class_docstr: Base class for computing Hessian-vector product.
  
  Args:
      num_slices (int): Hessian-vector product function's inputs will be
          divided into num_slices and then averaged together to improve
          performance.
class_docstr_tok: ["Base","class","for","computing","Hessian-vector","product",".","Args",":","num_slices","(","int",")",":","Hessian-vector","product","function","'s","inputs","will","be","divided","into","num_slices","and","then","averaged","together","to","improve","performance","."]
code: def __init__(self, num_slices=1):
      self._target = None
      self._reg_coeff = None
      self._hvp_fun = None
      self._num_slices = num_slices
  
imports: import abc
  from dowel import logger
  import numpy
  import tensorflow
  from garage.tf import compile_function, flatten_tensor_variables, new_tensor_like
  from garage.tf.optimizers._dtypes import LazyDict
label_desc: Use image node_id 1 to create a new HessianVectorProduct object from inherited base classes: abc with example: obj = HessianVectorProduct(num_slices)