Python inception.inception_v4方法代碼示例

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testBuildLogits(self):
    batch_size = 5
    height, width = 299, 299
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    logits, end_points = inception.inception_v4(inputs, num_classes)
    auxlogits = end_points['AuxLogits']
    predictions = end_points['Predictions']
    self.assertTrue(auxlogits.op.name.startswith('InceptionV4/AuxLogits'))
    self.assertListEqual(auxlogits.get_shape().as_list(),
                         [batch_size, num_classes])
    self.assertTrue(logits.op.name.startswith('InceptionV4/Logits'))
    self.assertListEqual(logits.get_shape().as_list(),
                         [batch_size, num_classes])
    self.assertTrue(predictions.op.name.startswith(
        'InceptionV4/Logits/Predictions'))
    self.assertListEqual(predictions.get_shape().as_list(),
                         [batch_size, num_classes]) 

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testTrainEvalWithReuse(self):
    train_batch_size = 5
    eval_batch_size = 2
    height, width = 150, 150
    num_classes = 1000
    with self.test_session() as sess:
      train_inputs = tf.random_uniform((train_batch_size, height, width, 3))
      inception.inception_v4(train_inputs, num_classes)
      eval_inputs = tf.random_uniform((eval_batch_size, height, width, 3))
      logits, _ = inception.inception_v4(eval_inputs,
                                         num_classes,
                                         is_training=False,
                                         reuse=True)
      predictions = tf.argmax(logits, 1)
      sess.run(tf.global_variables_initializer())
      output = sess.run(predictions)
      self.assertEquals(output.shape, (eval_batch_size,)) 

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testGlobalPoolUnknownImageShape(self):
    batch_size = 1
    height, width = 350, 400
    num_classes = 1000
    with self.test_session() as sess:
      inputs = tf.placeholder(tf.float32, (batch_size, None, None, 3))
      logits, end_points = inception.inception_v4(
          inputs, num_classes, create_aux_logits=False)
      self.assertTrue(logits.op.name.startswith('InceptionV4/Logits'))
      self.assertListEqual(logits.get_shape().as_list(),
                           [batch_size, num_classes])
      pre_pool = end_points['Mixed_7d']
      images = tf.random_uniform((batch_size, height, width, 3))
      sess.run(tf.global_variables_initializer())
      logits_out, pre_pool_out = sess.run([logits, pre_pool],
                                          {inputs: images.eval()})
      self.assertTupleEqual(logits_out.shape, (batch_size, num_classes))
      self.assertTupleEqual(pre_pool_out.shape, (batch_size, 9, 11, 1536)) 

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testGlobalPoolUnknownImageShape(self):
    batch_size = 2
    height, width = 400, 600
    num_classes = 1000
    with self.test_session() as sess:
      inputs = tf.placeholder(tf.float32, (batch_size, None, None, 3))
      logits, end_points = inception.inception_v4(
          inputs, num_classes, create_aux_logits=False)
      self.assertTrue(logits.op.name.startswith('InceptionV4/Logits'))
      self.assertListEqual(logits.get_shape().as_list(),
                           [batch_size, num_classes])
      pre_pool = end_points['Mixed_7d']
      images = tf.random_uniform((batch_size, height, width, 3))
      sess.run(tf.global_variables_initializer())
      logits_out, pre_pool_out = sess.run([logits, pre_pool],
                                          {inputs: images.eval()})
      self.assertTupleEqual(logits_out.shape, (batch_size, num_classes))
      self.assertTupleEqual(pre_pool_out.shape, (batch_size, 11, 17, 1536)) 

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testBuildWithoutAuxLogits(self):
    batch_size = 5
    height, width = 299, 299
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    logits, endpoints = inception.inception_v4(inputs, num_classes,
                                               create_aux_logits=False)
    self.assertFalse('AuxLogits' in endpoints)
    self.assertTrue(logits.op.name.startswith('InceptionV4/Logits'))
    self.assertListEqual(logits.get_shape().as_list(),
                         [batch_size, num_classes]) 

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testVariablesSetDevice(self):
    batch_size = 5
    height, width = 299, 299
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    # Force all Variables to reside on the device.
    with tf.variable_scope('on_cpu'), tf.device('/cpu:0'):
      inception.inception_v4(inputs, num_classes)
    with tf.variable_scope('on_gpu'), tf.device('/gpu:0'):
      inception.inception_v4(inputs, num_classes)
    for v in tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope='on_cpu'):
      self.assertDeviceEqual(v.device, '/cpu:0')
    for v in tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope='on_gpu'):
      self.assertDeviceEqual(v.device, '/gpu:0') 

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testHalfSizeImages(self):
    batch_size = 5
    height, width = 150, 150
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    logits, end_points = inception.inception_v4(inputs, num_classes)
    self.assertTrue(logits.op.name.startswith('InceptionV4/Logits'))
    self.assertListEqual(logits.get_shape().as_list(),
                         [batch_size, num_classes])
    pre_pool = end_points['Mixed_7d']
    self.assertListEqual(pre_pool.get_shape().as_list(),
                         [batch_size, 3, 3, 1536]) 

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testEvaluation(self):
    batch_size = 2
    height, width = 299, 299
    num_classes = 1000
    with self.test_session() as sess:
      eval_inputs = tf.random_uniform((batch_size, height, width, 3))
      logits, _ = inception.inception_v4(eval_inputs,
                                         num_classes,
                                         is_training=False)
      predictions = tf.argmax(logits, 1)
      sess.run(tf.global_variables_initializer())
      output = sess.run(predictions)
      self.assertEquals(output.shape, (batch_size,)) 

# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v4 [as 別名]
def testBuildPreLogitsNetwork(self):
    batch_size = 5
    height, width = 299, 299
    num_classes = None
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4(inputs, num_classes)
    self.assertTrue(net.op.name.startswith('InceptionV4/Logits/AvgPool'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 1, 1, 1536])
    self.assertFalse('Logits' in end_points)
    self.assertFalse('Predictions' in end_points)