{gvr("extensions", "v1beta1", "deployments"), "", gvk("extensions", "v1beta1", "Deployment")},
		// deployments/scale (omitted for apps/v1alpha1)
		{gvr("apps", "v1", "deployments"), "scale", gvk("", "", "Scale")},
		{gvr("apps", "v1beta1", "deployments"), "scale", gvk("", "", "Scale")},
		{gvr("extensions", "v1beta1", "deployments"), "scale", gvk("", "", "Scale")},
		// deployments/status (omitted for apps/v1alpha1)

-	  if (cp[2 * nhere - 1] < usrc[nhere -1])
+	  if (cp[2 * nhere - 1] < usrc[nhere - 1])
 	    {
 	      cp += 2 * nhere;
 	      continue;
diff --git a/locale/xlocale.h b/locale/xlocale.h
index 98c080b..843bd45 100644
--- a/locale/xlocale.h
+++ b/locale/xlocale.h
@@ -20,6 +20,9 @@
 #ifndef _XLOCALE_H
 #define _XLOCALE_H	1
 
+#ifndef _BITS_TYPES___LOCALE_T_H
+#define _BITS_TYPES___LOCALE_T_H 1
+

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/autoscaling/v2";

// ContainerResourceMetricSource indicates how to scale on a resource metric known to
// Kubernetes, as specified in requests and limits, describing each pod in the
// current scale target (e.g. CPU or memory).  The values will be averaged
// together before being compared to the target.  Such metrics are built in to

// AUTO-GENERATED FUNCTIONS START HERE. DO NOT EDIT.
var map_ContainerResourceMetricSource = map[string]string{

namespace mlir::quant::stablehlo {

// Checks whether an op is connected with a quantized composite function. If
// not, the same-scale op will not be quantized. This decision is based on the
// current assumption that the performance gain of the same-scale op itself
// could not beat the overhead of the quantize and dequantize routines need to
// be added around that op. When the assumption changes, this policy might

		value  int64
		max    int64
		result int64
		scale  int32
	}{
		{100, 10, 1, 2},
		{100, 10, 1, 2},
		{100, 100, 1, 1},
		{1, 10, 1, 0},
	} {
		r, s := removeInt64Factors(test.value, test.max)
		if r != test.result {
			t.Errorf("%v: unexpected result: %d", test, r)
		}
		if s != test.scale {
			t.Errorf("%v: unexpected scale: %d", test, s)
		}
	}
}

tfr.func @tf__my_requantize(%input: !tfr.tensor) -> !tfr.tensor {
  %raw_data = tfr.quant_raw_data(%input) : (!tfr.tensor) -> !tfr.tensor
  %scale, %zp = tfr.quant_qparam(%input) : (!tfr.tensor) -> (!tfr.tensor, !tfr.tensor)
  %result = tfr.call @tf__requantize(%raw_data, %scale, %zp) : (!tfr.tensor, !tfr.tensor, !tfr.tensor) -> !tfr.tensor
  tfr.return %result : !tfr.tensor
}

// CHECK-LABEL: @tf__intermediate

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/autoscaling/v2beta1";

// ContainerResourceMetricSource indicates how to scale on a resource metric known to
// Kubernetes, as specified in requests and limits, describing each pod in the
// current scale target (e.g. CPU or memory).  The values will be averaged
// together before being compared to the target.  Such metrics are built in to

	// to get seconds (96 bit scaled result)
	MOVW	$0x89705f41, R3		// 2**61 * 10**-9
	MULLU	R1,R3,(R6,R5)		// R5:R6:R7 = R1:R2 * R3
	MOVW	$0,R7
	MULALU	R2,R3,(R7,R6)

	// unscale by discarding low 32 bits, shifting the rest by 29
	MOVW	R6>>29,R6		// R6:R7 = (R5:R6:R7 >> 61)
	ORR	R7<<3,R6
	MOVW	R7>>29,R7

	// subtract (10**9 * sec) from nsec to get nanosecond remainder

    x_shape = [label_to_size.get(x_label) for x_label in x_labels]
    y_shape = [label_to_size.get(y_label) for y_label in y_labels]
    bias_shape = None
    if use_bias:
      bias_shape = [label_to_size.get(out_label) for out_label in out_labels]
      bias_shape = bias_shape[-1:]
    contracting_dims = set()

    x_signature = list(x_shape)
    y_signature = list(y_shape)