// Permutation from the OIHW (== (output features, input features, height,
// width)) tensor format to HWIO. This is commonly used to transpose convolution
// weights represented as OIHW format to HWIO, which is more desirable for
// certain downstream optimization passes (e.g. XLA).
inline constexpr std::array<int64_t, 4> kOihwToHwioPermutation = {2, 3, 1, 0};

// Returns true if the value has static shape.

      // TODO(b/172517537): check if other tensors should go through this
      // check too.
      op.emitError() << "Input tensor [" << input_index
                     << "] is a state tensor, but has more than one use.";
      return failure();
    }
    auto stats = mlir::dyn_cast<DenseFPElementsAttr>(stats_op.getLayerStats());
    if (!stats || stats.getNumElements() != 2) {

#include <unordered_set>
#include <vector>

#include "tensorflow/core/config/flag_defs.h"
#include "tensorflow/core/config/flags.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/gtl/array_slice.h"
#include "tensorflow/core/lib/gtl/cleanup.h"
#include "tensorflow/core/lib/gtl/flatmap.h"
#include "tensorflow/core/lib/gtl/flatset.h"
#include "tensorflow/core/platform/errors.h"

    if (!expand_op.getResult().hasOneUse()) {
      return rewriter.notifyMatchFailure(
          expand_op, "result for current op has more than 1 use");
    }
    if (!squeeze_op.getResult().hasOneUse()) {
      return rewriter.notifyMatchFailure(
          squeeze_op, "result for current op has more than 1 use");
    }
    // Make sure that the axis in `expand_op` is constant.
    if (auto const_op =

#include <optional>
#include <string>
#include <vector>

#include "absl/container/flat_hash_set.h"
#include "absl/types/optional.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/config.pb.h"
#include "tensorflow/core/util/command_line_flags.h"

namespace tensorflow {

struct XlaAutoJitFlag {
  // Control compilation of operators into XLA computations on CPU and GPU

#include "absl/strings/str_cat.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/lib/hash/hash.h"
#include "tensorflow/core/lib/strings/strcat.h"

namespace tensorflow {

/// @defgroup core Core Tensorflow API

class Output;

/// @addtogroup core
/// @{

/// Represents a node in the computation graph.

    if (llvm::isa<FixedOutputRangeInterface, SameScalesOpInterface>(def) ||
        !def->hasTrait<OpTrait::quant::QuantizableResult>()) {
      return failure();
    }

    // This op should not clobber def, if more than one requant of this value.
    if (!pre_quantized.hasOneUse()) {
      return failure();
    }

    op.emitWarning("Remove trivial `rescale` op. Please fix the source graph.");

    llvm::APSInt result(storage_bit_width_, !is_signed_);
    fixed_point.convertToInteger(result, round_mode_, &lossy);

    return std::move(result);
  }

  int64_t quantizeFloatToInt64(APFloat expressed_value) const {
    const APInt q_value = quantizeFloatToInt(std::move(expressed_value));
    return is_signed_ ? q_value.getSExtValue() : q_value.getZExtValue();
  }

        ":util",
        "//tensorflow/core:lib",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core/platform:errors",
        "//tensorflow/core/platform:strcat",
        "//tensorflow/core/platform:tstring",
        "//tensorflow/core/util/tensor_bundle",
        "//tensorflow/core/util/tensor_bundle:byteswaptensor",
        "@com_google_absl//absl/container:flat_hash_set",
        "@com_google_absl//absl/log",

#include "absl/strings/str_cat.h"
#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/lib/gtl/array_slice.h"

namespace tensorflow {

class Graph;
class GraphDef;
class NodeBuilder;
struct CompositeOpScopes;

/// @addtogroup core
/// @{

/// A `Scope` object represents a set of related TensorFlow ops that have the