return err.Error() == "sql: statement is closed"
}

// TestPreparedStmtConcurrentReset test calling reset and executing SQL concurrently
// this test making sure that the gorm would not get a Segmentation Fault, and the only error cause by this is using a closed Stmt
func TestPreparedStmtConcurrentReset(t *testing.T) {
	name := "prepared_stmt_concurrent_reset"
	user := *GetUser(name, Config{})

number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution, one of the nodes would participate more drives. To avoid this the affinity is given towards nodes which leads to next best GCD factor of 12 which provides uniform distribution.

- In this algorithm, we also make sure that we spread the drives...

     * silently {@link #addNode(Object) add} {@code nodeU} and {@code nodeV} to the graph.
     *
     * @return this {@code Builder} object
     * @throws IllegalArgumentException if the introduction of the edge would violate {@link
     *     #allowsSelfLoops()}
     */
    @CanIgnoreReturnValue
    public ImmutableValueGraph.Builder<N, V> putEdgeValue(N nodeU, N nodeV, V value) {

   *
   * Since these fields are non-final that means that TimeoutFuture is not being 'safely published',
   * thus a motivated caller may be able to expose the reference to another thread that would then
   * call cancel() and be unable to cancel the delegate.
   * There are a number of ways to solve this, none of which are very pretty, and it is currently

 
## Pruning the Cache

Pruning the entire Cache to clear space temporarily can be done using evictAll.

```kotlin
cache.evictAll()
```

Removing individual items can be done using the urls iterator.
This would be typical after a user initiates a force refresh by a pull to refresh type action.

```java
    val urlIterator = cache.urls()
    while (urlIterator.hasNext()) {

    /*
     * For example, if concentration=2.0, the following takes the square root of
     * the uniformly-distributed random integer, then truncates any fractional
     * part, so higher integers would appear (in this case linearly) more often
     * than lower ones.
     */
    return (int) Math.pow(a, 1.0 / concentration);
  }

  @AfterExperiment
  void tearDown() {
    double req = requests.get();

    validations:
      required: true

  - type: textarea
    attributes:
      label: Example
      description: >
        Please provide an example usage of the feature that would be different with the improvement.
      render: java
    validations:
      required: true

  - type: textarea
    attributes:
      label: Current Behavior
      description: What does the feature currently do?

  //
  // If false, a caller might implement pretty-printing by resolving and
  // iterating over the resulting tensor. This may still be viable if resolving
  // the handle loses information, but `SummarizeValue` would be more precise.
  virtual bool PreferCustomSummarizer() const { return false; }

  // Returns a string which summarizes the value of this TensorHandle, for
  // debugging. Does not include a shape or dtype.
  //

# by trying to run a trivial program and ensuring it actually ran. If not, emit our warning.
# Note: we cannot do anything like $(shell docker version) to check, since that would also fail.
CAN_RUN := $(shell echo "can I run echo")
ifeq ($(CAN_RUN),)
$(error $(warning))
endif

#-----------------------------------------------------------------------------
# Global Variables

name: TensorFlow Issue Template
description: Use this template to report TensorFlow-related issues
body:
  - type: dropdown
    id: issue-type
    attributes:
      label: Issue type
      description: What type of issue would you like to report?
      multiple: false
      options:
        - Bug
        - Build/Install
        - Performance
        - Support
        - Feature Request
        - Documentation Feature Request