tpp.Param.goString(indent+2, "Param: "))
}

// Cast is a type cast.
type Cast struct {
	To AST
}

func (c *Cast) print(ps *printState) {
	ps.writeString("operator ")
	ps.print(c.To)
}

func (c *Cast) Traverse(fn func(AST) bool) {
	if fn(c) {
		c.To.Traverse(fn)
	}
}

func (c *Cast) Copy(fn func(AST) AST, skip func(AST) bool) AST {
	if skip(c) {

    // CHECK-SAME: (tensor<*xf32>) -> tensor<*xi8>
    // CHECK: %[[TENSOR_CAST:.*]] = tensor.cast %[[CAST_RESULT_2]] : tensor<*xi8> to tensor<?x?x?x?xi8>
    %2 = tensor.cast %28 : tensor<*xi8> to tensor<?x?x?x?xi8>
    // CHECK: %[[CAST_RESULT_0:.*]] = "tf.Cast"(%arg0)
    // CHECK-SAME: (tensor<16x194x199x4xf32>) -> tensor<16x194x199x4xui8>
    // CHECK: %[[CAST_RESULT_1:.*]] = "tf.Cast"(%arg0)

// CHECK-LABEL: Tanh
// CHECK:  "tfl.tanh"(%arg0) : (tensor<1xf32>) -> tensor<1xf32>
}

func.func @cast(%arg0: tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32> {
  %0 = "tf.Cast"(%arg0) : (tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32>
  func.return %0 : tensor<1x2x2x5xf32>

  // CHECK-LABEL: cast
  // CHECK: "tfl.cast"(%arg0) : (tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32>
}

    if (!mlir::cast<ShapedType>(conv_op.getRhs().getType()).hasStaticShape()) {
      return false;
    }
    if (!mlir::cast<ShapedType>(conv_op.getLhs().getType()).hasStaticShape() &&
        !mlir::cast<ShapedType>(conv_op.getType()).hasStaticShape()) {
      auto dnums = conv_op.getDimensionNumbers();
      auto lhs_type = mlir::cast<ShapedType>(conv_op.getLhs().getType());

  auto input_args_have_static_shape = [&]() -> bool {
    return mlir::cast<TensorType>(input_tensor.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(kernel_tensor.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(window_strides.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(padding.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(lhs_dilation.getType()).hasStaticShape() &&

          CPred<"$_op.getOperand(0).getType().cast<ShapedType>().getRank() <= 1">,
          CPred<"$_op.getOperand(0).getType().cast<ShapedType>().getRank() == 2 && !$_op.getOperand(0).getType().cast<ShapedType>().hasStaticShape()">,
          CPred<"$_op.getOperand(0).getType().cast<ShapedType>().getRank() == 2 && $_op.getOperand(0).getType().cast<ShapedType>().getShape()[1] <= 4">]>>]> {

  %0 = "tf.Cast"(%arg0) {Truncate = false} : (tensor<8x16x32x64xf32>) -> tensor<8x16x32x64xi32>
  %1 = "tf.Cast"(%arg0) {Truncate = true} : (tensor<8x16x32x64xf32>) -> tensor<8x16x32x64xi32>
  func.return %0, %1: tensor<8x16x32x64xi32>, tensor<8x16x32x64xi32>

  // CHECK: %0 = "tf.Cast"(%arg0) <{Truncate = false}> : (tensor<8x16x32x64xf32>) -> tensor<8x16x32x64xi32>

			v = AppendValidation(v, fmt.Errorf("invalid gateway name: %q", name))
		}
		value, ok := cfg.Spec.(*networking.Gateway)
		if !ok {
			v = AppendValidation(v, fmt.Errorf("cannot cast to gateway: %#v", cfg.Spec))
			return v.Unwrap()
		}

		if len(value.Servers) == 0 {
			v = AppendValidation(v, fmt.Errorf("gateway must have at least one server"))
		} else {

github.com/spf13/afero v1.11.0/go.mod h1:GH9Y3pIexgf1MTIWtNGyogA5MwRIDXGUr+hbWNoBjkY=
github.com/spf13/cast v1.3.0/go.mod h1:Qx5cxh0v+4UWYiBimWS+eyWzqEqokIECu5etghLkUJE=
github.com/spf13/cast v1.3.1/go.mod h1:Qx5cxh0v+4UWYiBimWS+eyWzqEqokIECu5etghLkUJE=
github.com/spf13/cast v1.6.0 h1:GEiTHELF+vaR5dhz3VqZfFSzZjYbgeKDpBxQVS4GYJ0=
github.com/spf13/cast v1.6.0/go.mod h1:ancEpBxwJDODSW/UG4rDrAqiKolqNNh2DX3mk86cAdo=

func.func @testReshape(%arg0: tensor<10x10xf32>) -> tensor<?x?xf32> {
  %shape1 = arith.constant dense<[100]> : tensor<1xi32>
  // expected-error @+1 {{requires 'output' type 'tensor<?x?xf32>' to be cast compatible with expected type 'tensor<100xf32>'}}
  %r1 = "tf.Reshape" (%arg0, %shape1) : (tensor<10x10xf32>, tensor<1xi32>) -> tensor<?x?xf32>
  func.return %r1 : tensor<?x?xf32>
}

// -----