return op_->SetAttrInt(attr_name, value);
}
Status SetAttrFloat(AbstractOperation* op_, const char* attr_name, float value,
                    ForwardOperation* forward_op_) {
  forward_op_->attrs.Set(attr_name, value);
  return op_->SetAttrFloat(attr_name, value);
}
Status SetAttrBool(AbstractOperation* op_, const char* attr_name, bool value,

    ],
)

filegroup(
    name = "pywrap_tf_session_hdrs",
    srcs = [
        "python_api.h",
    ],
    visibility = [
        "//tensorflow/core:__pkg__",
        "//tensorflow/python:__pkg__",
    ],
)

cc_library(
    name = "tf_attrtype",
    hdrs = ["tf_attrtype.h"],
    visibility = ["//visibility:public"],
)

cc_library(
    name = "c_api_macros_hdrs",
    hdrs = [

)

# buildifier: disable=same-origin-load
load("@rules_python//python:repositories.bzl", "py_repositories")

py_repositories()

load("@rules_python//python:repositories.bzl", "python_register_toolchains")  # buildifier: disable=same-origin-load
load(
    "//tensorflow/tools/toolchains/python:python_repo.bzl",
    "python_repository",
)

python_repository(name = "python_version_repo")

    tensorflow::NameAttrList func_name;
    func_name.set_name(string(value, value + length));
    op_->node_builder.Attr(attr_name, func_name);
    return absl::OkStatus();
  }
  Status SetAttrTensor(const char* attr_name,
                       AbstractTensorInterface* tensor) override {
    return tensorflow::errors::Unimplemented(
        "SetAttrTensor has not been implemented yet.");
  }

extern "C" {
#endif

// Resets `op_to_reset` with `op_or_function_name` and `raw_device_name`. This
// is for performance optimization by reusing an exiting unused op rather than
// creating a new op every time. If `raw_device_name` is `NULL` or empty, it
// does not set the device name. If it's not `NULL`, then it attempts to parse
// and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster

    std::string name = "Conj_Log1p_Grad_X";
    TF_RETURN_IF_ERROR(SafeConj(ctx, X, &temp_output, name.c_str()));

    AbstractTensorHandlePtr Conj_X(temp_output);

    // Creates Ones
    name = "OnesLike_Log1p_Grad_X";
    TF_RETURN_IF_ERROR(OnesLike(ctx, Conj_X.get(), &temp_output, name.c_str()));

    AbstractTensorHandlePtr Ones_X(temp_output);

    name = "Add_Log1p_Grad_X";

  }
  Status s;
  const char* device_name = DeviceName(&s);
  if (!s.ok()) {
    device_name = "<error fetching device name>";
  }
  return absl::StrCat("TensorHandle(", value_string, ", shape=", shape_string,
                      ", dtype=", DataType_Name(DataType()), ", device=\"",
                      device_name, "\")");
}

Status ImmediateExecutionTensorHandle::SummarizeValue(

  }
}

void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name, int64_t value) {
  auto s = tensorflow::unwrap(op)->SetAttrInt(attr_name, value);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

void TFE_OpSetAttrFloat(TFE_Op* op, const char* attr_name, float value) {
  auto s = tensorflow::unwrap(op)->SetAttrFloat(attr_name, value);
  if (!s.ok()) {

          ref: 'nightly'
      - name: Checkout repository
        if: ${{ github.event_name == 'push' }}
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
      - name: Build binary and run python tests on nightly for all python versions
        shell: bash
        run: |
          is_nightly=0 && tf_project_name='tf_ci_ext' && ${{ github.event_name == 'schedule' }} && is_nightly=1 && tf_project_name='tf_nightly_ci_ext'

*   Fixes an NPE in RandomShuffle with XLA enable [CVE-2023-25674](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2023-25674)
*   Fixes an FPE in TensorListSplit with XLA [CVE-2023-25673](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2023-25673)
*   Fixes segmentation fault in tfg-translate [CVE-2023-25671](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2023-25671)