class_docstr: Class surrounding CURAND kernels from CUDA 3.2.
  It allows for generating random numbers with uniform
  and normal probability function of various types.
class_docstr_tok: ["Class","surrounding","CURAND","kernels","from","CUDA","3.2",".","It","allows","for","generating","random","numbers","with","uniform","and","normal","probability","function","of","various","types","."]
code: def call_skip_ahead(self, i, stream=None):
      self.skip_ahead.prepared_async_call(
          (self.block_count, 1),
          (self.generators_per_block, 1, 1),
          stream,
          self.state,
          self.generators_per_block,
          i,
      )
  
imports: import numpy
  import pycuda.compiler
  import pycuda.driver
  import pycuda.gpuarray
  from pytools import memoize_method
label_desc: Use image node_id 10 for calling the _RandomNumberGeneratorBase obj's underlying member method code with example usage: obj.call_skip_ahead(i, stream) without return types