":1,"min_t":1316289444,"max_t":1316289444,"mean_t":1316289444},{"name":"transport.go","kids":[],"cl_weight":0.1,"touches":1,"min_t":1316289444,"max_t":1316289444,"mean_t":1316289444}],"cl_weight":0.9999999999999999,"touches":1,"min_t":1316289444,"max_t":1316289444,"mean_t":1316289444},{"name":"draw","kids":[{"name":"Makefile","kids":[],"cl_weight":1,"touches":1,"min_t":1258062920,"max_t":1258062920,"mean_t":1258062920}],"cl_weight":1,"touches":1,"min_t":1258062920,"max_t":1258062920,"mean_t":125...

type codeNode struct {
	Name     string      `json:"name"`
	Kids     []*codeNode `json:"kids"`
	CLWeight float64     `json:"cl_weight"`
	Touches  int         `json:"touches"`
	MinT     int64       `json:"min_t"`
	MaxT     int64       `json:"max_t"`
	MeanT    int64       `json:"mean_t"`
}

var codeJSON []byte
var codeStruct codeResponse

func codeInit() {
	f, err := os.Open("testdata/code.json.gz")
	if err != nil {
		panic(err)
	}

// CHECK: %[[CUSTOM_AGGREGATOR_0:.*]], %[[MIN_O:.*]], %[[MAX_O:.*]], %[[HISTOGRAM_0:.*]] = "tf.CustomAggregator"
// CKECK-SAME: <{calibration_method = 5 : i32, id = "0", num_bins = 32 : i32, max_percentile = 0.000000e+00 : f32, min_percentile = 0.000000e+00 : f32}> : (tensor<1x3x4x3xf32>) -> (tensor<1x3x4x3xf32>, tensor<f32>, tensor<f32>, tensor<512xi64>)
// CHECK: %[[CUSTOM_AGGREGATOR_1:.*]], %[[MIN_1:.*]], %[[MAX_1:.*]], %[[HISTOGRAM_1:.*]] = "tf.CustomAggregator"

// CHECK: %[[CUSTOM_AGGREGATOR_0:.*]], %[[MIN_O:.*]], %[[MAX_O:.*]], %[[HISTOGRAM_0:.*]] = "tf.CustomAggregator"
// CKECK-SAME: <{calibration_method = 5 : i32, id = "skipping_id", num_bins = 32 : i32, max_percentile = 0.000000e+00 : f32, min_percentile = 0.000000e+00 : f32}> : (tensor<1x3x4x3xf32>) -> (tensor<1x3x4x3xf32>, tensor<f32>, tensor<f32>, tensor<512xi64>)
// CHECK: %[[CUSTOM_AGGREGATOR_1:.*]], %[[MIN_1:.*]], %[[MAX_1:.*]], %[[HISTOGRAM_1:.*]] = "tf.CustomAggregator"

	var t []*Value
	if total <= len(c.valstorage) {
		t = c.valstorage[:total]
		max_b = c
		totalBeforeMax = total - len(c.Values)
		copy(t[totalBeforeMax:], c.Values)
	} else if total <= cap(max_b.Values) { // in place, somewhere
		t = max_b.Values[0:total]
		copy(t[totalBeforeMax:], max_b.Values)
	} else {
		t = make([]*Value, total)
		max_b = nil
	}

	// copy the values
	copyTo := 0

  %2 = stablehlo.maximum %1, %0 : tensor<1x3x2x4xf32>
  return %2 : tensor<1x3x2x4xf32>
}
// CHECK: %[[TRANSPOSE_0:.+]] = stablehlo.transpose
// CHECK: %[[MAX_0:.+]] = stablehlo.maximum %[[TRANSPOSE_0]], {{.*}}
// CHECK: return %[[MAX_0]]

// -----

// [No change] Tests that the activation transpose of `stablehlo.maximum` whose
// rank is not 4 is not deferred.

  const int min_T = std::numeric_limits<T>::min();
  const int max_T = std::numeric_limits<T>::max();
  const float max_float = std::numeric_limits<float>::max();

  const float scale_factor_from_min_side =
      (min_T * min_range > 0) ? min_T / min_range : max_float;
  const float scale_factor_from_max_side =
      (max_T * max_range > 0) ? max_T / max_range : max_float;

  -Z int
    	an int that defaults to zero
  -ZP0 value
    	a flag whose String method panics when it is zero
  -ZP1 value
    	a flag whose String method panics when it is zero
  -maxT timeout
    	set timeout for dial

panic calling String method on zero flag_test.zeroPanicker for flag ZP0: panic!
panic calling String method on zero flag_test.zeroPanicker for flag ZP1: panic!
`

 *                aborting test runs, added CU_FAIL and CU_PASS macros. (JDS)
 *
 *  07-May-2005   Added CU_ prefix to remaining CUnit defines (BOOL, TRUE, 
 *                FALSE, MAX_...).  Added CU_UNREFERENCED_PARAMETER() define. (JDS)
 */

/** @file
 * Basic CUnit include file for user and system code.
 * Defines macros for assertions for use in user test cases.

			// 4.8.2 also says "[for non-interleaved data], the MCU is defined to be
			// one data unit". Similarly, section A.1.1 explains that it is the ratio
			// of H_i to max_j(H_j) that matters, and similarly for V. For grayscale
			// images, H_1 is the maximum H_j for all components j, so that ratio is
			// always 1. The component's (h, v) is effectively always (1, 1): even if