} else {
				schema.Fields = append(schema.Fields, field)
			}
		}
	}

	for _, field := range schema.Fields {
		if field.DBName == "" && field.DataType != "" {
			field.DBName = namer.ColumnName(schema.Table, field.Name)
		}

		bindName := field.BindName()
		if field.DBName != "" {
			// nonexistence or shortest path or first appear prioritized if has permission

// `result_types` respectively.
absl::StatusOr<std::unique_ptr<Graph>> CreateSingleOpGraph(
    const NodeDef& node_def, absl::Span<const XlaArgument> args,
    absl::Span<const DataType> result_types);

// Checks if single device compilation and execution with PJRT is enabled for
// `device_type` in either the XlaLaunch op or the XlaCompileOnDemand op.

						columnType)
				}
			case "name":
				dataType := DB.Dialector.DataTypeOf(stmt.Schema.LookUpField(columnType.Name()))
				if !strings.Contains(strings.ToUpper(dataType), strings.ToUpper(columnType.DatabaseTypeName())) {
					t.Fatalf("column name type should be correct, name: %v, length: %v, expects: %v, column: %#v",
						columnType.Name(), columnType.DatabaseTypeName(), dataType, columnType)
				}

odified[f]),E.etag[f]&&T.setRequestHeader("If-None-Match",E.etag[f])),(y.data&&y.hasContent&&!1!==y.contentType||t.contentType)&&T.setRequestHeader("Content-Type",y.contentType),T.setRequestHeader("Accept",y.dataTypes[0]&&y.accepts[y.dataTypes[0]]?y.accepts[y.dataTypes[0]]+("*"!==y.dataTypes[0]?", "+It+"; q=0.01":""):y.accepts["*"]),y.headers)T.setRequestHeader(i,y.headers[i]);if(y.beforeSend&&(!1===y.beforeSend.call(v,T,y)||h))return T.abort();if(u="abort",b.add(y.complete),T.done(y.success),T....

    .Attr("dtype: type")
    .Attr("shape: shape")
    .Output("resource: resource")
    .SetIsStateful()
    .SetShapeFn([](shape_inference::InferenceContext* c) {
      c->set_output(0, c->Scalar());
      DataType t;
      TF_RETURN_IF_ERROR(c->GetAttr("dtype", &t));
      PartialTensorShape p;
      TF_RETURN_IF_ERROR(c->GetAttr("shape", &p));
      shape_inference::ShapeHandle s;

import com.tngtech.archunit.junit.AnalyzeClasses;
import com.tngtech.archunit.junit.ArchTest;
import com.tngtech.archunit.lang.ArchRule;
import org.gradle.internal.xml.XmlFactories;

import javax.xml.datatype.DatatypeFactory;
import javax.xml.parsers.DocumentBuilderFactory;
import javax.xml.parsers.SAXParserFactory;
import javax.xml.stream.XMLEventFactory;
import javax.xml.stream.XMLInputFactory;

class AbstractTensorInterface {
 public:
  // Release any underlying resources, including the interface object.
  virtual void Release() = 0;

  // Returns tensor dtype.
  virtual DataType Type() const = 0;
  // Returns number of dimensions.
  virtual int NumDims() const = 0;
  // Returns size of specified dimension
  virtual int64_t Dim(int dim_index) const = 0;

				Param(ws.QueryParameter("untilTime", "untilTime is an RFC3339 timestamp until which to show logs").DataType("string")).
				Param(ws.QueryParameter("tailLines", "tailLines is used to retrieve the specified number of lines from the end of the log").DataType("string")).
				Param(ws.QueryParameter("pattern", "pattern filters log entries by the provided regex pattern").DataType("string")).

  }

  // Returns whether any tensor in a list of tensors is being watched and has
  // a trainable dtype.
  bool ShouldRecord(absl::Span<const int64_t> tensor_ids,
                    absl::Span<const tensorflow::DataType> dtypes) const;

  // Adds this tensor to the list of watched tensors.
  //
  // This is a no-op if the tensor is already being watched either from an

	ws := new(restful.WebService)
	ws.Path("/logs")
	ws.Doc("get log files")
	ws.Route(ws.GET("/{logpath:*}").To(logFileHandler).Param(ws.PathParameter("logpath", "path to the log").DataType("string")))
	ws.Route(ws.GET("/").To(logFileListHandler))

	c.Add(ws)
}

func logFileHandler(req *restful.Request, resp *restful.Response) {
	logdir := "/var/log"