parameters: (self)
docstring: Reset the reader object when :code:`fluid.core.EOFException` raises. 
          Can only call when the reader object is not iterable.
          
          Example:
              .. code-block:: python
  
                  import paddle
                  import paddle.fluid as fluid
                  import numpy as np
  
                  BATCH_SIZE = 10
  
                  def generator():
                      for i in range(5):
                          yield np.random.uniform(low=0, high=255, size=[784, 784]),
  
                  image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
                  reader = fluid.io.PyReader(feed_list=[image], capacity=4, iterable=False)
                  reader.decorate_sample_list_generator(
                      paddle.batch(generator, batch_size=BATCH_SIZE))
  
                  executor = fluid.Executor(fluid.CPUPlace())
                  executor.run(fluid.default_startup_program())
                  for i in range(3):
                      reader.start()
                      while True:
                          try:
                              executor.run(feed=None)
                          except fluid.core.EOFException:
                              reader.reset()
                              break
docstring_summary: Reset the reader object when :code:`fluid.core.EOFException` raises. 
          Can only call when the reader object is not iterable.
          
          Example:
              .. code-block:: python
docstring_tokens: Reset the reader object when : code : fluid . core . EOFException raises . Can only call when the reader object is not iterable . Example : .. code - block :: python
function: def reset(self):
          '''
          Reset the reader object when :code:`fluid.core.EOFException` raises. 
          Can only call when the reader object is not iterable.
          
          Example:
              .. code-block:: python
  
                  import paddle
                  import paddle.fluid as fluid
                  import numpy as np
  
                  BATCH_SIZE = 10
  
                  def generator():
                      for i in range(5):
                          yield np.random.uniform(low=0, high=255, size=[784, 784]),
  
                  image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
                  reader = fluid.io.PyReader(feed_list=[image], capacity=4, iterable=False)
                  reader.decorate_sample_list_generator(
                      paddle.batch(generator, batch_size=BATCH_SIZE))
  
                  executor = fluid.Executor(fluid.CPUPlace())
                  executor.run(fluid.default_startup_program())
                  for i in range(3):
                      reader.start()
                      while True:
                          try:
                              executor.run(feed=None)
                          except fluid.core.EOFException:
                              reader.reset()
                              break        
  
          '''
          self._loader.reset()
function_tokens: def reset ( self ) : self . _loader . reset ( )