-	  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

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

    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)

// CHECK-NEXT:        scale: [ 0.021827 ],
// CHECK-NEXT:        zero_point: [ 151 ]
// CHECK-NEXT:      },
// CHECK-NEXT:      has_rank: true
// CHECK-NEXT:    }, {
// CHECK-NEXT:      shape: [ 32 ],
// CHECK-NEXT:      type: INT32,
// CHECK-NEXT:      buffer: 5,
// CHECK-NEXT:      name: "tfl.pseudo_qconst1",
// CHECK-NEXT:      quantization: {
// CHECK-NEXT:        scale: [ 0.000171 ],

1. [Standalone Deployment](#standalone-deployment)
2. [Distributed Deployment](#distributed-deployment)
3. [Cloud Scale Deployment](#cloud-scale-deployment)

## 1. Standalone Deployment

To host multiple tenants on a single machine, run one MinIO Server per tenant with a dedicated HTTPS port, configuration, and data directory.

    verbs:
    - create
  - apiGroups:
    - apps
    resources:
    - daemonsets
    - deployments
    - deployments/rollback
    - deployments/scale
    - replicasets
    - replicasets/scale
    - statefulsets
    - statefulsets/scale
    verbs:
    - create
    - delete
    - deletecollection
    - patch
    - update
  - apiGroups:
    - autoscaling
    resources: