// Returns a failure() on error, otherwise returns true to indicate that it
  // reached convergence, false otherwise.
  FailureOr<bool> PropagateShapeIntoAttachedFunctions(Operation* op,
                                                      int64_t max_iterations);

  // Shape propagation for region based control flow.
  // Returns a failure() on error, otherwise returns true to indicate that it

  // node name couldn't be found in the input DebugInfo, a NameLoc is used as
  // the location.
  mlir::Location GetLocation(const Node& node);

  // Appends the location string for the node to the error message and returns
  // the combined error status.
  Status EmitErrorWithLocationStr(const Node& node, const Status& error_status);

  // Inserts a placeholder node in the graph to replace a feed output tensor,

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

package windows

import (
	"net"
	"syscall"
	"unsafe"
)

// NTStatus corresponds with NTSTATUS, error values returned by ntdll.dll and
// other native functions.
type NTStatus uint32

const (
	// Invented values to support what package os expects.
	O_RDONLY   = 0x00000
	O_WRONLY   = 0x00001
	O_RDWR     = 0x00002

        return lockedGetOrLoad(key, hash, loader);
      } catch (ExecutionException ee) {
        Throwable cause = ee.getCause();
        if (cause instanceof Error) {
          throw new ExecutionError((Error) cause);
        } else if (cause instanceof RuntimeException) {
          throw new UncheckedExecutionException(cause);
        }
        throw ee;
      } finally {

    },
    "io.k8s.api.core.v1.ComponentCondition": {
      "description": "Information about the condition of a component.",
      "properties": {
        "error": {
          "description": "Condition error code for a component. For example, a health check error code.",
          "type": "string"
        },
        "message": {

    }

    // This shows current behaviour, where the transform is executed even though the input artifact has not been created yet
    // This should become an error eventually
    def "executes transform immediately when required during task graph building"() {
        buildFile << declareAttributes() << withJarTasks() << """

		Name:      "errors_timeout",
		Help:      "Total number of drive timeout errors since server uptime",
		Type:      counterMetric,
	}
}

func getNodeDriveIOErrorsMD() MetricDescription {
	return MetricDescription{
		Namespace: nodeMetricNamespace,
		Subsystem: driveSubsystem,
		Name:      "errors_ioerror",
		Help:      "Total number of drive I/O errors since server uptime",
		Type:      counterMetric,
	}
}

    differences between float and quantized activations, output
    logs, set differences to the output tensors, and throws an error if errors
    above tolerance exist. If log_if_failed = false, then it doesn't care about
    errors.
  }];

  let arguments = (ins
    TFL_TensorOf<[QI8, QUI8, QI16, F16, TFL_Quint8]>:$input,
    TFL_TensorOf<[F32]>:$ref,

    // Attributes

// easier to write, but generates horrible messages when there is a
// compiler error, as gcc insists on printing out each template
// argument, even if it has the default value (this means Types<int>
// will appear as Types<int, None, None, ..., None> in the compiler
// errors).
//
// Our solution is to combine the best part of the two approaches: a

    a tf_executor.fetch into a sea of nodes consisting of TensorFlow Dialect ops by
    lifting such ops out of a tf_executor.graph's tf_executor.islands. If V1 control
    flow ops are present in a tf_executor.graph, an error will be returned.

    For example, the following:

    ```mlir
    func @my_fn(%arg0: tensor<i32>, %arg1: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
      %graph_results:2 = tf_executor.graph {