class_docstr: Two-dimensional convolutional layer.
  
  Parameters
  ----------
  input_size : tuple
      the size of the input.
  output_size : tuple
      the size of the output..
  strides : matrix-like
      stride of the cross-correlation kernel.
  kernel : matrix-like
      the cross-correlation kernel.
  activation : str or None
      activation function name
  input_index_mapper : IndexMapper or None
      map indexes from this layer index to the input layer index size
code: def _eval_at_index(self, x, out_d, out_r, out_c):
      acc = 0.0
      for k, index in self.kernel_with_input_indexes(
          out_d, out_r, out_c
      ):
          acc += k * x[index]
      return acc
  
imports: import itertools
  import numpy
label_desc: Use image node_id 7 for calling the ConvLayer2D obj's underlying member method code with example usage: obj._eval_at_index(x, out_d, out_r, out_c) and returns: acc