def test_get_hidden_node_location_text(self):
num_channels = 128
output_activation_map_shape = (498, 1)
flattened_indices = np.arange(
num_channels * output_activation_map_shape[0]).reshape(
num_channels, output_activation_map_shape[0],
output_activation_map_shape[1])
true_row = np.random.randint(low=0, high=output_activation_map_shape[0])
true_channel = np.random.randint(low=0, high=num_channels)
true_column = 0
(predicted_channel, predicted_row,
predicted_column) = masking._get_hidden_node_location(
flattened_index=flattened_indices[true_channel][true_row][true_column],
num_rows=output_activation_map_shape[0],
num_columns=output_activation_map_shape[1])
self.assertEqual(true_channel, predicted_channel)
self.assertEqual(true_row, predicted_row)
self.assertEqual(true_column, predicted_column)
def test_get_hidden_node_location_image(self):
num_channels = 64
output_activation_map_size = 112
flattened_indices = np.arange(
num_channels * output_activation_map_size ** 2).reshape(
num_channels, output_activation_map_size,
output_activation_map_size)
true_row = np.random.randint(low=0, high=output_activation_map_size)
true_column = np.random.randint(low=0, high=output_activation_map_size)
true_channel = np.random.randint(low=0, high=num_channels)
(predicted_channel, predicted_row,
predicted_column) = masking._get_hidden_node_location(
flattened_index=flattened_indices[true_channel][true_row][true_column],
num_rows=output_activation_map_size,
num_columns=output_activation_map_size)
self.assertEqual(true_channel, predicted_channel)
self.assertEqual(true_row, predicted_row)
self.assertEqual(true_column, predicted_column)