const val INITIAL_MAX_FRAME_SIZE = 0x4000 // 16384

  const val TYPE_DATA = 0x0
  const val TYPE_HEADERS = 0x1
  const val TYPE_PRIORITY = 0x2
  const val TYPE_RST_STREAM = 0x3
  const val TYPE_SETTINGS = 0x4
  const val TYPE_PUSH_PROMISE = 0x5
  const val TYPE_PING = 0x6
  const val TYPE_GOAWAY = 0x7
  const val TYPE_WINDOW_UPDATE = 0x8
  const val TYPE_CONTINUATION = 0x9

}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
                               const TF_DataType* values, int num_values) {
  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, tensorflow::gtl::ArraySlice<const tensorflow::DataType>(
                          reinterpret_cast<const tensorflow::DataType*>(values),
                          num_values));
}

0!==arguments[2]?arguments[2]:h;t&&t(e,null);let i=o.length;for(;i--;){let t=o[i];if("string"==typeof t){const e=r(t);e!==t&&(n(o)||(o[i]=e),t=e)}e[t]=!0}return e}function w(e){for(let t=0;t<e.length;t++){_(e,t)||(e[t]=null)}return e}function C(t){const n=l(null);for(const[o,r]of e(t)){_(t,o)&&(Array.isArray(r)?n[o]=w(r):r&&"object"==typeof r&&r.constructor===Object?n[o]=C(r):n[o]=r)}return n}function O(e,t){for(;null!==e;){const n=r(e,t);if(n){if(n.get)return D(n.get);if("function"==typeof n.value)return D(n.value)}e=o(e)}return...

  }
}

bool CheckpointReader::HasTensor(const string& name) const {
  if (reader_ != nullptr) {
    return reader_->HasTensor(name, nullptr, nullptr);
  }
  return v2_reader_->Contains(name);
}

const TensorSliceReader::VarToShapeMap&
CheckpointReader::GetVariableToShapeMap() const {
  CHECK(var_to_shape_map_);
  return *var_to_shape_map_;
}

const TensorSliceReader::VarToDataTypeMap&

pkg os, const ModeDir FileMode
pkg os, const ModeExclusive FileMode
pkg os, const ModeIrregular FileMode
pkg os, const ModeNamedPipe FileMode
pkg os, const ModePerm FileMode
pkg os, const ModeSetgid FileMode
pkg os, const ModeSetuid FileMode
pkg os, const ModeSocket FileMode
pkg os, const ModeSticky FileMode
pkg os, const ModeSymlink FileMode
pkg os, const ModeTemporary FileMode
pkg os, const ModeType = 2399141888

/** `100 Continue` (HTTP/1.1 - RFC 7231)  */
const val HTTP_CONTINUE = 100

/** `101 Switching Protocols` (HTTP/1.1 - RFC 9110)  */
const val HTTP_SWITCHING_PROTOCOLS = 101

/** `102 Processing` (WebDAV - RFC 2518)  */
const val HTTP_PROCESSING = 102

/** `103 Early Hints (Early Hints - RFC 8297)` */
const val HTTP_EARLY_HINTS = 103

/** `307 Temporary Redirect` (HTTP/1.1 - RFC 7231)  */
const val HTTP_TEMP_REDIRECT = 307

pkg p1, const A //deprecated
pkg p1, const A = 1
pkg p1, const A ideal-int
pkg p1, const A64 = 1
pkg p1, const A64 int64
pkg p1, const AIsLowerA = 11
pkg p1, const AIsLowerA ideal-int
pkg p1, const B0 = 2
pkg p1, const B0 ideal-int
pkg p1, const ConstChase2 = 11
pkg p1, const ConstChase2 ideal-int
pkg p1, const ConversionConst = 5
pkg p1, const ConversionConst MyInt
pkg p1, const FloatConst = 1.5  // 3/2
pkg p1, const FloatConst ideal-float

        node.style.display = "block";
        new Termynal(node, {
            lineDelay: 500
        });
    });
    const progressLiteralStart = "---> 100%";
    const promptLiteralStart = "$ ";
    const customPromptLiteralStart = "# ";
    const termynalActivateClass = "termy";
    let termynals = [];

    function createTermynals() {
        document

data class VersionedSettingsBranch(
    val branchName: String,
) {
    companion object {
        private const val MASTER_BRANCH = "master"

        private const val RELEASE_BRANCH = "release"

        private const val EXPERIMENTAL_BRANCH = "xperimental"

        // master branch of gradle/gradle-promote
        private const val GRADLE_PROMOTE_MASTER_VCS_ROOT_ID = "Gradle_GradlePromoteMaster"

      absl::Span<AbstractTensorHandle* const> gradient_tensors) const override;

  // Calls the passed-in backward function.
  // op_type is the op's name provided in RecordOperation.
  absl::Status CallBackwardFunction(
      const string& op_type, GradientFunction* gradient_function,
      const std::vector<int64_t>& unneeded_gradients,
      absl::Span<AbstractTensorHandle* const> output_gradients,