%1 = "tf.AddV2"(%arg1, %cst_1) {device = "/job:localhost/replica:0/task:0/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %3 = "tf.RaggedTensorToVariant"(%arg7) {RAGGED_RANK = 0 : i64, Tsplits = i64, Tvalues = i32, batched_input = false, device = "/job:localhost/replica:0/task:0/device:CPU:0"} : (tensor<*xi32>) -> tensor<!tf_type.variant>

			return err
		}
		f, err := fsys.Open(name)
		if err != nil {
			return err
		}
		defer f.Close()
		_, err = io.Copy(tw, f)
		return err
	})
}

// splitUSTARPath splits a path according to USTAR prefix and suffix rules.
// If the path is not splittable, then it will return ("", "", false).
func splitUSTARPath(name string) (prefix, suffix string, ok bool) {
	length := len(name)

  let summary = "";

  let arguments = (ins
    TF_StrTensor:$program_key,
    TF_Int32Tensor:$row_ids,
    TF_Int32Tensor:$col_ids,
    TF_Float32Tensor:$gains,
    TF_Int64Tensor:$splits,
    TF_Int32Tensor:$id_counts,

    ConfinedAttr<I64Attr, [IntMinValue<1>]>:$sample_count,
    ConfinedAttr<I64Attr, [IntMinValue<1>]>:$num_replica,

	//
	// The format of the metric may be described by the following regular expression.
	//
	// 	^(?P<name>/[^:]+):(?P<unit>[^:*/]+(?:[*/][^:*/]+)*)$
	//
	// The format splits the name into two components, separated by a colon: a path which always
	// starts with a /, and a machine-parseable unit. The name may contain any valid Unicode

}

func convertToStringMap(s []string) map[string]string {
	out := make(map[string]string, len(s))
	for _, l := range s {
		k, v := splitEqual(l)
		out[k] = v
	}
	return out
}

// splitEqual splits key=value string into key,value. if no = is found
// the whole string is the key and value is empty.
func splitEqual(str string) (string, string) {
	idx := strings.Index(str, "=")
	var k string
	var v string

// Addr returns p's IP address.
func (p AddrPort) Addr() Addr { return p.ip }

// Port returns p's port.
func (p AddrPort) Port() uint16 { return p.port }

// splitAddrPort splits s into an IP address string and a port
// string. It splits strings shaped like "foo:bar" or "[foo]:bar",
// without further validating the substrings. v6 indicates whether the
// ip string should parse as an IPv6 address or an IPv4 address, in

  EXPECT_EQ(add_fn.error_msg(), "");
  EXPECT_EQ(add_fn.result0(), 3);
  EXPECT_EQ(add_fn.result0_data()[0], 3);
  EXPECT_EQ(add_fn.result0_data(), add_fn.results()[0]);
}

TEST(TFCompileTest, Splits) {
  Eigen::ThreadPool tp(1);
  Eigen::ThreadPoolDevice device(&tp, tp.NumThreads());

  SplitsComp fn;

  fn.set_thread_pool(&device);
  // x = [[1, 2], [3, 4]]
  fn.arg0(0, 0) = 1;

	{name: "select", format: "package main; func main() { «select { default: «» }» }", scope: true},
}

// split splits pre«mid»post into pre, mid, post.
// If the string does not have that form, split returns x, "", "".
func split(x string) (pre, mid, post string) {
	start, end := strings.Index(x, "«"), strings.LastIndex(x, "»")

		sep := `\`
		if strings.HasPrefix(dirname, "/") {
			sep = `/`
		}
		dirname += sep
	}
	return drive + dirname + filename
}

// splitDrive splits the DOS drive letter or UNC share point from
// path, if any. path == drive + rest
func splitDrive(path string) (drive, rest string) {
	if len(path) >= 2 && path[1] == ':' {

    SameOperandsAndResultsScale]> {
  let summary = "Splits a tensor into `num_split` tensors along one dimension.";

  let description = [{
    Splits the `value` tensor along `split_dim` into a number of sub-tensors
    with same shape as the original one, except for `split_dim`. The grouping
    of the resultant sub-tensors is decided by `size-splits`. Same as tf.SplitV.
  }];

  let arguments = (ins