def get_slices(self, builder, array_arg_vars, axes, index_input_vars, 
                 cartesian_product = False, index_offsets = None): 
    slice_values = []
    axes = self.normalize_axes(array_arg_vars, axes)
    # only gets incremented if we're doing a cartesian product
    if cartesian_product:
      idx_counter = 0
      for i, curr_array in enumerate(array_arg_vars):
        axis = axes[i]
        rank = curr_array.type.rank
        if rank <= 1 and axis is None:
          axis = 0
           
        if axis is None:
          start = idx_counter
          stop = idx_counter + rank
          curr_indices = index_input_vars[start:stop]
          idx_counter = stop 
          curr_slice = builder.index(curr_array, curr_indices)
        elif rank > axis:
          idx = index_input_vars[idx_counter]
          idx_counter += 1
          curr_slice = builder.slice_along_axis(curr_array, axis, idx)
        else:
          curr_slice = curr_array 
        slice_values.append(curr_slice)
    else:
      for i, curr_array in enumerate(array_arg_vars):
        axis = axes[i]
        rank = curr_array.type.rank

        if rank <= 1 and axis is None:
          axis = 0
        if axis is None:
          assert rank <= len(index_input_vars), \
            "Insufficient indices for array arg %s : %s" % (curr_array, curr_array.type)
            
          # to be compatible with NumPy's broadcasting, we pull out the *last* r
          # indices so that Matrix + Vector will replicate the vector as columns, not rows
          curr_indices = index_input_vars[-rank:]
          curr_slice = builder.index(curr_array, curr_indices)
        elif rank > axis:
          curr_idx = index_input_vars[0]
          if index_offsets is not None:
            assert len(index_offsets) > i
            curr_offset = index_offsets[i]
            if not isinstance(curr_offset, Expr): 
              curr_offset = builder.int(curr_offset)
            curr_idx = builder.add(curr_idx, curr_offset)
          curr_slice = builder.slice_along_axis(curr_array, axis, curr_idx) 
        else:
          # if we're trying to map over axis 1 of a 1-d object, then there aren't
          # enough dims to slice anything, so it just gets passed in without modification
          
          curr_slice = curr_array 
        
          
        slice_values.append(curr_slice)
    return slice_values
dataset/ETHPy150Open iskandr/parakeet/parakeet/transforms/indexify_adverbs.py/IndexifyAdverbs.get_slices/swapped operands of `<=`