package org.gradle.internal

import spock.lang.Specification

import static Cast.cast

class CastTest extends Specification {

    def "casting"() {
        given:
        def arg = "1"

        when:
        cast(Integer, arg)

        then:
        def e = thrown(ClassCastException)
        e.message == "Failed to cast object $arg of type ${arg.class.name} to target type ${Integer.name}"

        when:

// CHECK: %[[quant:.*]] = "tfr.cast"(%arg0) : (tensor<1x10xi8>) -> !tfr.tensor
// CHECK: %[[scale_cast:.*]] = "tfr.cast"(%[[scale]])
// CHECK: %[[zp_cast:.*]] = "tfr.cast"(%[[zp]])
// CHECK: %[[requant:.*]] = tfr.call @tf__requantize(%[[quant]], %[[scale_cast]], %[[zp_cast]])
// CHECK: %[[result:.*]] = "tfr.cast"(%[[requant]])
// CHECK-NOT: quant.uniform

    public static <T> Spec<T> satisfyAll() {
        return Cast.uncheckedCast(SATISFIES_ALL);
    }

    public static final Spec<Object> SATISFIES_NONE = new Spec<Object>() {
        @Override
        public boolean isSatisfiedBy(Object element) {
            return false;
        }
    };

    public static <T> Spec<T> satisfyNone() {
        return Cast.uncheckedCast(SATISFIES_NONE);
    }

  func.return
}

// CHECK-LABEL: func @cast_at_head_expanded
func.func @cast_at_head_expanded(%arg0: tensor<?xi32>) {
  // CHECK: "tf_device.cluster"
  // CHECK-NEXT: "tf.Cast"
  // CHECK-SAME: _xla_outside_compilation = ""
  "tf_device.cluster"() ({
    %1 = "tf.Cast"(%arg0) : (tensor<?xi32>) -> (tensor<?xi32>)
    "tf.B"(%1) {_xla_outside_compilation = "cluster1"} : (tensor<?xi32>) -> ()
    "tf.C"() : () -> ()
    tf_device.return

    // Check if the same-scale requirement is met.
    auto dq_arg_type = preceding_sc_op.getArg().getType().cast<TensorType>();
    auto qtype = dq_arg_type.getElementType().cast<QuantizedType>();
    auto q_result_type = sc_op.getType().cast<TensorType>();
    auto out_qtype = q_result_type.getElementType().cast<QuantizedType>();
    if (qtype != out_qtype) {
      avg_pool_op.emitError(

            MapProperty<Object, Object> asMapProperty = Cast.uncheckedNonnullCast(target);
            DefaultProvider<Map<Object, Object>> convention = new DefaultProvider<>(() -> Cast.uncheckedNonnullCast(mapping.getValue(_convention, _source)));
            asMapProperty.convention(convention);
        } else if (target instanceof HasMultipleValues) {
            HasMultipleValues<Object> asCollectionProperty = Cast.uncheckedNonnullCast(target);

// Attribute Constraint that checks if the attribute value is zero.
def ZeroIntAttr
  : AttrConstraint<CPred<"$_self.cast<::mlir::IntegerAttr>().getInt() == 0">>;

// Checks if the value has rank at most 'n'.
class HasRankAtLeast<int n> : Constraint<
    CPred<"$0.getType().cast<ShapedType>().hasRank() && "
          "$0.getType().cast<ShapedType>().getRank() >= " # n>>;

// Checks value is not produced by a TFL_Quant or

// Ensure cast with bfloat16 roundtrip exactly

func.func @main(tensor<4x5xbf16>) -> tensor<4x5xbf16> {
^bb0(%arg0: tensor<4x5xbf16>):
  // CHECK-LABEL: @main
  // CHECK:  (tensor<4x5xbf16>) -> tensor<4x5xf32>
  // CHECK-NEXT:  (tensor<4x5xf32>) -> tensor<4x5xbf16>
  %0 = "tfl.cast" (%arg0) : (tensor<4x5xbf16>) -> tensor<4x5xf32> loc("cast1")
  %1 = "tfl.cast" (%0) : (tensor<4x5xf32>) -> tensor<4x5xbf16> loc("cast2")

        %input_i32 = "tf.Cast"(%weight) : (tensor<1024x24x24x3xi8>) -> tensor<1024x24x24x3xi32>
        %output = "tf.Sub"(%input_i32, %zp) : (tensor<1024x24x24x3xi32>, tensor<i32>) -> tensor<1024x24x24x3xi32>
        %cast = "tf.Cast"(%output) : (tensor<1024x24x24x3xi32>) -> tensor<1024x24x24x3xf32>
        %mul = "tf.Mul"(%cast, %scale) : (tensor<1024x24x24x3xf32>, tensor<f32>) -> tensor<1024x24x24x3xf32>

// CHECK: %[[quant:.*]] = "tf.Cast"(%[[round]]) : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xi8>
// CHECK: %[[pad:.*]] = "tf.PadV2"(%[[quant]]
// CHECK: %[[xlaconv:.*]] = "tf.XlaConvV2"(%[[pad]]
// CHECK: %[[sub:.*]] = "tf.Sub"(%[[xlaconv]]
// CHECK: %[[cast:.*]] = "tf.Cast"(%[[sub]]) <{Truncate = false}> : (tensor<1x3x2x2xi32>) -> tensor<1x3x2x2xf32>
// CHECK: %[[dequant1:.*]] = "tf.Mul"(%[[cast]]
// CHECK: %[[relu:.*]] = "tf.Relu"(%[[dequant1]]