// RUN: tf-opt -tfl-split-merged-operands %s | FileCheck %s

func.func @testSingleLstm(%arg0: tensor<4x4xf32>, %arg1: tensor<4xf32>, %arg2: tensor<4x4x4xf32>) -> tensor<4x4x4xf32> {
  // CHECK-LABEL: testSingleLstm
  // CHECK-DAG:  %[[CST_0:.*]] = "tfl.pseudo_const"() <{value = dense<0.000000e+00> : tensor<4x4xf32>}> : () -> tensor<4x4xf32>
  // CHECK-DAG:  %[[CST_1:.*]] = "tfl.pseudo_const"() <{value = dense<0.000000e+00> : tensor<4x4xf32>}> : () -> tensor<4x4xf32>

	}
	return res
}

func TestErroneous(t *testing.T) {

	type errtest struct {
		pseudo   string
		operands string
		expected string
	}

	nonRuntimeTests := []errtest{
		{"TEXT", "", "expect two or three operands for TEXT"},
		{"TEXT", "%", "expect two or three operands for TEXT"},
		{"TEXT", "1, 1", "TEXT symbol \"<erroneous symbol>\" must be a symbol(SB)"},

    private static Collection<?> toList(Object[] operands) {
        return singleCollection(operands) ? (Collection<?>) operands[0] : Arrays.asList(operands);
    }

    private static boolean singleCollection(Object[] operands) {
        return operands.length== 1 && operands[0] instanceof Collection;
    }

    private enum Subject {
        all(true, true),
        stackoverflow(false, true),
        operations(true, false);

// TFL op interface for stateful operands.

def TFL_StatefulOp : OpInterface<"StatefulOpInterface"> {
  let description = [{
    Interface for ops that are stateful and need to identify stateful operands.

    Stateful operands correspond to TF's variables semantics. An op that has 1
    or more stateful operands is a stateful op.
  }];

  let methods = [
    InterfaceMethod<

        switch (opType) {
            case "any of":
                def operands = []
                collectOperands(value, operands)
                return "anyOf(${operands.join(', ')})"
            case "all of":
                def operands = []
                collectOperands(value, operands)
                return "allOf(${operands.join(', ')})"
            case "exclude group":

    return success();
  }

  // Returns directly if any of the operands is not an elements attributes.
  if (std::any_of(operands.begin(), operands.end(), [](Attribute attr) {
        return !attr || !mlir::isa<ElementsAttr>(attr);
      }))
    return failure();

  SmallVector<ElementsAttr, 4> inputs;
  inputs.reserve(operands.size());
  for (auto input : operands) {
    inputs.push_back(mlir::cast<ElementsAttr>(input));
  }

    llvm::SetVector<Value> operands;
    getUsedValuesDefinedAbove(island_op.getBody(), operands);

    SmallVector<Type, 16> func_operand_types;
    func_operand_types.reserve(operands.size());
    for (Value operand : operands)
      func_operand_types.push_back(operand.getType());

    // Function results are the yield operands
    SmallVector<Type, 16> func_result_types;

    TFE_Context* context, llvm::SmallVectorImpl<mlir::Attribute>* results) {
  if (!context) {
    VLOG(1) << "Can't evaluate with null context.";
    return mlir::failure();
  }
  // If any operand is nullptr returns true for a failure.
  // TODO(b/120678030): remove this constraint if we find operators can be
  // evaluated with some unknown operands.

  // core. j-th column holds the operands for j-th replica.
  llvm::SmallVector<llvm::SmallVector<Value, 4>, 4>
      operands_per_replica_per_core(num_cores_per_replica);

  // Collect all operands in the 2D matrix.
  for (auto operand : replicated_input.getInputs()) {
    Operation* pi = operand.getDefiningOp();
    for (unsigned core_id = 0; core_id < num_cores_per_replica; ++core_id) {

	// 2
	// 4
	// 8
	// 16
}

func ExampleFloat_Cmp() {
	inf := math.Inf(1)
	zero := 0.0

	operands := []float64{-inf, -1.2, -zero, 0, +1.2, +inf}

	fmt.Println("   x     y  cmp")
	fmt.Println("---------------")
	for _, x64 := range operands {
		x := big.NewFloat(x64)
		for _, y64 := range operands {
			y := big.NewFloat(y64)
			fmt.Printf("%4g  %4g  %3d\n", x, y, x.Cmp(y))
		}
		fmt.Println()
	}