code: def paddle_unfold_handler(draw, dtype):
      dtype = draw(dtype)
      h_size = draw(helpers.ints(min_value=10, max_value=30))
      w_size = draw(helpers.ints(min_value=10, max_value=30))
      channels = draw(helpers.ints(min_value=1, max_value=3))
      batch = draw(helpers.ints(min_value=1, max_value=10))
  
      x = draw(
          helpers.array_values(
              dtype=dtype[0],
              shape=[batch, channels, h_size, w_size],
              min_value=0,
              max_value=1,
          )
      )
  
      kernel_sizes = draw(helpers.ints(min_value=1, max_value=3))
      strides = draw(helpers.ints(min_value=1, max_value=3))
      paddings = draw(helpers.ints(min_value=1, max_value=3))
      dilations = draw(helpers.ints(min_value=1, max_value=3))
      return dtype, x, kernel_sizes, strides, paddings, dilations
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_paddle/test_nn/test_functional/test_common.py
imports: from hypothesis import strategies
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_frontends.test_torch.test_nn.test_functional.test_linear_functions import _x_and_linear
label_desc: Use image node_id 3 for calling a global function with example usage: paddle_unfold_handler(draw, dtype) and returns: dtype,  x,  kernel_sizes,  strides,  paddings,  dilations