = 32
input_shape = (10, 10)
n_filters = 7
filter_shape = (5, 5)
vals = np.random.randn(batch_size, input_shape[0], input_shape[1], 1)
with self.test_session() as sess:
tensor_in = tf.placeholder(
tf.float32, [batch_size, input_shape[0], input_shape[1], 1])
res = ops.conv2d(tensor_in, n_filters, filter_shape)
sess.run(tf.initialize_all_variables())
conv = sess.run(res, feed_dict={tensor_in.name: vals})
self.assertEqual(
conv.shape,
(batch_size, input_shape[0], input_shape[1], n_filters))