code: def _partial_tensor_to_vec_data(draw):
      input_dtype, input, shape = draw(
          helpers.dtype_and_values(
              available_dtypes=helpers.get_dtypes("valid"),
              min_num_dims=1,
              ret_shape=True,
          )
      )
      ndims = len(shape)
      skip_begin = draw(helpers.ints(min_value=0, max_value=ndims - 1))
      skip_end = draw(
          helpers.ints(min_value=0, max_value=ndims - 1 - skip_begin)
      )
      return input_dtype, input, skip_begin, skip_end
  
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 10 for calling a global function with example usage: _partial_tensor_to_vec_data(draw) and returns: input_dtype,  input,  skip_begin,  skip_end