package types

import (
	"go/token"
	"testing"
)

var assignOps = map[token.Token]token.Token{
	token.ADD_ASSIGN:     token.ADD,
	token.SUB_ASSIGN:     token.SUB,
	token.MUL_ASSIGN:     token.MUL,
	token.QUO_ASSIGN:     token.QUO,
	token.REM_ASSIGN:     token.REM,
	token.AND_ASSIGN:     token.AND,
	token.OR_ASSIGN:      token.OR,
	token.XOR_ASSIGN:     token.XOR,
	token.SHL_ASSIGN:     token.SHL,

		bx := math.Float64bits(x)
		by := math.Float64bits(y)
		return math.Float64frombits(f(bx, by))
	}
}

func add(x, y float64) float64 { return x + y }
func sub(x, y float64) float64 { return x - y }
func mul(x, y float64) float64 { return x * y }
func div(x, y float64) float64 { return x / y }

func TestFloat64(t *testing.T) {
	base := []float64{
		0,
		math.Copysign(0, -1),
		-1,
		1,
		math.NaN(),

// var + var*var
func CmpToZero_ex3(a, b, c, d int64, e, f, g, h int32) int {
	// arm64:`CMN`,-`MADD`,`MUL`,`(BMI|BPL)`
	if a+b*c < 0 {
		return 1
	}

	// arm64:`CMN`,-`MADD`,`MUL`,`(BMI|BPL)`
	if b+c*d >= 0 {
		return 2
	}

	// arm64:`CMNW`,-`MADDW`,`MULW`,`BEQ`,`(BMI|BPL)`
	// arm:`CMN`,-`MULA`,`MUL`,`BEQ`,`(BMI|BPL)`
	if e+f*g > 0 {
		return 5
	}

	}
	// Initialize lastTs if it hasn't been yet.
	if b.lastTs == 0 {
		b.lastTs = freq.mul(batches[b.idx].time)
	}
	// Read an event out.
	n, tsdiff, err := readTimedBaseEvent(batches[b.idx].data[b.dataOff:], &b.ev)
	if err != nil {
		return false, err
	}
	// Complete the timestamp from the cursor's last timestamp.
	b.ev.time = freq.mul(tsdiff) + b.lastTs

	// Move the cursor's timestamp forward.
	b.lastTs = b.ev.time

TF_Operation* Min(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                  TF_Status* s, const char* name = "min");

TF_Operation* Mul(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                  TF_Status* s, const char* name = "mul");

// If `op_device` is non-empty, set the created op on that device.
TF_Operation* MinWithDevice(TF_Operation* l, TF_Operation* r, TF_Graph* graph,

		{0, 1, 2, -1, '-', (*Float).Sub},
		{1, 2, 0, 2, '-', (*Float).Sub},
		{2, 0, 1, -1, '-', (*Float).Sub},

		{0, 0, 0, 0, '*', (*Float).Mul},
		{0, 1, 2, 2, '*', (*Float).Mul},
		{1, 2, 0, 0, '*', (*Float).Mul},
		{2, 0, 1, 0, '*', (*Float).Mul},

		// {0, 0, 0, 0, '/', (*Float).Quo}, // panics
		{0, 2, 1, 2, '/', (*Float).Quo},
		{1, 2, 0, 0, '/', (*Float).Quo}, // = +Inf
		{2, 0, 1, 0, '/', (*Float).Quo},

	"}\n" +
	"\n" +
	"func testInt64Binary(a, b, add, sub, mul, div, mod, and, or, xor, andnot int64, dodiv bool) {\n" +
	"	if n, op, want := a + b, `+`, add; n != want { ok=false; println(`int64`, a, op, b, `=`, n, `should be`, want); }\n" +
	"	if n, op, want := a - b, `-`, sub; n != want { ok=false; println(`int64`, a, op, b, `=`, n, `should be`, want); }\n" +

  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
  %1 = "tfl.mul"(%0, %arg2) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
  %2 = "tfl.add"(%arg0, %arg3) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

  --source_dir=third_party/tensorflow"

${generate} \
  --category=array \
  Identity \
  IdentityN \
  ZerosLike \
  Shape \
  ExpandDims \
  OnesLike

${generate} \
  --category=math \
  Mul \
  Conj \
  AddV2 \
  MatMul \
  Neg \
  Sum \
  Sub \
  Div \
  DivNoNan \
  Exp \
  Sqrt \
  SqrtGrad \
  Log1p

${generate} \
  --category=nn \

  %mul = tf.Mul %input, %three : (tensor<*xf32>, tensor<f32>) -> tensor<*xf32>

  // Only control flow v2 is supported in TF dialect.
  // The tf.If operation takes three functions that accept the same
  // arguments: the condition returns a bool and the two branches must return
  // the same type, which is also the return of the tf.If.
  %value = "tf.If”(%added, %mul)