if sect.Addr <= s.Value && s.Value < sect.Addr+sect.Size {
							if sdat, err := sect.Data(); err == nil {
								data := sdat[s.Value-sect.Addr:]
								floats = make([]float64, len(data)/8)
								for i := range floats {
									floats[i] = math.Float64frombits(bo.Uint64(data[i*8:]))
								}
							}
						}
					}
				default:
					if n := indexOfDebugStr(s.Name); n != -1 {

    }

    public void setBoost_Equal(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Equal(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {
        setBoost_Term(boost, opLambda);
    }

    public void setBoost_Term(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Term(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {

            """
        ),
    ] = None,
    gt: Annotated[
        Optional[float],
        Doc(
            """
            Greater than. If set, value must be greater than this. Only applicable to
            numbers.
            """
        ),
    ] = None,
    ge: Annotated[
        Optional[float],
        Doc(
            """

    }

    public void setBoost_Equal(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Equal(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {
        setBoost_Term(boost, opLambda);
    }

    public void setBoost_Term(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Term(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {

  Tensor t_cc(DT_FLOAT, TensorShape({2, 3}));
  t_cc.flat<float>().setConstant(1.0);
  tensorflow::TensorProto t_proto;
  t_cc.AsProtoField(&t_proto);

  TF_Buffer* t_buffer = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(t_proto, t_buffer));

  const int num_bytes = 6 * sizeof(float);
  float* values =
      reinterpret_cast<float*>(tensorflow::cpu_allocator()->AllocateRaw(

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  float value = 0.0f;
  TF_Tensor* t = TFE_TensorHandleResolve(value_handle, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  ASSERT_EQ(sizeof(float), TF_TensorByteSize(t));
  memcpy(&value, TF_TensorData(t), sizeof(float));
  TF_DeleteTensor(t);
  EXPECT_EQ(12.0, value);

  TFE_DeleteTensorHandle(var_handle);

                || height < getThumbnailHtmlImageMinHeightAsInteger().intValue()) {
            return false;
        }

        final float ratio = getThumbnailHtmlImageMaxAspectRatioAsDecimal().floatValue();
        if ((float) width / (float) height > ratio || (float) height / (float) width > ratio) {
            return false;
        }

        return true;
    }

    String getHttpProxyHost();

		},
		{
			name:       "select-in-number-float",
			query:      `SELECT * from s3object s WHERE 3 in s.numbers[*]`,
			wantResult: `{"id":2,"title":"Second Record","desc":"another text","numbers":[2,3,4]}`,
		},
		{
			name:       "select-in-number-float-in-sql",
			query:      `SELECT * from s3object s WHERE 3.0 in s.numbers[*]`,

                            "name": "item_id",
                            "in": "path",
                        }
                    ],
                }
            },
            "/path/float/{item_id}": {
                "get": {
                    "responses": {
                        "200": {
                            "description": "Successful Response",

    assertEquals(int.class, TypeToken.of(int[].class).getComponentType().getType());
    assertEquals(long.class, TypeToken.of(long[].class).getComponentType().getType());
    assertEquals(float.class, TypeToken.of(float[].class).getComponentType().getType());
    assertEquals(double.class, TypeToken.of(double[].class).getComponentType().getType());
    assertNull(TypeToken.of(Object.class).getComponentType());