{"abc\nd\t ", "abc", "d\t "},
}

func TestGetLine(t *testing.T) {
	for i, test := range getLineTests {
		x, y := getLine([]byte(test.in))
		if string(x) != test.out1 || string(y) != test.out2 {
			t.Errorf("#%d got:%+v,%+v want:%s,%s", i, x, y, test.out1, test.out2)
		}
	}
}

func TestDecode(t *testing.T) {
	result, remainder := Decode([]byte(pemData))
	if !reflect.DeepEqual(result, certificate) {

// Test the solution, silently.

package main

type T chan uint64

func M(f uint64) (in, out T) {
	in = make(T, 100)
	out = make(T, 100)
	go func(in, out T, f uint64) {
		for {
			out <- f*<-in
		}
	}(in, out, f)
	return in, out
}


func min(xs []uint64) uint64 {
	m := xs[0]
	for i := 1; i < len(xs); i++ {
		if xs[i] < m {
			m = xs[i]
		}
	}

  let description = [{
    Transfer a CPU tensor to device.

    Example:
      %device_tensor = gpurt.transfer_to_device %cpu_tensor
  }];

  let arguments = (ins TFTensorType);
  let results = (outs TFTensorType);
  let assemblyFormat = "operands attr-dict";
}

// TODO(b/260267885): We may add a device argument when we want to support
// GPU MIG.
def TransferFromDeviceOp: Gpu_Op<"transfer_from_device"> {

func machoRewriteUuid(ctxt *Link, exef *os.File, exem *macho.File, outexe string) error {
	outf, err := os.OpenFile(outexe, os.O_RDWR|os.O_CREATE|os.O_TRUNC, 0755)
	if err != nil {
		return err
	}
	defer outf.Close()

	// Copy over the file.
	if _, err := io.Copy(outf, exef); err != nil {
		return err
	}

	// Locate the portion of the binary containing the load commands.

  let results = (outs quant_RealValueType);
}

// A DequantizeCast op (dcast) represents the inverse of a qcast,
// converting back from a quantized to quantizable (expressed) type.
//
// Like qcasts, a dcast is allowed to have both its operand and result
// as non quantized types. This facilitates transformations and marks edges
// where the computation must be carried out in the expressed type.
//

				fmt.Fprintf(w, "\t// %0*b\n", size, e.out[i])
				if e.name == "RotateLeft" && e.out2[i] != nil {
					fmt.Fprintf(w, "\t// %0*b\n", size, e.out2[i])
				}
			default:
				fmt.Fprintf(w, "\tfmt.Printf(\"%s(%%0%db) = %%d\\n\", %d, bits.%s(%d))\n", f, size, e.in, f, e.in)
				fmt.Fprintf(w, "\t// Output:\n")
				fmt.Fprintf(w, "\t// %s(%0*b) = %d\n", f, size, e.in, e.out[i])
			}
			fmt.Fprintf(w, "}\n")
		}
	}

    $future: A value of type !mlrt.future. The underlying value must be a tensorflow tensor.

    $result: a tensorflow tensor.
  }];

  let arguments = (ins
    MlrtFutureType:$future
  );

  let results = (outs
    TF_Tensor:$result
  );
}

// tf_mlrt.tf_promise takes a tensorflow Tensor. It is a fake op that is only
// used during parallelization and has no runtime implementation.

  }];

  let description = [{
This op captures all needed live-in values.
  }];

  let arguments = (ins
    StrAttr:$device
  );

  let results = (outs
    Variadic<AnyType>:$results
  );

  let regions = (region SizedRegion<1>:$body);

  let extraClassDeclaration = [{
    Block &GetBody() { return getOperation()->getRegion(0).front(); }
    bool WrapsSingleOp();

	}

	for i, tt := range parseMACTests {
		out, err := ParseMAC(tt.in)
		if !reflect.DeepEqual(out, tt.out) || !match(err, tt.err) {
			t.Errorf("ParseMAC(%q) = %v, %v, want %v, %v", tt.in, out, err, tt.out, tt.err)
		}
		if tt.err == "" {
			// Verify that serialization works too, and that it round-trips.
			s := out.String()
			out2, err := ParseMAC(s)
			if err != nil {

    the result values (or fetches) of the `tf_executor.graph` operation. The
    behavior is undefined if any of the operands of the `tf_executor.fetch` is
    dead.
  }];

  let results = (outs
    Variadic<AnyType>:$results
  );

  let regions = (region SizedRegion<1>:$body);

  let extraClassDeclaration = [{
    Block &GetBody() { return getOperation()->getRegion(0).front(); }