let summary = "Legalize StableHLO custom call ops where the call target is 'stablehlo.composite' to composite ops.";
  let dependentDialects = ["mlir::stablehlo::StablehloDialect"];
}

def UnfoldSplatConstantPass : Pass<"unfold-splat-constant-pass", "ModuleOp"> {
  let summary = "Replaces a splat constant tensor with a BroadcastInDim op.";
  let constructor = "mlir::odml::CreateUnfoldSplatConstantPass()";
}

#define FUNC3(a, b, c, d, e) \
	MOVL	b, SI; \
	ORL	c, SI; \
	ANDL	d, SI; \
	MOVL	b, DI; \
	ANDL	c, DI; \
	ORL	SI, DI

#define FUNC4 FUNC2

#define MIX(a, b, c, d, e, const) \
	ROLL	$30, b; \
	ADDL	DI, e; \
	MOVL	a, SI; \
	ROLL	$5, SI; \
	LEAL	const(e)(SI*1), e

#define ROUND1(a, b, c, d, e, index) \
	LOAD(index, e); \
	FUNC1(a, b, c, d, e); \
	MIX(a, b, c, d, e, 0x5A827999)

  // By default we freeze all variables and disallow mutable variables. When
  // 'enable_tflite_variables' is true then we allow mutable variable only.
  bool disable_variable_freezing = false;
  // Whether to unfold large splat constant tensors and replace them with
  // fill operation.
  bool unfold_large_splat_constant = false;
  // Whether to run the `GuaranteeAllFuncsOneUsePass` to ensure each function
  // has a single use.

element[upperSide];\n}\n","import getScroll from './getScroll';\n\n/*\n * Sum or subtract the element scroll values (left and top) from a given rect object\n * @method\n * @memberof Popper.Utils\n * @param {Object} rect - Rect object you want to change\n * @param {HTMLElement} element - The element from the function reads the scroll values\n * @param {Boolean} subtract - set to true if you want to subtract the scroll values\n * @return {Object} rect - The modifier rect object\n */\nexport default function includeScroll(rect,...

                                PatternRewriter& rewriter) const override;
};

#define GEN_PASS_DEF_UNROLLBATCHMATMULPASS
#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc"

// Unrolls a BatchMatMul on the batch dimension. We need to slice each batch out
// of the inputs, matmul them individually, then stack them all back together at
// the end.
struct UnrollBatchMatMulPass

 * This API does not try to cover all the requirements out there, just the basic ones, and is intentionally simple.
 * If plugin or extension needs anything more complex feature wise (i.e. HTTP range support or alike) it should
 * probably roll its own.
 * <p>
 * This implementation is backed by Maven Resolver API, supported protocols and transport selection depends on it. If
 * resolver preference regarding transport is altered, it will affect this service as well.
 *

	XORQ	$0xffff, AX
	JNE	diff64

	ADDQ	$64, SI
	ADDQ	$64, DI
	SUBQ	$64, R8
	CMPQ	R8, $64
	JBE	loop
	JMP	big_loop
#endif

	// Compare 64-bytes per loop iteration.
	// Loop is unrolled and uses AVX2.
big_loop_avx2:
	VMOVDQU	(SI), Y2
	VMOVDQU	(DI), Y3
	VMOVDQU	32(SI), Y4
	VMOVDQU	32(DI), Y5
	VPCMPEQB Y2, Y3, Y0
	VPMOVMSKB Y0, AX
	XORL	$0xffffffff, AX
	JNE	diff32_avx2

        given:
        fillArea()

        when:
        progressArea.setVisible(false)
        redraw()

        then:
        0 * ansi._
    }

    def "doesn't scroll the area when visibility is set to false"() {
        given:
        fillArea()
        def absoluteDeltaRow = 2

        when:
        redraw()
        progressArea.setVisible(false)

				})
			}

			istioctl.NewOrFail(t, t, istioctl.Config{}).InvokeOrFail(t, []string{
				"waypoint",
				"apply",
				"--namespace",
				nsConfig.Name(),
				"--name",
				"w3",
				"--enroll-namespace",
				"true",
				"--wait",
			})
			nameSet = append(nameSet, "w3")

			output, _ := istioctl.NewOrFail(t, t, istioctl.Config{}).InvokeOrFail(t, []string{
				"waypoint",
				"list",

// count value. The length of out must be greater than or equal to the length
// of in.
// counterCryptASM implements counterCrypt which then allows the loop to
// be unrolled and optimized.
func (g *gcmAsm) counterCrypt(out, in []byte, counter *[gcmBlockSize]byte) {
	counterCryptASM(int(g.cipher.l)/4-1, out, in, counter, &g.cipher.enc[0])

}