encodings[0xb] = encoding // Vertical Tab
      encodings[0xe] = encoding // Shift Out
      encodings[0xf] = encoding // Shift In
      encodings[0x10] = encoding // Data Link Escape
      encodings[0x11] = encoding // Device Control 1 (oft. XON)
      encodings[0x12] = encoding // Device Control 2
      encodings[0x13] = encoding // Device Control 3 (oft. XOFF)

  TF_AddInput(desc, r);
  return TF_FinishOperation(desc, s);
}

TF_Operation* RandomUniform(TF_Operation* shape, TF_DataType dtype,
                            TF_Graph* graph, TF_Status* s) {
  TF_OperationDescription* desc =
      TF_NewOperation(graph, "RandomUniform", "random_uniform");
  TF_AddInput(desc, {shape, 0});
  TF_SetAttrType(desc, "dtype", dtype);
  return TF_FinishOperation(desc, s);
}

      TFE_OpSetAttrType(op, attr_name,
                        static_cast<TF_DataType>(default_value.type()));
      break;
    case tensorflow::AttrValue::kShape: {
      const auto& tensor_shape = default_value.shape();
      if (tensor_shape.unknown_rank()) {
        TFE_OpSetAttrShape(op, attr_name, nullptr, -1, status);
      } else {
        const auto num_dims = tensor_shape.dim_size();

inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape
inference
functions](https://www.tensorflow.org/guide/create_op#define_the_op_interface)
are skipped, and any checks implemented inside the shape inference code are not
executed.

The security impact of skipping those checks should be low, since the attack

    if (this[i] == '"'.code.toByte()) {
      result.write(this, i)
      // Consume '"'.
      readByte()
      return result.readUtf8()
    }

    if (size == i + 1L) return null // Dangling escape.
    result.write(this, i)
    // Consume '\'.
    readByte()
    result.write(this, 1L) // The escaped character.
  }
}

/**

			}
		}
	}
	var tokens []Token
	// Scan to newline. Backslashes escape newlines.
	for tok != '\n' {
		if tok == scanner.EOF {
			in.Error("missing newline in definition for macro:", name)
		}
		if tok == '\\' {
			tok = in.Stack.Next()
			if tok != '\n' && tok != '\\' {
				in.Error(`can only escape \ or \n in definition for macro:`, name)
			}
		}

  void GetTensor(const std::string& name,
                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,

     *
     * <p>Example:</p>
     * <pre>
     * input string: He didn't say, "Stop!"
     * output string: He didn't say, \"Stop!\"
     * </pre>
     *
     *
     * @param str  String to escape values in, may be null
     * @return String with escaped values, <code>null</code> if null string input
     */
    @SuppressWarnings("checkstyle:MagicNumber")
    protected static String escapeJava(String str) {

     *
     * <p>Example:</p>
     * <pre>
     * input string: He didn't say, "Stop!"
     * output string: He didn't say, \"Stop!\"
     * </pre>
     *
     *
     * @param str  String to escape values in, may be null
     * @return String with escaped values, <code>null</code> if null string input
     */
    @SuppressWarnings("checkstyle:MagicNumber")
    protected static String escapeJava(String str) {

      multiple: true
      options:
        - com.google.common.annotations
        - com.google.common.base
        - com.google.common.cache
        - com.google.common.collect
        - com.google.common.escape
        - com.google.common.eventbus
        - com.google.common.graph
        - com.google.common.hash
        - com.google.common.io
        - com.google.common.math
        - com.google.common.net