code: def _partial_vec_to_tensor(draw):
      shape = draw(helpers.get_shape(min_num_dims=1, max_num_dims=5))
      numel = int(ivy.prod(shape))
      input_dtype, input = draw(
          helpers.dtype_and_values(
              available_dtypes=helpers.get_dtypes("float"),
              shape=(numel,),
          )
      )
      ndims = len(shape)
      skip_begin = draw(helpers.ints(min_value=0, max_value=ndims - 1))
      return input_dtype, input, shape, skip_begin
  
imports: from hypothesis import strategies, assume
  import hypothesis.extra.numpy
  import numpy
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test, create_concatenable_arrays_dtypes
  from ivy.functional.ivy.experimental.manipulation import _check_bounds
  from ivy_tests.test_ivy.test_functional.test_core.test_manipulation import _get_splits
label_desc: Use image node_id 12 for calling a global function with example usage: _partial_vec_to_tensor(draw) and returns: input_dtype,  input,  shape,  skip_begin