hdrs = ["gradients/grad_helper.h"],
    visibility = ["//tensorflow:internal"],
    deps = [
        ":cc_ops",
        "//tensorflow/cc:ops",
        "//tensorflow/cc:scope",
    ],
)

cc_library(
    name = "linalg_grad",
    srcs = ["gradients/linalg_grad.cc"],
    deps = [
        ":cc_ops",
        ":cc_ops_internal",
        ":grad_helper",
        ":grad_op_registry",
        ":gradients",

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

#include <algorithm>
#include <cstdint>
#include <functional>
#include <limits>
#include <numeric>
#include <string>
#include <tuple>
#include <type_traits>
#include <utility>

// refreshes.
//
// This file includes another file, `tf_generated_ops.td`, which contains
// all ops whose definitions are generated from TensorFlow codebase.
// Changes made there are not respected.

#ifndef TF_OPS
#define TF_OPS

include "tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td"
include "mlir/Interfaces/CallInterfaces.td"

Deqiang Chen <******@****.***> 1709591321 -0800

Deqiang Chen <******@****.***> 1716411971 -0700

#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/init_main.h"
#include "tensorflow/core/platform/types.h"
#include "tsl/platform/status.h"

namespace tensorflow {
namespace cc_op {
namespace {

void PrintAllCCOps(const std::string& dot_h, const std::string& dot_cc,
                   bool include_internal,
                   const std::vector<string>& api_def_dirs) {
  OpList ops;

  // it's a constant. Basically, `paddings` tensor in `SpaceToBatch` and `crops`
  // tensor  in `BatchToSpace` must satisfy the following:
  //  paddings[i, 0] = base_paddings[i, 0].
  //  0 <= paddings[i, 1] - base_paddings[i, 1] < block_shape[i]
  // (input_shape[i] + paddings[i, 0] + paddings[i, 1]) % block_shape[i] == 0.
  //  crops[i, 0] = 0.
  //  crops[i, 1] = paddings[i, 1] - base_paddings[i, 1].

from tensorflow.python.ops import array_ops_stack  # pylint: disable=g-direct-tensorflow-import
from tensorflow.python.ops import io_ops
from tensorflow.python.ops import lookup_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import nn_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import string_ops
from tensorflow.python.ops import variables

#include "tensorflow/core/platform/statusor.h"
#include "tensorflow/core/platform/str_util.h"
#include "tensorflow/core/platform/types.h"
#include "tsl/platform/status.h"

namespace tensorflow {
namespace cc_op {
namespace {

void WriteAllFuzzers(string root_location, std::vector<string> api_def_dirs,
                     std::vector<string> op_names) {
  OpList ops;
  absl::StatusOr<ApiDefMap> api_def_map =

        return true;
      }

      // Check if the preceding op is a quantized same-scale op.
      if (llvm::isa<quantfork::StorageCastOp>(preceding_op)) {
        auto sc_op = llvm::cast<quantfork::StorageCastOp>(preceding_op);
        auto sc_arg_type = sc_op.getArg().getType().dyn_cast<TensorType>();
        if (sc_arg_type.getElementType().isInteger(8)) {
          return true;
        }
      }
    }