lib/layer/average_pool_test.py
import tensorflow as tf
from .average_pool import AveragePool
class AveragePoolTest(tf.test.TestCase):
def test_init(self):
layer = AveragePool()
self.assertEqual(layer.name, 'averagepool_1')
def test_call(self):
layer = AveragePool(name='call')
input_1 = [[1, 2], [3, 4], [5, 6], [7, 8]]
input_2 = [[9, 10], [11, 12], [13, 14], [15, 16]]
input_1 = tf.constant(input_1, dtype=tf.float32)
input_2 = tf.constant(input_2, dtype=tf.float32)
inputs = [input_1, input_2]
outputs = layer(inputs)
expected = [[4, 5], [12, 13]]
with self.test_session():
# Average pooling converts lists to tensors.
self.assertAllEqual(outputs.eval(), expected)
def test_call_with_tensor(self):
layer = AveragePool(name='call_with_tensor')
inputs = tf.constant([[[
[1, 2],
[3, 4],
], [
[5, 6],
[7, 8],
]], [[
[1, 2],
[3, 4],
], [
[5, 6],
[7, 8],
]]])
outputs = layer(inputs)
expected = [[4, 5], [4, 5]]
with self.test_session():
self.assertAllEqual(outputs.eval(), expected)