p2.y, cond) q.z.Select(p1.z, p2.z, cond) return q } // A {{.p}}Table holds the first 15 multiples of a point at offset -1, so [1]P // is at table[0], [15]P is at table[14], and [0]P is implicitly the identity // point. type {{.p}}Table [15]*{{.P}}Point // Select selects the n-th multiple of the table base point into p. It works in // constant time by iterating over every entry of the table. n must be in [0, 15]. func (table *{{.p}}Table) Select(p *{{.P}}Point, n uint8) { if n >= 16 { panic("nistec:...

        return doFindEpg(_epgMap, prop);
    }

    // ===================================================================================
    //                                                                          Table Info
    //                                                                          ==========
    protected final String _tableDbName = "related_content";
    protected final String _tableDispName = "related_content";

	}

	if !reflect.DeepEqual([]interface{}{"jinzhu", "POINT(100 100)"}, stmt.Vars) {
		t.Errorf("generated vars is not equal, got %v", stmt.Vars)
	}

	stmt = dryRunDB.Table("user_with_points").Create(&map[string]interface{}{
		"Name":  "jinzhu",
		"Point": clause.Expr{SQL: "ST_PointFromText(?)", Vars: []interface{}{"POINT(100 100)"}},
	}).Statement

						return err
					}
				default:
					return gorm.ErrInvalidData
				}
			} else {
				tx := db.Table("").Session(&gorm.Session{Context: db.Statement.Context, SkipHooks: db.Statement.SkipHooks})
				tx.Statement.ReflectValue = db.Statement.ReflectValue
				tx.Statement.Unscoped = db.Statement.Unscoped

	data, err := json.Marshal(event.Log{EventName: eventData.EventName, Key: key, Records: []event.Event{eventData}})
	if err != nil {
		return err
	}

	headers := make(amqp091.Table)
	// Add more information here as required, but be aware to not overload headers
	headers["minio-bucket"] = eventData.S3.Bucket.Name
	headers["minio-event"] = eventData.EventName.String()

    package from source.

## Continuous build status

You can find more community-supported platforms and configurations in the
[TensorFlow SIG Build Community Builds Table](https://github.com/tensorflow/build#community-supported-tensorflow-builds).

### Official Builds

     *
     *
     * <table>
     * <caption>LM Compatibility Levels</caption>
     * <tr>
     * <td>0 or 1</td>
     * <td>LM and NTLM</td>
     * </tr>
     * <tr>
     * <td>2</td>
     * <td>NTLM only</td>
     * </tr>
     * <tr>
     * <td>3-5</td>
     * <td>NTLMv2 only</td>
     * </tr>
     * </table>
     *
     *

        out.println("<b><a class=\"plain\" href=\".\">normal</a> | <a class=\"plain\" href=\"?fmt=detail\">detailed</a></b>");
        out.println("<p><table border='0' cellspacing='0' cellpadding='0'><tr><td>");

        out.print("<A style=\"width: " + maxLen);
        out.print("; height: 18;\" HREF=\"");
        out.print(path);
        out.println("\"><b>&uarr;</b></a>");

   * table is internally partitioned to try to permit the indicated number of concurrent updates
   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to
   * accommodate as many threads as will ever concurrently modify the table. Using a significantly

        return doFindEpg(_epgMap, prop);
    }

    // ===================================================================================
    //                                                                          Table Info
    //                                                                          ==========
    protected final String _tableDbName = "job_log";
    protected final String _tableDispName = "job_log";