new_contents: from __future__ import absolute_import, division, print_function
  
  from .common import Benchmark
  
  import numpy as np
  
  
  class ArrayCoercionSmall(Benchmark):
      # More detailed benchmarks for array coercion,
      # some basic benchmarks are in `bench_core.py`.
      params = [[range(3), [1], 1, np.array([5], dtype=np.int64), np.int64(5)]]
      param_names = ['array_like']
      int64 = np.dtype(np.int64)
  
      def time_array_invalid_kwarg(self, array_like):
          try:
              np.array(array_like, ndmin="not-integer")
          except TypeError:
              pass
  
      def time_array(self, array_like):
          np.array(array_like)
  
      def time_array_dtype_not_kwargs(self, array_like):
          np.array(array_like, self.int64)
  
      def time_array_no_copy(self, array_like):
          np.array(array_like, copy=False)
  
      def time_array_subok(self, array_like):
          np.array(array_like, subok=True)
  
      def time_array_all_kwargs(self, array_like):
          np.array(array_like, dtype=self.int64, copy=False, order="F",
                   subok=False, ndmin=2)
  
      def time_asarray(self, array_like):
          np.asarray(array_like)
  
      def time_asarray_dtype(self, array_like):
          np.array(array_like, dtype=self.int64)
  
      def time_asarray_dtype(self, array_like):
          np.array(array_like, dtype=self.int64, order="F")
  
      def time_asanyarray(self, array_like):
          np.asarray(array_like)
  
      def time_asanyarray_dtype(self, array_like):
          np.array(array_like, dtype=self.int64)
  
      def time_asanyarray_dtype(self, array_like):
          np.array(array_like, dtype=self.int64, order="F")
  
      def time_ascontiguousarray(self, array_like):
          np.ascontiguousarray(array_like)
  
  
subject: Add benchmark for small array coercions