code: def input(
      shape,
      dtype=default_override_or(np.float32),
      needs_gradient=False,
      is_sparse=False,
      sequence_axis=Axis.default_dynamic_axis(),
      name="",
  ):
      """
      DEPRECATED.
  
      It creates an input in the network: a place where data,
      such as features and labels, should be provided.
  
      Args:
          shape (tuple or int): the shape of the input tensor
          dtype (np.float32 or np.float64 or np.float16): data type. Default is np.float32.
          needs_gradients (bool, optional): whether to back-propagates to it or not. False by default.
          is_sparse (bool, optional): whether the variable is sparse (`False` by default)
          sequence_axis (:class:`~cntk.axis.Axis`): a dynamic axis (e.g., default_dynamic_axis())
          name (str, optional): the name of the Function instance in the network
  
      Returns:
          :class:`~cntk.variables.Variable`
      """
      import warnings
  
      warnings.warn(
          "This will be removed in future versions. Please use "
          "input_variable() instead.",
          DeprecationWarning,
      )
  
      return input_variable(
          shape, dtype, needs_gradient, is_sparse, sequence_axis, name
      )
  
imports: import numpy
  from cntk.internal import typemap, sanitize_input
  from cntk.internal.utils import get_data_type
  from ...axis import Axis
  from ...default_options import default_override_or
label_desc: Use image node_id 1 for calling a global function with example usage: input(shape, dtype, needs_gradient, is_sparse, sequence_axis, name) and returns: input_variable