x59 := (uint8(x58) & 0xff) x60 := uint8((x58 >> 8)) out1[0] = x5 out1[1] = x7 out1[2] = x9 out1[3] = x11 out1[4] = x13 out1[5] = x15 out1[6] = x17 out1[7] = x18 out1[8] = x19 out1[9] = x21 out1[10] = x23 out1[11] = x25 out1[12] = x27 out1[13] = x29 out1[14] = x31 out1[15] = x32 out1[16] = x33 out1[17] = x35 out1[18] = x37 out1[19] = x39 out1[20] = x41 out1[21] = x43 out1[22] = x45 out1[23] = x46 out1[24] = x47 out1[25] = x49 out1[26] = x51 out1[27] = x53 out1[28] = x55 out1[29] = x57 out1[30] = x59...

        secondLine.put("kinds", Arrays.toString(item.getKinds()));
        secondLine.put("@timestamp", item.getTimestamp());

        try (OutputStream out1 = getXContentOutputStream(firstLineMap); OutputStream out2 = getXContentOutputStream(secondLine)) {
            return ((ByteArrayOutputStream) out1).toString(CoreLibConstants.UTF_8) + '\n'
                    + ((ByteArrayOutputStream) out2).toString(CoreLibConstants.UTF_8);

  Define(-1, {}, {feed1, feed2}, {add, add}, {"out1", "out2"});

  // Use, run, and verify
  TF_Operation* two = ScalarConst(2, host_graph_, s_);
  TF_Operation* func_feed = Placeholder(host_graph_, s_);
  TF_Operation* func_op = Use({two, func_feed});
  Run({{func_feed, Int32Tensor(3)}}, {{func_op, 0}, {func_op, 1}}, {5, 5});
  VerifyFDef({"add"}, M({{"feed1"}, {"feed2"}}), M({{"out1"}, {"out2"}}),
             {{"feed1", "add:0"},

		result[i] = string(v)
	}
	return result
}

func collect(t *testing.T, seq iter.Seq[[]byte]) [][]byte {
	out := slices.Collect(seq)
	out1 := slices.Collect(seq)
	if !slices.Equal(sliceOfString(out), sliceOfString(out1)) {
		t.Fatalf("inconsistent seq:\n%s\n%s", out, out1)
	}
	return out
}

type LinesTest struct {
	a string
	b []string
}

var linesTests = []LinesTest{

    csession->SetOutputs(grad_outputs_vec);
    csession->Run(s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
    TF_Tensor* out0 = csession->output_tensor(0);
    TF_Tensor* out1 = csession->output_tensor(1);

    std::vector<TF_Output> expected_grad_outputs_vec;
    expected_grad_outputs_vec.assign(expected_grad_outputs,
                                     expected_grad_outputs + 2);