// RUN: tf-tfrt-opt -verify-diagnostics -split-input-file -tfrt-fuse-tpu-compile-and-execute-ops -canonicalize %s | FileCheck %s --dump-input=fail --dump-input-filter=all

module attributes {tf_saved_model.semantics} {

// Test fusing _TPUCompileMlirOp and TPUExecuteOp into TPUCompileMlirAndExecuteOp.

// CHECK-LABEL: func private @test_fuse_tpu_ops
func.func private @test_fuse_tpu_ops(%arg0: tensor<*xi32>, %arg1: tensor<*x!tf_type.resource>) -> tensor<*xi32> {

c=this[0];if(c)return r.event.trigger(a,b,c,!0)}}),r.each("blur focus focusin focusout resize scroll click dblclick mousedown mouseup mousemove mouseover mouseout mouseenter mouseleave change select submit keydown keypress keyup contextmenu".split(" "),function(a,b){r.fn[b]=function(a,c){return arguments.length>0?this.on(b,null,a,c):this.trigger(b)}}),r.fn.extend({hover:function(a,b){return this.mouseenter(a).mouseleave(b||a)}}),o.focusin="onfocusin"in a,o.focusin||r.each({focus:"focusin",blur:"focusout"},function(a,b){var...

			simple = bb
			post = other
			break
		}
	}
	if simple == nil || len(post.Preds) != 2 || post == dom {
		return false
	}

	// We've found our diamond CFG of blocks.
	// Now decide if fusing 'simple' into dom+post
	// looks profitable.

	// Check that there are Phis, and that all of them
	// can be safely rewritten to CondSelect.
	hasphis := false
	for _, v := range post.Values {

            data_format='NHWC',
            name='sample/conv',
        )
        if bias_fn is not None:
          out = nn_ops.bias_add(out, self.bias)
        if has_batch_norm:
          # Fusing is supported for non-training case.
          out, _, _, _, _, _ = nn_ops.fused_batch_norm_v3(
              out, scale, offset, mean, variance, is_training=False
          )
        if activation_fn is not None:

    auto users = op.getResult().getUsers();
    quantizing_ops.append(users.begin(), users.end());

    bool changed = false;
    // Rewrite the floating-point ops to the quantized version, by fusing
    // preceding dequantize ops and succeding quantize ops.
    for (Operation* quantizing_op : quantizing_ops) {
      // If it is requantize op, we shouldn't rewrite this op.

E.Event,n,{type:e,isSimulated:!0});E.event.trigger(r,null,t)}}),E.fn.extend({trigger:function(e,t){return this.each(function(){E.event.trigger(e,t,this)})},triggerHandler:function(e,t){var n=this[0];if(n)return E.event.trigger(e,t,n,!0)}}),v.focusin||E.each({focus:"focusin",blur:"focusout"},function(n,r){var i=function(e){E.event.simulate(r,e.target,E.event.fix(e))};E.event.special[r]={setup:function(){var e=this.ownerDocument||this.document||this,t=Y.access(e,r);t||e.addEventListener(n,i,!0),Y.access(e...

E.Event,n,{type:e,isSimulated:!0});E.event.trigger(r,null,t)}}),E.fn.extend({trigger:function(e,t){return this.each(function(){E.event.trigger(e,t,this)})},triggerHandler:function(e,t){var n=this[0];if(n)return E.event.trigger(e,t,n,!0)}}),v.focusin||E.each({focus:"focusin",blur:"focusout"},function(n,r){var i=function(e){E.event.simulate(r,e.target,E.event.fix(e))};E.event.special[r]={setup:function(){var e=this.ownerDocument||this.document||this,t=Y.access(e,r);t||e.addEventListener(n,i,!0),Y.access(e...

            padding='SAME',
            data_format='NHWC',
        )
        if has_bias:
          out = nn_ops.bias_add(out, self.bias)
        if has_batch_norm:
          # Fusing is supported for non-training case.
          out, _, _, _, _, _ = nn_ops.fused_batch_norm_v3(
              out, scale, offset, mean, variance, is_training=False
          )
        if activation_fn is not None:

      // Found an operand that isn't scheduled yet, return true.
      return true;
    }
  }
  return false;
}

// Sorts the operations in the provided range to enforce dominance.
// This is useful after fusing / reorganizing Operations in a block and later
// needing to readjust the ordering to ensure dominance.
LogicalResult SortTopologically(Block::iterator begin, Block::iterator end) {
  Block* block = begin->getBlock();

# Architecture of Istiod

This document describes the high level architecture of the Istio control plane, Istiod.
Istiod is structured as a modular monolith, housing a wide range of functionality from certificate signing, proxy configuration (XDS), traditional Kubernetes controllers, and more.

## Proxy Configuration