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 {

	skip := func(oi ObjectInfo) (ok bool) {
		if r.Flags.Filter.OlderThan > 0 && time.Since(oi.ModTime) < r.Flags.Filter.OlderThan.D() {
			// skip all objects that are newer than specified older duration
			return true
		}

		if r.Flags.Filter.NewerThan > 0 && time.Since(oi.ModTime) >= r.Flags.Filter.NewerThan.D() {

    }

    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) {

TEST(CAPI, TestFromProto) {
  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);

	info, err := s.diskInfoCache.Get()
	if err != nil {
		return false
	}
	if info.Used == 0 || info.UsedInodes == 0 {
		return false
	}
	return (float64(info.Free)/float64(info.Used)) < almostFilledPercent || (float64(info.FreeInodes)/float64(info.UsedInodes)) < almostFilledPercent
}

func (s *xlStorage) moveToTrashNoDeadline(filePath string, recursive, immediatePurge bool) (err error) {
	pathUUID := mustGetUUID()

                || 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[*]`,