'can be specified as "x.y" or "compute_xy" to include both virtual and'
        ' binary GPU code, or as "sm_xy" to only include the binary '
        'code.\nPlease note that each additional compute capability '
        'significantly increases your build time and binary size, and that '
        'TensorFlow only supports compute capabilities >= 3.5 [Default is: '

 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 * 1. Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright

# Debug config
build:dbg -c dbg
# Only include debug info for files under tensorflow/, excluding kernels, to
# reduce the size of the debug info in the binary. This is because if the debug
# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:

	// access.
	//
	// However, the value of px_proto_oe is 0, so we can use
	// encoding/binary helpers to write the bytes without worrying
	// about the ordering.
	binary.BigEndian.PutUint32(sa.raw[2:6], px_proto_oe)
	// This field is deliberately big-endian, unlike the previous
	// one. The kernel expects SID to be in network byte order.
	binary.BigEndian.PutUint16(sa.raw[6:8], sa.SID)
	copy(sa.raw[8:14], sa.Remote)

	}
}

// RunKubelet is responsible for setting up and running a kubelet.  It is used in three different applications:
//
//	1 Integration tests
//	2 Kubelet binary
//	3 Standalone 'kubernetes' binary
//
// Eventually, #2 will be replaced with instances of #3
func RunKubelet(ctx context.Context, kubeServer *options.KubeletServer, kubeDeps *kubelet.Dependencies, runOnce bool) error {

//	             ::= sP <template-arg>* E
//	             ::= sp <expression>
//	             ::= fl <binary operator-name> <expression>
//	             ::= fr <binary operator-name> <expression>
//	             ::= fL <binary operator-name> <expression> <expression>
//	             ::= fR <binary operator-name> <expression> <expression>
//	             ::= tw <expression>
//	             ::= tr

    /**
     * For `=` and compound access like `+=`, `-=`, `*=`, `/=`, `%=`, the LHS of the binary expression is not a complete call. Hence we
     * find the containing binary expression and resolve that instead.
     *
     * However, if, say, `+=` resolves to `plusAssign`, then the LHS is self-contained. In this case we do not return the containing binary
     * expression so that the FIR element corresponding to the LHS is used directly.
     */

	{"%#.4x", 123.0, "0x1.ec00p+06"},
	{"%#.4g", 123.0, "123.0"},
	{"%#.4g", 123000.0, "1.230e+05"},
	{"%#9.4g", 1.0, "    1.000"},
	// The sharp flag has no effect for binary float format.
	{"%#b", 1.0, "4503599627370496p-52"},
	// Precision has no effect for binary float format.
	{"%.4b", float32(1.0), "8388608p-23"},
	{"%.4b", -1.0, "-4503599627370496p-52"},
	// Test correct f.intbuf boundary checks.

The plugin declares a consumable `binaryTestResultsElements` configuration that represents the binary test results of the `test` task.
In the aggregation project's build file, we declare the `testReportData` configuration and depend on all of the projects that we want to aggregate the results from. Gradle will automatically select the binary test result variant from each of the subprojects instead of the project's jar file.

	"cmd/compile/internal/logopt"
	"cmd/compile/internal/reflectdata"
	"cmd/compile/internal/types"
	"cmd/internal/obj"
	"cmd/internal/obj/s390x"
	"cmd/internal/objabi"
	"cmd/internal/src"
	"encoding/binary"
	"fmt"
	"internal/buildcfg"
	"io"
	"math"
	"math/bits"
	"os"
	"path/filepath"
	"strings"
)

type deadValueChoice bool

const (
	leaveDeadValues  deadValueChoice = false