// CHECK-NEXT:     [[PREFIX:%.*]] = "tf.Const"() <{value = dense<"restore_ariables"> : tensor<!tf_type.string>}> : () -> tensor<!tf_type.string>
// CHECK-NEXT:     [[SLICE:%.*]] = "tf.Const"() <{value = dense<""> : tensor<1x!tf_type.string>}> : () -> tensor<1x!tf_type.string>
// CHECK-NEXT:     [[NAME:%.*]] = "tf.Const"() <{value = dense<"y"> : tensor<1x!tf_type.string>}> : () -> tensor<1x!tf_type.string>

    StringRef calibration_data_dir,
    const std::vector<std::string>& aggregator_ops_to_ignore);

// Adds generated pass default constructors or options definitions.
#define GEN_PASS_DECL
// Adds generated pass registration functions.
#define GEN_PASS_REGISTRATION
#include "tensorflow/compiler/mlir/quantization/stablehlo/passes/passes.h.inc"

}  // namespace mlir::quant::stablehlo

// scanning.
//
// The second local is an abi.RegArgs value whose offset is also known to the
// runtime, so that a stack map for it can be constructed, since it contains
// pointers visible to the GC.
#define LOCAL_RETVALID 40
#define LOCAL_REGARGS 48

// The frame size of the functions below is
// 32 (args of callReflect) + 8 (bool + padding) + 392 (abi.RegArgs) = 432.

// makeFuncStub is the code half of the function returned by MakeFunc.

  %0 = stablehlo.constant dense<1.0> : tensor<4x3xf32>
  %1 = stablehlo.dot_general %arg0, %0, contracting_dims = [1] x [0], precision = [DEFAULT, DEFAULT] : (tensor<1x4xf32>, tensor<4x3xf32>) -> tensor<1x3xf32>
  return %1 : tensor<1x3xf32>
}
// CHECK: @main(%[[ARG_0:.+]]: tensor<1x4xf32>) -> tensor<1x3xf32>
// CHECK-DAG: %[[CST:.+]] = stablehlo.constant dense<1.000000e+00> : tensor<4x3xf32>

import (
	"html/template"
)

// AddSourceTemplates adds templates used by PrintWebList to t.
func AddSourceTemplates(t *template.Template) {
	template.Must(t.Parse(`{{define "weblistcss"}}` + weblistPageCSS + `{{end}}`))
	template.Must(t.Parse(`{{define "weblistjs"}}` + weblistPageScript + `{{end}}`))
}

const weblistPageCSS = `<style type="text/css">
body #content{
font-family: sans-serif;
}
h1 {
  font-size: 1.5em;

// Methods associated with non-local or unnamed types.
func (int /* ERROR "cannot define new methods on non-local type int" */ ) m() {}
func ([ /* ERROR "invalid receiver" */ ]int) m() {}
func (time /* ERROR "cannot define new methods on non-local type time.Time" */ .Time) m() {}
func (* /* ERROR "cannot define new methods on non-local type time.Time" */ time.Time) m() {}
func (x /* ERROR "invalid receiver" */ interface{}) m() {}

  context->getOrLoadDialect<tfrt::fallback::FallbackDialect>();
  context->getOrLoadDialect<compiler::TFRTDialect>();
  context->getOrLoadDialect<corert::CoreRTDialect>();

  allowUnknownTypes();

  addOperations<
#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tfrt/ir/tfrt_fallback_sync.cpp.inc"
      >();
}

static Type GetTensorType(Builder *builder) {
  return tfrt::tfrt_tensor::TensorType::get(builder->getContext());
}

	}
	d.sparse[id] = data
	return nil
}

// compactify attempts to compact sparse into dense.
//
// This is intended to be called only once after insertions are done.
func (d *dataTable[EI, E]) compactify() {
	if d.sparse == nil || len(d.dense) != 0 {
		// Already compactified.
		return
	}
	// Find the range of IDs.
	maxID := EI(0)
	minID := ^EI(0)

#include <fstream>
#include <string>

#include <gtest/gtest.h>
#include "flatbuffers/flatc.h"  // from @flatbuffers
#include "tensorflow/core/platform/platform.h"

#ifdef PLATFORM_GOOGLE
#define TFLITE_TF_PREFIX "third_party/tensorflow/"
#else
#define TFLITE_TF_PREFIX "tensorflow/"
#endif
/// Load filename `name`
bool LoadFileRaw(const char *name, std::string *buf) {
  std::ifstream fp(name, std::ios::binary);
  if (!fp) {

// for weight.

module attributes {tf_saved_model.semantics} {
  func.func private @quantize_dot_general_fn(%arg0: tensor<1x2xf32>) -> tensor<1x3xf32> attributes {tf._original_func_name = "main_0"} {
    %cst = stablehlo.constant dense<3.000000e-01> : tensor<2x3xf32>
    %0 = "quantfork.qcast"(%cst) : (tensor<2x3xf32>) -> tensor<2x3x!quant.uniform<i8:f32, 6.000000e-03>>
    %1 = "quantfork.dcast"(%0) : (tensor<2x3x!quant.uniform<i8:f32, 6.000000e-03>>) -> tensor<2x3xf32>