requires all optimizer variables to be created at the first
        `apply_gradients()` or `minimize()` call. If your workflow calls
        optimizer to update different parts of model in multiple stages,
        please call `optimizer.build(model.trainable_variables)` before the
        training loop.
    *   **Performance regression on `ParameterServerStrategy`.** This could be

VSLDOI $8, T2, T1, T1 // VSLDB $8, T2, T1, T1 VADDCUQ T0, RED1, CAR1 // VACCQ T0, RED1, CAR1 VADDUQM T0, RED1, T0 // VAQ T0, RED1, T0 VADDECUQ T1, RED2, CAR1, CAR2 // VACCCQ T1, RED2, CAR1, CAR2 VADDEUQM T1, RED2, CAR1, T1 // VACQ T1, RED2, CAR1, T1 VADDUQM T2, CAR2, T2 // VAQ T2, CAR2, T2 // ---------- VSUBCUQ T0, PL, CAR1 // VSCBIQ PL, T0, CAR1 VSUBUQM T0, PL, TT0 // VSQ PL, T0, TT0 VSUBECUQ T1, PH, CAR1, CAR2 // VSBCBIQ T1, PH, CAR1, CAR2 VSUBEUQM T1, PH, CAR1, TT1 // VSBIQ T1, PH, CAR1, TT1 VSUBEUQM...

				"text/sgml",
				"text/t140",
				"text/tab-separated-values",
				"text/troff",
				"text/ulpfec",
				"text/uri-list",
				"text/vnd.abc",
				"text/vnd.curl",
				"text/vnd.curl.dcurl",
				"text/vnd.curl.scurl",
				"text/vnd.curl.mcurl",
				"text/vnd.dmclientscript",
				"text/vnd.esmertec.theme-descriptor",
				"text/vnd.fly",
				"text/vnd.fmi.flexstor",
				"text/vnd.graphviz",

		Context: context,
	})
}

// Save calls to C.xxx for later processing.
func (f *File) saveCall(call *ast.CallExpr, context astContext) {
	sel, ok := call.Fun.(*ast.SelectorExpr)
	if !ok {
		return
	}
	if l, ok := sel.X.(*ast.Ident); !ok || l.Name != "C" {
		return
	}
	c := &Call{Call: call, Deferred: context == ctxDefer}
	f.Calls = append(f.Calls, c)
}

and the matching call to <code>l.RUnlock</code> is synchronized before the return from call <i>n</i>+1 to <code>l.Lock</code>.
</p>

<p class="rule">
A successful call to <code>l.TryLock</code> (or <code>l.TryRLock</code>)
is equivalent to a call to <code>l.Lock</code> (or <code>l.RLock</code>).
An unsuccessful call has no synchronizing effect at all.
As far as the memory model is concerned,

	0x001d 00029 (x.go:4)	PCDATA	$0, $0
	0x001d 00029 (x.go:4)	PCDATA	$1, $0
	0x001d 00029 (x.go:4)	CALL	runtime.printlock(SB)
	0x0022 00034 (x.go:4)	MOVQ	$3, (SP)
	0x002a 00042 (x.go:4)	CALL	runtime.printint(SB)
	0x002f 00047 (x.go:4)	CALL	runtime.printnl(SB)
	0x0034 00052 (x.go:4)	CALL	runtime.printunlock(SB)
	0x0039 00057 (x.go:5)	MOVQ	8(SP), BP
	0x003e 00062 (x.go:5)	ADDQ	$16, SP
	0x0042 00066 (x.go:5)	RET

	SARL $1, (BX)                           // d13b
	SARL $1, (R11)                          // 41d13b
	SARL $1, DX                             // d1fa
	SARL $1, R11                            // 41d1fb
	SARL CL, (BX)                           // d33b
	SARL CL, (R11)                          // 41d33b
	SARL CL, DX                             // d3fa
	SARL CL, R11                            // 41d3fb

#
#   You will need the NVIDIA Container Toolkit for GPU testing:
#   https://github.com/NVIDIA/nvidia-container-toolkit
#
#   Note: if you interrupt a bazel command on docker (ctrl-c), you
#   will need to run `docker exec tf pkill bazel` to quit bazel.
#
#   Note: new files created from the container are owned by "root".
#   You can run e.g. `docker exec tf chown -R $(id -u):$(id -g) build_output`

# - we set GRADLE_RO_DEP_CACHE to '/opt/gradle-cache' if the folder exists.

curl -m 1 -s "http://169.254.169.254/latest/meta-data/instance-id"
IS_EC2_INSTANCE=$?
if [ $IS_EC2_INSTANCE -ne 0 ]; then
  echo "Not running on an EC2 instance, skipping the configuration"
  exit 0
fi

# TAG
EC2_INSTANCE_TYPE=$(curl -s "http://169.254.169.254/latest/meta-data/instance-type")

	JMP	label0+0	// JMP 66
	BEQ	R1, 2(PC)
	JAL	1(PC)	// CALL 1(PC)
	BEQ	R1, 2(PC)
	JAL	label0+0	// CALL 66

	//	LBRA addr
	//	{
	//		outcode(int($1), &nullgen, 0, &$2);
	//	}
	BEQ	R1, 2(PC)
	JMP	0(R1)	// JMP (R1)
	BEQ	R1, 2(PC)
	JMP	foo+0(SB)	// JMP foo(SB)
	BEQ	R1, 2(PC)
	JAL	0(R1)	// CALL (R1)
	BEQ	R1, 2(PC)
	JAL	foo+0(SB)	// CALL foo(SB)

//
// BEQ/BNE
//
//	LBRA rreg ',' rel