Beispiel #1
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 def test_close_early(self):
     sampler = WeightedSampler(reader=get_2d_reader(),
                               data_param=MOD_2D_DATA,
                               batch_size=2,
                               windows_per_image=10,
                               queue_length=10)
     sampler.close_all()
 def test_close_early(self):
     sampler = WeightedSampler(reader=get_2d_reader(),
                               data_param=MOD_2D_DATA,
                               batch_size=2,
                               windows_per_image=10,
                               queue_length=10)
     sampler.close_all()
 def test_dynamic_init(self):
     sampler = WeightedSampler(reader=get_dynamic_window_reader(),
                               data_param=DYNAMIC_MOD_DATA,
                               batch_size=2,
                               windows_per_image=10,
                               queue_length=10)
     with self.test_session() as sess:
         coordinator = tf.train.Coordinator()
         sampler.run_threads(sess, coordinator, num_threads=2)
         with self.assertRaisesRegexp(tf.errors.OutOfRangeError, ""):
             out = sess.run(sampler.pop_batch_op())
Beispiel #4
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 def test_dynamic_init(self):
     sampler = WeightedSampler(reader=get_dynamic_window_reader(),
                               data_param=DYNAMIC_MOD_DATA,
                               batch_size=2,
                               windows_per_image=10,
                               queue_length=10)
     with self.test_session() as sess:
         coordinator = tf.train.Coordinator()
         sampler.run_threads(sess, coordinator, num_threads=2)
         with self.assertRaisesRegexp(tf.errors.OutOfRangeError, ""):
             out = sess.run(sampler.pop_batch_op())
 def test_dynamic_init(self):
     sampler = WeightedSampler(reader=get_dynamic_window_reader(),
                               data_param=DYNAMIC_MOD_DATA,
                               batch_size=2,
                               windows_per_image=10,
                               queue_length=10)
     with self.test_session() as sess:
         coordinator = tf.train.Coordinator()
         sampler.run_threads(sess, coordinator, num_threads=2)
         out = sess.run(sampler.pop_batch_op())
         self.assertAllClose(out['image'].shape[1:], (8, 2, 256, 2))
Beispiel #6
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 def test_ill_init(self):
     with self.assertRaisesRegexp(KeyError, ""):
         sampler = WeightedSampler(reader=get_3d_reader(),
                                   data_param=MOD_2D_DATA,
                                   batch_size=2,
                                   windows_per_image=10,
                                   queue_length=10)
Beispiel #7
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 def initialise_weighted_sampler(self):
     self.sampler = [[WeightedSampler(
         reader=reader,
         data_param=self.data_param,
         batch_size=self.net_param.batch_size,
         windows_per_image=self.action_param.sample_per_volume,
         queue_length=self.net_param.queue_length) for reader in
         self.readers]]
Beispiel #8
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 def test_2d_init(self):
     sampler = WeightedSampler(reader=get_2d_reader(),
                               data_param=MOD_2D_DATA,
                               batch_size=2,
                               windows_per_image=10,
                               queue_length=10)
     with self.test_session() as sess:
         coordinator = tf.train.Coordinator()
         sampler.run_threads(sess, coordinator, num_threads=2)
         out = sess.run(sampler.pop_batch_op())
         self.assertAllClose(out['image'].shape, (2, 10, 9, 1))
     sampler.close_all()
 def test_2d_init(self):
     sampler = WeightedSampler(reader=get_2d_reader(),
                               data_param=MOD_2D_DATA,
                               batch_size=2,
                               windows_per_image=10,
                               queue_length=10)
     with self.test_session() as sess:
         coordinator = tf.train.Coordinator()
         sampler.run_threads(sess, coordinator, num_threads=2)
         out = sess.run(sampler.pop_batch_op())
         self.assertAllClose(out['image'].shape, (2, 10, 9, 1))
     sampler.close_all()