import "./a"

func main() {
	// Test that inlined type switches without short variable
	// declarations work correctly.
	check(0, a.F(nil)) // ERROR "inlining call to a.F"
	check(1, a.F(0))   // ERROR "inlining call to a.F" "does not escape"
	check(2, a.F(0.0)) // ERROR "inlining call to a.F" "does not escape"
	check(3, a.F(""))  // ERROR "inlining call to a.F" "does not escape"

	// Test that inlined type switches with short variable

	for i := range b[f()] {
		b[f()][i] = 0
	}
	if want := n + 1; x != n+1 {
		fmt.Printf("range expr function calls = %d want %d\n", x, want)
		os.Exit(1)
	}
}

func main() {
	check(0)
	check(1)
	check(15)

	}
	panic("not reached")
}

func check(x interface{}, s string) {
	w := whatis(x)
	if w != s {
		fmt.Println("whatis", x, "=>", w, "!=", s)
		panic("fail")
	}

	w = whatis1(x)
	if w != s {
		fmt.Println("whatis1", x, "=>", w, "!=", s)
		panic("fail")
	}
}

func main() {
	check(1, "signed 1")
	check(uint(1), "unsigned 1")
	check(int64(1), "signed64 1")
	check(uint64(1), "unsigned64 1")

		os.Exit(1)
	}
	if want := rune(-1); r != want {
		fmt.Printf("rune after range without side-effect = %q want %q\n", r, want)
		os.Exit(1)
	}
}

func main() {
	check(0)
	check(1)
	check(15)

// CHECK-LABEL: avg_pool2d_3
// CHECK: %cst = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32>
// CHECK: %0 = "tfl.transpose"(%arg0, %cst) : (tensor<1x1x1x8xf32>, tensor<4xi32>) -> tensor<1x1x8x1xf32>
// CHECK{LITERAL}: %cst_0 = arith.constant dense<[[0, 0], [0, 0], [1, 1], [0, 0]]> : tensor<4x2xi32>

	CMPBLT	R6, $4, lt4
	MOVWZ	0(R3)(R2*1), R8
	MOVWZ	0(R5)(R2*1), R9
	CMPBNE	R8, R9, notequal
	LA	4(R2), R2
	SUB	$4, R6
lt4:
#define CHECK(n) \
	CMPBEQ	R6, $n, equal \
	MOVB	n(R3)(R2*1), R8 \
	MOVB	n(R5)(R2*1), R9 \
	CMPBNE	R8, R9, notequal
	CHECK(0)
	CHECK(1)
	CHECK(2)
	CHECK(3)
	BR	equal

TEXT memeqbodyclc<>(SB),NOSPLIT|NOFRAME,$0-0
	CLC	$1, 0(R3), 0(R5)

  func.return %1 : tensor<2x1xf32>

// CHECK:  %cst = arith.constant
// CHECK:  %0 = "tf.Reshape"(%arg0, %cst)
// CHECK-SAME: tensor<2x1xf32>
// CHECK:  %1 = "tf.FakeQuantWithMinMaxVars"(%0, %arg1, %arg2)
// CHECK:  return %1
}

// CHECK-LABEL: fakeQuantFollowedByReshapes

  func.return %0 : tensor<8xf32>

// CHECK:  %0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %cst, %cst_0)
// CHECK:  %1 = "quantfork.qcast"(%0) : (tensor<8xf32>) -> tensor<8x!quant.uniform<i8:f32, 1.000000e+00:-128>>
// CHECK:  %2 = "quantfork.dcast"(%1)
// CHECK:  return %2
}

// CHECK-LABEL: fakeQuantForActivationNoDuplication

  func.return %0 : tensor<8xf32>

// CHECK:  %0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %cst, %cst_0)
// CHECK:  %1 = "quantfork.qcast"(%0) : (tensor<8xf32>) -> tensor<8x!quant.uniform<i4:f32, 1.000000e+00:-8>>
// CHECK:  %2 = "quantfork.dcast"(%1)
// CHECK:  return %2
}

// CHECK-LABEL: fakeQuantForActivationNoDuplication

  func.return %1 : tensor<2x1xf32>

// CHECK:  %cst = arith.constant
// CHECK:  %0 = "tf.Reshape"(%arg0, %cst)
// CHECK-SAME: tensor<2x1xf32>
// CHECK:  %1 = "tf.FakeQuantWithMinMaxVars"(%0, %arg1, %arg2)
// CHECK:  return %1
}

// CHECK-LABEL: fakeQuantFollowedByReshapes