class MaskGeneratorTests(unittest.TestCase):
def __init__(self, *args, **kwargs):
unittest.TestCase.__init__(self, *args, **kwargs)
self.input_size = 10
self.hidden_sizes = []
def setUp(self):
self.nb_layers = len(self.hidden_sizes) + 2
self.mask_generator = MaskGenerator(self.input_size, self.hidden_sizes, 0)
def tearDown(self):
pass
def test_mask(self):
for i in range(self.nb_layers - 1):
layerToOutput = self.mask_generator.get_mask_layer_UPDATE(i).eval()
layerConnectivity = self.mask_generator.layers_connectivity[i].get_value()
nextLayerConnectivity = self.mask_generator.layers_connectivity[i + 1].get_value()
for i, output in enumerate(layerToOutput.T):
conn = (layerConnectivity <= nextLayerConnectivity[i])
assert_equal(output[conn].sum(), conn.sum())
assert_equal(output[np.logical_not(conn)].sum(), 0)
def test_direct_output_mask(self):
# layer0ToOutput = self.mask_generator.get_direct_output_mask_layer_UPDATE(0).eval()
# VALID_layer0ToOutput = np.triu(np.ones((self.input_size, self.input_size)), 1)
# assert_array_equal(layer0ToOutput, VALID_layer0ToOutput)
for i in range(self.nb_layers):
layerToOutput = self.mask_generator.get_direct_output_mask_layer_UPDATE(i).eval()
layerConnectivity = self.mask_generator.layers_connectivity[i].get_value()
for output, conn in zip(layerToOutput, layerConnectivity):
assert_equal(output[:conn].sum(), 0)
assert_equal(output[conn:].sum(), self.input_size - conn)
assert_raises(IndexError, self.mask_generator.get_direct_output_mask_layer_UPDATE, self.nb_layers)
def test_direct_input_mask(self):
for i in range(self.nb_layers):
layerToOutput = self.mask_generator.get_direct_input_mask_layer_UPDATE(i).eval()
layerConnectivity = self.mask_generator.layers_connectivity[i].get_value()
for output, conn in zip(layerToOutput.T, layerConnectivity):
assert_equal(output[:conn].sum(), conn)
assert_equal(output[conn:].sum(), 0)
assert_raises(IndexError, self.mask_generator.get_direct_input_mask_layer_UPDATE, self.nb_layers)
def test_shuffle_ordering(self):
initial_ordering = self.mask_generator.ordering.get_value()
initial_input_connectivity = self.mask_generator.layers_connectivity[0].get_value()
assert_array_equal(initial_ordering, np.arange(self.input_size))
assert_array_equal(initial_ordering + 1, initial_input_connectivity)
# Shuffling the mask
self.mask_generator.shuffle_ordering()
shuffled_ordering = self.mask_generator.ordering.get_value()
shuffled_input_connectivity = self.mask_generator.layers_connectivity[0].get_value()
assert_equal(initial_ordering.sum(), shuffled_ordering.sum()) # Making sure that all the number are there
assert_array_equal(set(initial_ordering), set(shuffled_ordering)) # Making sure that all the number are there
assert_false(np.array_equal(initial_ordering, shuffled_ordering)) # Making sure that there was an actual shuffle
assert_array_equal(shuffled_ordering + 1, shuffled_input_connectivity)
# Making sure that the mask is not only shuffled once
self.mask_generator.shuffle_ordering()
last_ordering = self.mask_generator.ordering.get_value()
last_input_connectivity = self.mask_generator.layers_connectivity[0].get_value()
assert_equal(shuffled_ordering.sum(), last_ordering.sum()) # Making sure that all the number are there
assert_array_equal(set(shuffled_ordering), set(last_ordering)) # Making sure that all the number are there
assert_false(np.array_equal(shuffled_ordering, last_ordering)) # Making sure that there was an actual shuffle
assert_array_equal(last_ordering + 1, last_input_connectivity)
def _reset_test_get_masks(self):
ordering = self.mask_generator.ordering.get_value()
masks = [self.mask_generator.get_mask_layer_UPDATE(i).eval() for i in range(self.nb_layers - 1)]
masks_direct_input = [self.mask_generator.get_direct_input_mask_layer_UPDATE(i).eval() for i in range(self.nb_layers)]
masks_direct_output = [self.mask_generator.get_direct_output_mask_layer_UPDATE(i).eval() for i in range(self.nb_layers)]
return ordering, masks, masks_direct_input, masks_direct_output
def test_reset(self):
ordering, masks, masks_direct_input, masks_direct_output = self._reset_test_get_masks()
# shuffle gen a couple iteration of mask
for i in range(3):
self.mask_generator.shuffle_ordering()
self.mask_generator.sample_connectivity()
new_ordering, new_masks, new_masks_direct_input, new_masks_direct_output = self._reset_test_get_masks()
assert_false(np.array_equal(ordering, new_ordering))
for m, nm in zip(masks, new_masks):
assert_false(np.array_equal(m, nm))
for m, nm in zip(masks_direct_input, new_masks_direct_input):
assert_false(np.array_equal(m, nm))
for m, nm in zip(masks_direct_output, new_masks_direct_output):
assert_false(np.array_equal(m, nm))
self.mask_generator.reset()
r_ordering, r_masks, r_masks_direct_input, r_masks_direct_output = self._reset_test_get_masks()
assert_array_equal(ordering, r_ordering)
for i in range(len(masks)):
assert_array_equal(masks[i], r_masks[i])
for i in range(len(masks_direct_input)):
assert_array_equal(masks_direct_input[i], r_masks_direct_input[i])
for i in range(len(masks_direct_output)):
assert_array_equal(masks_direct_output[i], r_masks_direct_output[i])
# shuffle gen a couple iteration of mask
for i in range(3):
self.mask_generator.shuffle_ordering()
self.mask_generator.sample_connectivity()
r_new_ordering, r_new_masks, r_new_masks_direct_input, r_new_masks_direct_output = self._reset_test_get_masks()
assert_array_equal(new_ordering, r_new_ordering)
for i in range(len(new_masks)):
assert_array_equal(new_masks[i], r_new_masks[i])
for i in range(len(new_masks_direct_input)):
assert_array_equal(new_masks_direct_input[i], r_new_masks_direct_input[i])
for i in range(len(new_masks_direct_output)):
assert_array_equal(new_masks_direct_output[i], r_new_masks_direct_output[i])
class MaskGeneratorTests(unittest.TestCase):
def __init__(self, *args, **kwargs):
unittest.TestCase.__init__(self, *args, **kwargs)
self.input_size = 10
self.hidden_sizes = []
def setUp(self):
self.nb_layers = len(self.hidden_sizes) + 2
self.mask_generator = MaskGenerator(self.input_size, self.hidden_sizes,
0)
def tearDown(self):
pass
def test_mask(self):
for i in range(self.nb_layers - 1):
layerToOutput = self.mask_generator.get_mask_layer_UPDATE(i).eval()
layerConnectivity = self.mask_generator.layers_connectivity[
i].get_value()
nextLayerConnectivity = self.mask_generator.layers_connectivity[
i + 1].get_value()
for i, output in enumerate(layerToOutput.T):
conn = (layerConnectivity <= nextLayerConnectivity[i])
assert_equal(output[conn].sum(), conn.sum())
assert_equal(output[np.logical_not(conn)].sum(), 0)
def test_direct_output_mask(self):
# layer0ToOutput = self.mask_generator.get_direct_output_mask_layer_UPDATE(0).eval()
# VALID_layer0ToOutput = np.triu(np.ones((self.input_size, self.input_size)), 1)
# assert_array_equal(layer0ToOutput, VALID_layer0ToOutput)
for i in range(self.nb_layers):
layerToOutput = self.mask_generator.get_direct_output_mask_layer_UPDATE(
i).eval()
layerConnectivity = self.mask_generator.layers_connectivity[
i].get_value()
for output, conn in zip(layerToOutput, layerConnectivity):
assert_equal(output[:conn].sum(), 0)
assert_equal(output[conn:].sum(), self.input_size - conn)
assert_raises(IndexError,
self.mask_generator.get_direct_output_mask_layer_UPDATE,
self.nb_layers)
def test_direct_input_mask(self):
for i in range(self.nb_layers):
layerToOutput = self.mask_generator.get_direct_input_mask_layer_UPDATE(
i).eval()
layerConnectivity = self.mask_generator.layers_connectivity[
i].get_value()
for output, conn in zip(layerToOutput.T, layerConnectivity):
assert_equal(output[:conn].sum(), conn)
assert_equal(output[conn:].sum(), 0)
assert_raises(IndexError,
self.mask_generator.get_direct_input_mask_layer_UPDATE,
self.nb_layers)
def test_shuffle_ordering(self):
initial_ordering = self.mask_generator.ordering.get_value()
initial_input_connectivity = self.mask_generator.layers_connectivity[
0].get_value()
assert_array_equal(initial_ordering, np.arange(self.input_size))
assert_array_equal(initial_ordering + 1, initial_input_connectivity)
# Shuffling the mask
self.mask_generator.shuffle_ordering()
shuffled_ordering = self.mask_generator.ordering.get_value()
shuffled_input_connectivity = self.mask_generator.layers_connectivity[
0].get_value()
assert_equal(initial_ordering.sum(), shuffled_ordering.sum()
) # Making sure that all the number are there
assert_array_equal(set(initial_ordering), set(
shuffled_ordering)) # Making sure that all the number are there
assert_false(np.array_equal(
initial_ordering,
shuffled_ordering)) # Making sure that there was an actual shuffle
assert_array_equal(shuffled_ordering + 1, shuffled_input_connectivity)
# Making sure that the mask is not only shuffled once
self.mask_generator.shuffle_ordering()
last_ordering = self.mask_generator.ordering.get_value()
last_input_connectivity = self.mask_generator.layers_connectivity[
0].get_value()
assert_equal(
shuffled_ordering.sum(),
last_ordering.sum()) # Making sure that all the number are there
assert_array_equal(
set(shuffled_ordering),
set(last_ordering)) # Making sure that all the number are there
assert_false(np.array_equal(
shuffled_ordering,
last_ordering)) # Making sure that there was an actual shuffle
assert_array_equal(last_ordering + 1, last_input_connectivity)
def _reset_test_get_masks(self):
ordering = self.mask_generator.ordering.get_value()
masks = [
self.mask_generator.get_mask_layer_UPDATE(i).eval()
for i in range(self.nb_layers - 1)
]
masks_direct_input = [
self.mask_generator.get_direct_input_mask_layer_UPDATE(i).eval()
for i in range(self.nb_layers)
]
masks_direct_output = [
self.mask_generator.get_direct_output_mask_layer_UPDATE(i).eval()
for i in range(self.nb_layers)
]
return ordering, masks, masks_direct_input, masks_direct_output
def test_reset(self):
ordering, masks, masks_direct_input, masks_direct_output = self._reset_test_get_masks(
)
# shuffle gen a couple iteration of mask
for i in range(3):
self.mask_generator.shuffle_ordering()
self.mask_generator.sample_connectivity()
new_ordering, new_masks, new_masks_direct_input, new_masks_direct_output = self._reset_test_get_masks(
)
assert_false(np.array_equal(ordering, new_ordering))
for m, nm in zip(masks, new_masks):
assert_false(np.array_equal(m, nm))
for m, nm in zip(masks_direct_input, new_masks_direct_input):
assert_false(np.array_equal(m, nm))
for m, nm in zip(masks_direct_output, new_masks_direct_output):
assert_false(np.array_equal(m, nm))
self.mask_generator.reset()
r_ordering, r_masks, r_masks_direct_input, r_masks_direct_output = self._reset_test_get_masks(
)
assert_array_equal(ordering, r_ordering)
for i in range(len(masks)):
assert_array_equal(masks[i], r_masks[i])
for i in range(len(masks_direct_input)):
assert_array_equal(masks_direct_input[i], r_masks_direct_input[i])
for i in range(len(masks_direct_output)):
assert_array_equal(masks_direct_output[i],
r_masks_direct_output[i])
# shuffle gen a couple iteration of mask
for i in range(3):
self.mask_generator.shuffle_ordering()
self.mask_generator.sample_connectivity()
r_new_ordering, r_new_masks, r_new_masks_direct_input, r_new_masks_direct_output = self._reset_test_get_masks(
)
assert_array_equal(new_ordering, r_new_ordering)
for i in range(len(new_masks)):
assert_array_equal(new_masks[i], r_new_masks[i])
for i in range(len(new_masks_direct_input)):
assert_array_equal(new_masks_direct_input[i],
r_new_masks_direct_input[i])
for i in range(len(new_masks_direct_output)):
assert_array_equal(new_masks_direct_output[i],
r_new_masks_direct_output[i])
def setUp(self):
self.nb_layers = len(self.hidden_sizes) + 2
self.mask_generator = MaskGenerator(self.input_size, self.hidden_sizes, 0)
def setUp(self):
self.nb_layers = len(self.hidden_sizes) + 2
self.mask_generator = MaskGenerator(self.input_size, self.hidden_sizes,
0)
