DenseElementsAttr perm2_const) {
  SmallVector<int32_t> initial_permutation;
  DenseElementsAttr perm1_const;

  SmallVector<int32_t> new_permutation;
  if (matchPattern(permutation1, m_Constant(&perm1_const))) {
    for (int32_t idx = 0; idx < perm1_const.getNumElements(); ++idx) {
      initial_permutation.push_back(idx);
    }

    return 1;
  }
  return 0;
}

int check_int32(void* handle, const char* fname, int32_t want) {
  int32_t (*fn)();
  fn = (int32_t (*)())dlsym(handle, fname);
  if (!fn) {
    fprintf(stderr, "ERROR: missing %s: %s\n", fname, dlerror());
    return 1;
  }
  int32_t ret = fn();
  if (ret != want) {
    fprintf(stderr, "ERROR: %s=%d, want %d\n", fname, ret, want);
    return 1;
  }

  ShapedType weight_type = mlir::cast<ShapedType>(weight.getType());
  const int32_t input_rank = input_type.getRank();
  const int32_t weight_rank = weight_type.getRank();
  const int32_t broadcasted_rank = std::max(input_rank, weight_rank);

  const int32_t num_matmul_dim = 2;
  const int32_t num_input_batch_dim = input_rank - num_matmul_dim;
  const int32_t num_weight_batch_dim = weight_rank - num_matmul_dim;

// license that can be found in the LICENSE file.

package main

/*
#include <stdint.h>

void f(int32_t *p, int n) {
  int i;

  for (i = 0; i < n; i++) {
    p[i] = (int32_t)i;
  }
}
*/
import "C"

import (
	"fmt"
	"os"
	"unsafe"
)

func main() {
	a := make([]int32, 10)
	C.f((*C.int32_t)(unsafe.Pointer(&a[0])), C.int(len(a)))
	for i, v := range a {
		if i != int(v) {

  CalibrationStatistics statistics;
  statistics.mutable_histogram_statistics()->CopyFrom(hist_stats);

  return statistics;
}

std::pair<int32_t, int32_t>
CalibrationStatisticsCollectorHistogram::ExpandHistogramIfNeeded(
    const float lower_bound, const float upper_bound) {
  int32_t lower_idx = CalculateBinIndex(lower_bound, lower_bound_, bin_width_);
  // If lower_idx < 0, then expand the histogram to the left.
  if (lower_idx < 0) {

  ASSERT_TRUE(succeeded(dense_attr));
  EXPECT_THAT(dense_attr->getValues<int32_t>(), testing::SizeIs(4));
  EXPECT_EQ(dense_attr->getValues<int32_t>()[0], 1);
  EXPECT_EQ(dense_attr->getValues<int32_t>()[1], 2);
  EXPECT_EQ(dense_attr->getValues<int32_t>()[2], 3);
  EXPECT_EQ(dense_attr->getValues<int32_t>()[3], 4);
}

TEST(GetDenseAttrFromTensorProtoAttrTest, Qint32ToInt32Succeeds) {

  auto padding_type = RankedTensorType::get({4, 2}, builder.getIntegerType(32));

  // Calculate paddings.
  int32_t pad_total = kernel_size - 1;
  int32_t pad_beg = (pad_total / 2 + 1) / block_size;
  int32_t pad_end = (pad_total / 2) / block_size;
  SmallVector<int32_t, 8> values = {0,       0,       pad_beg, pad_end,
                                    pad_beg, pad_end, 0,       0};

    flattened_out_segids[i] = 0;
  }
  llvm::SmallVector<int32_t, 4> flattened_contracting_segids =
      llvm::SmallVector<int32_t, 4>(operand_rank, static_cast<int32_t>(-1));
  for (int64_t i : dot_dimensions_info.contracting_dimensions().AxesArray()) {
    flattened_contracting_segids[i] = 0;
  }
  auto seg_prod_result_type =
      RankedTensorType::get(static_cast<int32_t>(1), builder.getI32Type());

#include <errno.h>
#include <stdint.h>
#include <stdlib.h>
#include <sys/mman.h>

#include "libcgo.h"

uintptr_t
x_cgo_mmap(void *addr, uintptr_t length, int32_t prot, int32_t flags, int32_t fd, uint32_t offset) {
	void *p;

	_cgo_tsan_acquire();
	p = mmap(addr, length, prot, flags, fd, offset);
	_cgo_tsan_release();
	if (p == MAP_FAILED) {

      mlir::TF::IfOp op, const std::vector<int32_t>& operands,
      const std::vector<int32_t>& results);

  // Build while operator where cond & body are regions.
  std::optional<BufferOffset<tflite::Operator>> BuildWhileOperator(
      mlir::TFL::WhileOp op, const std::vector<int32_t>& operands,
      const std::vector<int32_t>& results);

  // Build call once operator.