old_contents: import numpy
  
  from chainer import cuda
  from chainer import function
  from chainer import utils
  from chainer.utils import type_check
  
  
  class Log1p(function.Function):
  
      @property
      def label(self):
          return 'log1p'
  
      def check_type_forward(self, in_types):
          type_check.expect(in_types.size() == 1)
          type_check.expect(in_types[0].dtype.kind == 'f')
  
      def forward_cpu(self, x):
          return utils.force_array(numpy.log1p(x[0])),
  
      def forward_gpu(self, x):
          return cuda.cupy.log1p(x[0]),
  
      def backward(self, x, gy):
          return utils.force_array((gy[0] / (x[0] + 1.0)).astype(numpy.float32)),
  
  
  def log1p(x):
      """Elementwise natural logarithm plus one function. """
      return Log1p()(x)
  
new_contents: import numpy
  
  from chainer import cuda
  from chainer import function
  from chainer import utils
  from chainer.utils import type_check
  
  
  class Log1p(function.Function):
  
      @property
      def label(self):
          return 'log1p'
  
      def check_type_forward(self, in_types):
          type_check.expect(in_types.size() == 1)
          type_check.expect(in_types[0].dtype.kind == 'f')
  
      def forward_cpu(self, x):
          return utils.force_array(numpy.log1p(x[0])),
  
      def forward_gpu(self, x):
          return cuda.cupy.log1p(x[0]),
  
      def backward(self, x, gy):
          return utils.force_array((gy[0] / (x[0] + 1.0)).astype(numpy.float32)),
  
  
  def log1p(x):
      """Elementwise natural logarithm plus one function."""
      return Log1p()(x)
  
subject: modify logarithm_m1.py