_type{"int16", 16, true},
	_type{"uint16", 16, false},
	_type{"int32", 32, true},
	_type{"uint32", 32, false},
	_type{"int64", 64, true},
	_type{"uint64", 64, false},
	_type{"int", 8 * uint(unsafe.Sizeof(int(0))), true},
	_type{"uint", 8 * uint(unsafe.Sizeof(uint(0))), false},
	_type{"uintptr", 8 * uint(unsafe.Sizeof((*byte)(nil))), false},
}

type binop struct {
	name string
	eval func(x, y *big.Int) *big.Int
}

				{
					Type:   cType,
					Status: v1.ConditionTrue,
				},
			},
		},
		{
			description: "replace",
			conditions: []v1.PodCondition{
				{
					Type:   cType,
					Status: v1.ConditionTrue,
				},
			},
			condition: v1.PodCondition{
				Type:   cType,
				Status: v1.ConditionFalse,
			},
			wantConditions: []v1.PodCondition{
				{
					Type:   cType,

  name: "Const"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 1
      }
    }
  }
}
node {
  name: "Const_1"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {

// and returns an expression that yields the *runtime._type value
// representing that map type.
func MakeMapRType(pos src.XPos, n *ir.MakeExpr) ir.Node {
	assertOp(n, ir.OMAKEMAP)
	if hasRType(n, n.RType, "RType") {
		return n.RType
	}
	return mapRType(pos, n.Type())
}

// MakeSliceElemRType asserts that n is a "make" operation for a slice
// type, and returns an expression that yields the *runtime._type

node {
  name: "bf16_scalar"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_BFLOAT16
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_BFLOAT16
        tensor_shape {
        }
        half_val: 0
        # CHECK: value = dense<0.000000e+00> : tensor<bf16>
      }
    }
  }

using tsl::StatusOr;

// Converts the TensorFlow DataType 'dtype' into an MLIR (scalar) type.
Status ConvertDataType(DataType dtype, mlir::Builder builder, mlir::Type* type);

// Converts a scalar MLIR type to a TensorFlow Datatype.
Status ConvertScalarTypeToDataType(mlir::Type type, DataType* dtype);

// Converts an MLIR type to TensorFlow DataType. If 'type' is a scalar type, it

  name: "w"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
        }
        float_val: 2.0
      }
    }
  }
}
node {
  name: "x"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {

 */
package org.codelibs.fess.crawler.entity;

/**
 * @author shinsuke
 *
 */
public interface AccessResult<IDTYPE> {
    void init(ResponseData responseData, ResultData resultData);

    IDTYPE getId();

    void setId(IDTYPE id);

    String getSessionId();

    void setSessionId(String sessionId);

    String getRuleId();

    void setRuleId(String ruleId);

    %0:2 = tf_executor.island wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_HALF", value = dense<1.0> : tensor<1x2xf16>} : () -> tensor<1x2xf16> loc("const1")
    %1:2 = tf_executor.island wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_HALF", value = dense<[1.0, 2.0]> : tensor<2xf16>} : () -> tensor<2xf16> loc("const2")

        }
      }
    }
  }
}
node {
  name: "BoxPredictor_4/ClassPredictor/weights"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 1
          }
          dim {
            size: 1
          }