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Python networks.compression_model方法代码示例

本文整理汇总了Python中networks.compression_model方法的典型用法代码示例。如果您正苦于以下问题:Python networks.compression_model方法的具体用法?Python networks.compression_model怎么用?Python networks.compression_model使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在networks的用法示例。


在下文中一共展示了networks.compression_model方法的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: main

# 需要导入模块: import networks [as 别名]
# 或者: from networks import compression_model [as 别名]
def main(_, run_eval_loop=True):
  with tf.name_scope('inputs'):
    images = data_provider.provide_data(
        'validation', FLAGS.batch_size, dataset_dir=FLAGS.dataset_dir,
        patch_size=FLAGS.patch_size)

  # In order for variables to load, use the same variable scope as in the
  # train job.
  with tf.variable_scope('generator'):
    reconstructions, _, prebinary = networks.compression_model(
        images,
        num_bits=FLAGS.bits_per_patch,
        depth=FLAGS.model_depth,
        is_training=False)
  summaries.add_reconstruction_summaries(images, reconstructions, prebinary)

  # Visualize losses.
  pixel_loss_per_example = tf.reduce_mean(
      tf.abs(images - reconstructions), axis=[1, 2, 3])
  pixel_loss = tf.reduce_mean(pixel_loss_per_example)
  tf.summary.histogram('pixel_l1_loss_hist', pixel_loss_per_example)
  tf.summary.scalar('pixel_l1_loss', pixel_loss)

  # Create ops to write images to disk.
  uint8_images = data_provider.float_image_to_uint8(images)
  uint8_reconstructions = data_provider.float_image_to_uint8(reconstructions)
  uint8_reshaped = summaries.stack_images(uint8_images, uint8_reconstructions)
  image_write_ops = tf.write_file(
      '%s/%s'% (FLAGS.eval_dir, 'compression.png'),
      tf.image.encode_png(uint8_reshaped[0]))

  # For unit testing, use `run_eval_loop=False`.
  if not run_eval_loop: return
  tf.contrib.training.evaluate_repeatedly(
      FLAGS.checkpoint_dir,
      master=FLAGS.master,
      hooks=[tf.contrib.training.SummaryAtEndHook(FLAGS.eval_dir),
             tf.contrib.training.StopAfterNEvalsHook(1)],
      eval_ops=image_write_ops,
      max_number_of_evaluations=FLAGS.max_number_of_evaluations) 
开发者ID:rky0930,项目名称:yolo_v2,代码行数:42,代码来源:eval.py

示例2: test_generator_run

# 需要导入模块: import networks [as 别名]
# 或者: from networks import compression_model [as 别名]
def test_generator_run(self):
    img_batch = tf.zeros([3, 16, 16, 3])
    model_output = networks.compression_model(img_batch)
    with self.test_session() as sess:
      sess.run(tf.global_variables_initializer())
      sess.run(model_output) 
开发者ID:rky0930,项目名称:yolo_v2,代码行数:8,代码来源:networks_test.py

示例3: test_generator_graph

# 需要导入模块: import networks [as 别名]
# 或者: from networks import compression_model [as 别名]
def test_generator_graph(self):
    for i, batch_size in zip(xrange(3, 7), xrange(3, 11, 2)):
      tf.reset_default_graph()
      patch_size = 2 ** i
      bits = 2 ** i
      img = tf.ones([batch_size, patch_size, patch_size, 3])
      uncompressed, binary_codes, prebinary = networks.compression_model(
          img, bits)

      self.assertAllEqual([batch_size, patch_size, patch_size, 3],
                          uncompressed.shape.as_list())
      self.assertEqual([batch_size, bits], binary_codes.shape.as_list())
      self.assertEqual([batch_size, bits], prebinary.shape.as_list()) 
开发者ID:rky0930,项目名称:yolo_v2,代码行数:15,代码来源:networks_test.py

示例4: test_generator_invalid_input

# 需要导入模块: import networks [as 别名]
# 或者: from networks import compression_model [as 别名]
def test_generator_invalid_input(self):
    wrong_dim_input = tf.zeros([5, 32, 32])
    with self.assertRaisesRegexp(ValueError, 'Shape .* must have rank 4'):
      networks.compression_model(wrong_dim_input)

    not_fully_defined = tf.placeholder(tf.float32, [3, None, 32, 3])
    with self.assertRaisesRegexp(ValueError, 'Shape .* is not fully defined'):
      networks.compression_model(not_fully_defined) 
开发者ID:rky0930,项目名称:yolo_v2,代码行数:10,代码来源:networks_test.py

示例5: test_discriminator_invalid_input

# 需要导入模块: import networks [as 别名]
# 或者: from networks import compression_model [as 别名]
def test_discriminator_invalid_input(self):
    wrong_dim_input = tf.zeros([5, 32, 32])
    with self.assertRaisesRegexp(ValueError, 'Shape must be rank 4'):
      networks.discriminator(wrong_dim_input)

    not_fully_defined = tf.placeholder(tf.float32, [3, None, 32, 3])
    with self.assertRaisesRegexp(ValueError, 'Shape .* is not fully defined'):
      networks.compression_model(not_fully_defined) 
开发者ID:rky0930,项目名称:yolo_v2,代码行数:10,代码来源:networks_test.py


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