def testMultiplyInverse(self):
with ops.Graph().as_default(), self.test_session() as sess:
random_seed.set_random_seed(200)
params = random_ops.random_normal((3, 3, 8, 2))
inputs = random_ops.random_normal((32, 5, 5, 8))
outputs = random_ops.random_normal((32, 5, 5, 16))
layer_collection = lc.LayerCollection()
block = fb.DepthwiseConvKFCBasicFB(layer_collection,
params=params,
strides=[1, 1, 1, 1],
padding='SAME')
block.register_additional_tower(inputs, outputs)
grads = outputs**2
block.instantiate_factors(([grads], ), 0.5)
block._input_factor.instantiate_cov_variables()
block._output_factor.instantiate_cov_variables()
block.register_inverse()
block._input_factor.instantiate_inv_variables()
block._output_factor.instantiate_inv_variables()
# Ensure inverse update op doesn't crash.
sess.run(tf_variables.global_variables_initializer())
sess.run([
factor.make_inverse_update_ops()
for factor in layer_collection.get_factors()
])
# Ensure inverse-vector multiply doesn't crash.
output = block.multiply_inverse(params)
sess.run(output)
# Ensure same shape.
self.assertAllEqual(output.shape, params.shape)
def testInstantiateFactors(self):
with ops.Graph().as_default():
random_seed.set_random_seed(200)
params = random_ops.random_normal((3, 3, 8, 2))
inputs = random_ops.random_normal((32, 5, 5, 8))
outputs = random_ops.random_normal((32, 5, 5, 16))
layer_collection = lc.LayerCollection()
block = fb.DepthwiseConvKFCBasicFB(layer_collection,
params=params,
strides=[1, 1, 1, 1],
padding='SAME')
block.register_additional_tower(inputs, outputs)
grads = outputs**2
block.instantiate_factors(([grads], ), 0.5)