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Python model_helpers.generate_synthetic_data方法代码示例

本文整理汇总了Python中official.utils.misc.model_helpers.generate_synthetic_data方法的典型用法代码示例。如果您正苦于以下问题：Python model_helpers.generate_synthetic_data方法的具体用法？Python model_helpers.generate_synthetic_data怎么用？Python model_helpers.generate_synthetic_data使用的例子？那么恭喜您, 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类official.utils.misc.model_helpers的用法示例。


在下文中一共展示了model_helpers.generate_synthetic_data方法的9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: test_generate_nested_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def test_generate_nested_data(self):
    d = model_helpers.generate_synthetic_data(
        input_shape={'a': tf.TensorShape([2]),
                     'b': {'c': tf.TensorShape([3]), 'd': tf.TensorShape([])}},
        input_value=1.1)

    element = d.make_one_shot_iterator().get_next()
    self.assertIn('a', element)
    self.assertIn('b', element)
    self.assertEquals(len(element['b']), 2)
    self.assertIn('c', element['b'])
    self.assertIn('d', element['b'])
    self.assertNotIn('c', element)

    with self.test_session() as sess:
      inp = sess.run(element)
      self.assertAllClose(inp['a'], [1.1, 1.1])
      self.assertAllClose(inp['b']['c'], [1.1, 1.1, 1.1])
      self.assertAllClose(inp['b']['d'], 1.1)
开发者ID:rockyzhengwu，项目名称:nsfw，代码行数:21，代码来源:model_helpers_test.py

示例2: test_generate_nested_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def test_generate_nested_data(self):
    d = model_helpers.generate_synthetic_data(
        input_shape={'a': tf.TensorShape([2]),
                     'b': {'c': tf.TensorShape([3]), 'd': tf.TensorShape([])}},
        input_value=1.1)

    element = tf.compat.v1.data.make_one_shot_iterator(d).get_next()
    self.assertIn('a', element)
    self.assertIn('b', element)
    self.assertEquals(len(element['b']), 2)
    self.assertIn('c', element['b'])
    self.assertIn('d', element['b'])
    self.assertNotIn('c', element)

    with self.session() as sess:
      inp = sess.run(element)
      self.assertAllClose(inp['a'], [1.1, 1.1])
      self.assertAllClose(inp['b']['c'], [1.1, 1.1, 1.1])
      self.assertAllClose(inp['b']['d'], 1.1)
开发者ID:ShivangShekhar，项目名称:Live-feed-object-device-identification-using-Tensorflow-and-OpenCV，代码行数:21，代码来源:model_helpers_test.py

示例3: _generate_synthetic_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def _generate_synthetic_data(params):
  """Create synthetic data based on the parameter batch size."""
  batch_size = int(params["batch_size"] // params["max_length"])
  length = params["max_length"]
  dataset = model_helpers.generate_synthetic_data(
      input_shape=tf.TensorShape([length]),
      input_value=1,
      input_dtype=tf.int64,
      label_shape=tf.TensorShape([length]),
      label_value=1,
      label_dtype=tf.int64,
  )
  if params["static_batch"]:
    dataset = dataset.batch(batch_size, drop_remainder=True)
  else:
    dataset = dataset.padded_batch(batch_size, ([None], [None]))
  return dataset
开发者ID:tensorflow，项目名称:models，代码行数:19，代码来源:data_pipeline.py

示例4: test_generate_synethetic_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def test_generate_synethetic_data(self):
    input_element, label_element = model_helpers.generate_synthetic_data(
        input_shape=tf.TensorShape([5]),
        input_value=123,
        input_dtype=tf.float32,
        label_shape=tf.TensorShape([]),
        label_value=456,
        label_dtype=tf.int32).make_one_shot_iterator().get_next()

    with self.test_session() as sess:
      for n in range(5):
        inp, lab = sess.run((input_element, label_element))
        self.assertAllClose(inp, [123., 123., 123., 123., 123.])
        self.assertEquals(lab, 456)
开发者ID:rockyzhengwu，项目名称:nsfw，代码行数:16，代码来源:model_helpers_test.py

示例5: test_generate_only_input_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def test_generate_only_input_data(self):
    d = model_helpers.generate_synthetic_data(
        input_shape=tf.TensorShape([4]),
        input_value=43.5,
        input_dtype=tf.float32)

    element = d.make_one_shot_iterator().get_next()
    self.assertFalse(isinstance(element, tuple))

    with self.test_session() as sess:
      inp = sess.run(element)
      self.assertAllClose(inp, [43.5, 43.5, 43.5, 43.5])
开发者ID:rockyzhengwu，项目名称:nsfw，代码行数:14，代码来源:model_helpers_test.py

示例6: _generate_synthetic_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def _generate_synthetic_data(params):
  """Create synthetic data based on the parameter batch size."""
  batch = length = int(math.sqrt(params["batch_size"]))
  return model_helpers.generate_synthetic_data(
      input_shape=tf.TensorShape([batch, length]),
      input_value=1,
      input_dtype=tf.int32,
      label_shape=tf.TensorShape([batch, length]),
      label_value=1,
      label_dtype=tf.int32,
  )
开发者ID:PipelineAI，项目名称:models，代码行数:13，代码来源:dataset.py

示例7: test_generate_synethetic_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def test_generate_synethetic_data(self):
    input_element, label_element = tf.compat.v1.data.make_one_shot_iterator(
        model_helpers.generate_synthetic_data(input_shape=tf.TensorShape([5]),
                                              input_value=123,
                                              input_dtype=tf.float32,
                                              label_shape=tf.TensorShape([]),
                                              label_value=456,
                                              label_dtype=tf.int32)).get_next()

    with self.session() as sess:
      for n in range(5):
        inp, lab = sess.run((input_element, label_element))
        self.assertAllClose(inp, [123., 123., 123., 123., 123.])
        self.assertEquals(lab, 456)
开发者ID:ShivangShekhar，项目名称:Live-feed-object-device-identification-using-Tensorflow-and-OpenCV，代码行数:16，代码来源:model_helpers_test.py

示例8: test_generate_only_input_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def test_generate_only_input_data(self):
    d = model_helpers.generate_synthetic_data(
        input_shape=tf.TensorShape([4]),
        input_value=43.5,
        input_dtype=tf.float32)

    element = tf.compat.v1.data.make_one_shot_iterator(d).get_next()
    self.assertFalse(isinstance(element, tuple))

    with self.session() as sess:
      inp = sess.run(element)
      self.assertAllClose(inp, [43.5, 43.5, 43.5, 43.5])
开发者ID:ShivangShekhar，项目名称:Live-feed-object-device-identification-using-Tensorflow-and-OpenCV，代码行数:14，代码来源:model_helpers_test.py

示例9: _generate_synthetic_data

# 需要导入模块: from official.utils.misc import model_helpers [as 别名]
# 或者: from official.utils.misc.model_helpers import generate_synthetic_data [as 别名]
def _generate_synthetic_data(params):
  """Create synthetic data based on the parameter batch size."""
  batch = length = int(math.sqrt(params["batch_size"]))
  dataset = model_helpers.generate_synthetic_data(
      input_shape=tf.TensorShape([length]),
      input_value=1,
      input_dtype=tf.int64,
      label_shape=tf.TensorShape([length]),
      label_value=1,
      label_dtype=tf.int64,
  )
  return dataset.batch(batch, drop_remainder=True)
开发者ID:ShivangShekhar，项目名称:Live-feed-object-device-identification-using-Tensorflow-and-OpenCV，代码行数:14，代码来源:data_pipeline.py


注：本文中的official.utils.misc.model_helpers.generate_synthetic_data方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。