285714285,"touches":1,"min_t":1266965732,"max_t":1266965732,"mean_t":1266965732},{"name":"control-clip-expected.txt","kids":[],"cl_weight":0.041666666666666664,"touches":1,"min_t":1244593336,"max_t":1244593336,"mean_t":1244593336},{"name":"control-clip-expected.png","kids":[],"cl_weight":0.044727967825377454,"touches":3,"min_t":1228781586,"max_t":1244593336,"mean_t":1236526846},{"name":"control-clip-expected.checksum","kids":[],"cl_weight":0.044727967825377454,"touches":3,"min_t":1228781586,"max...

}

.dlist dt code {
	color: var(--text-color);
	font-size: 1em;
	font-weight: bold;
}

.dlist p {
	margin-bottom: 0.625rem;
}

.sr-only {
	border: 0;
	clip: rect(0, 0, 0, 0);
	height: 1px;
	margin: -1px;
	overflow: hidden;
	padding: 0;
	position: absolute;
	width: 1px;
}

/* Layout */
.main-content>.appendix,
.main-content>.book,

ky;top:0;z-index:1020}}.sr-only{position:absolute;width:1px;height:1px;padding:0;overflow:hidden;clip:rect(0,0,0,0);white-space:nowrap;-webkit-clip-path:inset(50%);clip-path:inset(50%);border:0}.sr-only-focusable:active,.sr-only-focusable:focus{position:static;width:auto;height:auto;overflow:visible;clip:auto;white-space:normal;-webkit-clip-path:none;clip-path:none}.w-25{width:25%!important}.w-50{width:50%!important}.w-75{width:75%!important}.w-100{width:100%!important}.h-25{height:25%!important...

	if len(mainModuleMatches) > 0 && len(results) == 0 && modOnly == nil && errors.Is(err, fs.ErrNotExist) {
		return nil, nil, &QueryMatchesMainModulesError{
			Pattern: pattern,
			Query:   query,
		}
	}
	return slices.Clip(results), modOnly, err
}

// modulePrefixesExcludingTarget returns all prefixes of path that may plausibly
// exist as a module, excluding targetPrefix but otherwise including path

				"application/vnd.fdf",
				"application/vnd.fdsn.mseed",
				"application/vnd.fdsn.seed",
				"application/vnd.ffsns",
				"application/vnd.fints",
				"application/vnd.flographit",
				"application/vnd.fluxtime.clip",
				"application/vnd.font-fontforge-sfd",
				"application/vnd.framemaker",
				"application/vnd.frogans.fnc",
				"application/vnd.frogans.ltf",
				"application/vnd.fsc.weblaunch",

		var extra []string
		for _, path := range absTests {
			if strings.Contains(path, "$") {
				continue
			}
			path = vol + path
			extra = append(extra, path)
		}
		tests = append(slices.Clip(tests), extra...)
	}

	err = os.Chdir(absTestDirs[0])
	if err != nil {
		t.Fatal("chdir failed: ", err)
	}

	for _, path := range tests {
		path = strings.ReplaceAll(path, "$", root)

t&&b(t.mode,"hover")&&Yt(t.toggle.$el,this.$el)&&t},transitionTo:function(t,e){var i=this,n=this.dropbar,r=Wt(n)?ci(n):0;return Ve(e=r<t&&e,"clip","rect(0,"+e.offsetWidth+"px,"+r+"px,0)"),ci(n,r),Ze.cancel([e,n]),se.all([Ze.start(n,{height:t},this.duration),Ze.start(e,{clip:"rect(0,"+e.offsetWidth+"px,"+t+"px,0)"},this.duration)]).catch(et).then(function(){Ve(e,{clip:""}),i.$update(n)})},getDropdown:function(t){return this.$getComponent(t,"drop")||this.$getComponent(t,"dropdown")}}},lr={mixins:[sr],a...

sticky;\n    top: 0;\n    z-index: 1020;\n  }\n}\n\n.sr-only {\n  position: absolute;\n  width: 1px;\n  height: 1px;\n  padding: 0;\n  overflow: hidden;\n  clip: rect(0, 0, 0, 0);\n  white-space: nowrap;\n  border: 0;\n}\n\n.sr-only-focusable:active, .sr-only-focusable:focus {\n  position: static;\n  width: auto;\n  height: auto;\n  overflow: visible;\n  clip: auto;\n  white-space: normal;\n}\n\n.shadow-sm {\n  box-shadow: 0 0.125rem 0.25rem rgba(0, 0, 0, 0.075) !important;\n}\n\n.shadow {\n  box-shadow:...

// The caller must not modify the returned list, but may safely append to it
// and may rely on it not to be modified.
func (mg *ModuleGraph) BuildList() []module.Version {
	mg.buildListOnce.Do(func() {
		mg.buildList = slices.Clip(mg.g.BuildList())
	})
	return mg.buildList
}

func (mg *ModuleGraph) findError() error {
	errStack := mg.g.FindPath(func(m module.Version) bool {
		_, err := mg.loadCache.Get(m)

    Res<TF_Float32Tensor, [{The final quantization range minimum, used to clip input values before scaling
and rounding them to quantized values.
If the `axis` attribute is specified, this will be a 1-D tensor whose size
matches the `axis` dimension of the input and output tensors.}]>:$output_min,
    Res<TF_Float32Tensor, [{The final quantization range maximum, used to clip input values before scaling
and rounding them to quantized values.