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| 1 | from multiprocessing import Process, Queue | |
| 2 | from keras.utils.test_utils import keras_test | |
| 3 | from keras.utils.test_utils import layer_test | |
| 4 | from keras.utils.generic_utils import CustomObjectScope | |
| 5 | from keras.models import Sequential | |
| 6 | from keras import applications | |
| 7 | from keras import backend as K | |
| 8 | ||
| 9 | def test_inceptionresnetv2_notop(): | |
| 10 | def target(queue): | |
| 11 | model = applications.InceptionResNetV2(weights=None, include_top=False) | |
| 12 | queue.put(model.output_shape) | |
| 13 | global_image_data_format = K.image_data_format() | |
| 14 | queue = Queue() | |
| 15 | K.set_image_data_format('channels_first')
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| 16 | p = Process(target=target, args=(queue,)) | |
| 17 | p.start() | |
| 18 | p.join() | |
| 19 | K.set_image_data_format(global_image_data_format) | |
| 20 | assert not queue.empty(), 'Model creation failed.' | |
| 21 | model_output_shape = queue.get_nowait() | |
| 22 | assert model_output_shape == (None, 1536, None, None) | |
| 23 | K.set_image_data_format('channels_last')
| |
| 24 | p = Process(target=target, args=(queue,)) | |
| 25 | p.start() | |
| 26 | p.join() | |
| 27 | K.set_image_data_format(global_image_data_format) | |
| 28 | assert not queue.empty(), 'Model creation failed.' | |
| 29 | model_output_shape = queue.get_nowait() | |
| 30 | assert model_output_shape == (None, None, None, 1536) | |
| 31 | - | return True |
| 31 | + | |
| 32 | ||
| 33 | ||
| 34 | - | test_inceptionresnetv2_notop() |
| 34 | + | |
| 35 | import time | |
| 36 | start = time.time() | |
| 37 | test_inceptionresnetv2_notop() | |
| 38 | print('Exec time: ' + str(time.time()-start)) |
