code: def generate_conv_inputs(
      stride,
      pad,
      kernel,
      dilation,
      size,
      group,
      input_channels_per_group,
      output_channels_per_group,
      batch_size,
      order,
      groupwise_quantization=False,
      preserve_activation_sparsity=False,
      preserve_weight_sparsity=False,
  ):
      return generate_convnd_inputs(
          (stride,) * 2,
          (pad,) * 2,
          (kernel,) * 2,
          (dilation,) * 2,
          (size,) * 2,
          group,
          input_channels_per_group,
          output_channels_per_group,
          batch_size,
          order,
          groupwise_quantization,
          preserve_activation_sparsity,
          preserve_weight_sparsity,
      )
  
file_path: pytorch/caffe2/quantization/server/dnnlowp_test_utils.py
imports: import collections
  import numpy
  from caffe2.python import utils, workspace
  from caffe2.quantization.server import dnnlowp_pybind11
  from hypothesis import assume
label_desc: Use image node_id 6 for calling a global function with example usage: generate_conv_inputs(stride, pad, kernel, dilation, size, group, input_channels_per_group, output_channels_per_group, batch_size, order, groupwise_quantization, preserve_activation_sparsity, preserve_weight_sparsity) and returns: generate_convnd_inputs