//
// Like qcasts, a dcast is allowed to have both its operand and result
// as non quantized types. This facilitates transformations and marks edges
// where the computation must be carried out in the expressed type.
//
// Especially early in transformation, it is common to have dcasts on
// all operands to ops that must operate with the expressed type (typically

	// Now compute mant*(2^e2)*(10^q).
	// Is it an exact computation?
	// Only small positive powers of 10 are exact (5^28 has 66 bits).
	exact := q <= 27 && q >= 0

	di, dexp2, d0 := mult64bitPow10(mant, e2, q)
	if dexp2 >= 0 {
		panic("not enough significant bits after mult64bitPow10")
	}
	// As a special case, computation might still be exact, if exponent

//
// If you modify this table, you MUST run 'go generate' to regenerate anames.go!
const (
	// Unprivileged ISA (Document Version 20190608-Base-Ratified)

	// 2.4: Integer Computational Instructions
	AADDI = obj.ABaseRISCV + obj.A_ARCHSPECIFIC + iota
	ASLTI
	ASLTIU
	AANDI
	AORI
	AXORI
	ASLLI
	ASRLI
	ASRAI
	ALUI
	AAUIPC
	AADD
	ASLT
	ASLTU
	AAND

//
// Like qcasts, a dcast is allowed to have both its operand and result
// as non quantized types. This facilitates transformations and marks edges
// where the computation must be carried out in the expressed type.
//
// Especially early in transformation, it is common to have dcasts on
// all operands to ops that must operate with the expressed type (typically

      }
    } else if (src_outside_compilation && !dst_outside_compilation) {
      // Case 1b: outside compilation to its XLA computation control edge.
      ReplaceAttr(e->src(), kXlaConnectedToXlaComputationAttrName, true);
    } else if (!src_outside_compilation && dst_outside_compilation) {
      // Case 1b: XLA computation to outside compilation in it control edge.
      ReplaceAttr(e->dst(), kXlaConnectedFromXlaComputationAttrName, true);
    }

  // A non-blocking version of `Execute`. After each call, `Join` must be called
  // before `StartExecute` is called again. Using `StartExecute` with `Join`
  // allows the caller to schedule computation on multiple ParallelDevices
  // without sequencing those operations (first call `StartExecute` on each
  // parallel device, then call `Join` on each; even if some of the `Join`s

public final class Quantiles {

  /** Specifies the computation of a median (i.e. the 1st 2-quantile). */
  public static ScaleAndIndex median() {
    return scale(2).index(1);
  }

  /** Specifies the computation of quartiles (i.e. 4-quantiles). */
  public static Scale quartiles() {
    return scale(4);
  }

  /** Specifies the computation of percentiles (i.e. 100-quantiles). */

    // TODO(ycao): Support tensorlist-type output.
    out_desc.is_tensor_list = false;
  }

  // XLA computation always uses Tuple shape.
  *xla_output_shape = xla::ShapeUtil::MakeTupleShape(shapes);
  return absl::OkStatus();
}

// Creates a vector that maps from the parameters of the XLA computation to
// their original argument positions.
// MLIR-based TF-Compiler bridge doesn't have constant analysis yet, thus no

      TF_ASSIGN_OR_RETURN(xla::ProgramShape program_shape,
                          result.computation->GetProgramShape());
      xla::HloModuleConfig config(program_shape);
      TF_ASSIGN_OR_RETURN(
          std::unique_ptr<xla::HloModule> new_module,
          xla::HloModule::CreateFromProto(result.computation->proto(), config));

      xla::HloPrintOptions opts;
      if (stage == IrExportStage::HLO_NO_METADATA) {

    FunctionDef *xla_fdef = fdl.add_function();
    TF_CHECK_OK(GraphToFunctionDef(*g, "f3", xla_fdef));
  }
  FunctionLibraryDefinition fld(OpRegistry::Global(), fdl);

  // Build the XLA computation graph.
  // "arg0" (T=DT_RESOURCE), "arg1" (T=DT_INT32)
  // "arg0", "arg1" -> "if" (If) -> "ret0", "ret1"
  // "arg0", "arg1" -> "while" (While) -> "ret2", "ret3"
  tensorflow::Scope s = tensorflow::Scope::NewRootScope();