if err == nil {
		t.Fatalf("Transaction should get error when using cancelled context")
	}
}

func TestTransactionWithBlock(t *testing.T) {
	assertPanic := func(f func()) {
		defer func() {
			if r := recover(); r == nil {
				t.Fatalf("The code did not panic")
			}
		}()
		f()
	}

	// rollback
	err := DB.Transaction(func(tx *gorm.DB) error {
		user := *GetUser("transaction-block", Config{})

  private fun runWriter() {
    this.assertThreadHoldsLock()

    val writerTask = writerTask
    if (writerTask != null) {
      taskQueue.schedule(writerTask)
    }
  }

  /**
   * Attempts to remove a single frame from a queue and send it. This prefers to write urgent pongs
   * before less urgent messages and close frames. For example it's possible that a caller will

    // duplicate keys, hashTablePlus consists of 3 elements: [0] the hashTable; [1] the number of
    // entries in alternatingKeysAndValues that are still valid after rewriting to remove
    // duplicates; [2] a Builder.DuplicateKey that records the first duplicate key we encountered
    // for possible later use in exceptions, perhaps straight away.

```console
$ <font color="#4E9A06">fastapi</font> dev <u style="text-decoration-style:single">main.py</u>
<font color="#3465A4">INFO    </font> Using path <font color="#3465A4">main.py</font>
<font color="#3465A4">INFO    </font> Resolved absolute path <font color="#75507B">/home/user/code/awesomeapp/</font><font color="#AD7FA8">main.py</font>

  // Set device to CPU since there is no version of split for int32 on GPU
  // TODO(iga): Convert all these helpers and tests to use floats because
  // they are usually available on GPUs. After doing this, remove TF_SetDevice
  // call in c_api_function_test.cc
  TF_SetDevice(desc, "/cpu:0");
  *op = TF_FinishOperation(desc, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_NE(*op, nullptr);
}

     * 
     * @return the Oid of the mechanism being used
     */
    ASN1ObjectIdentifier[] getMechs () {
        return this.mechs;
    }


    /**
     * @return the mechanisms announced by the remote end
     */
    ASN1ObjectIdentifier[] getRemoteMechs () {
        return this.remoteMechs;
    }


    /**
     * Set what mechanism is being used for this context.
     * 
     * @param mechs

  // and not for correctness. The only downside of keeping this 1 seems to be
  // that the gradient accumulation is unbounded and we will never
  // aggressively aggregate accumulated gradients to recover memory.
  // Revisit and fix.
  return 1;
}

// Consumes references to the tensors in the gradient_tensors list and returns
// a tensor with the result.
AbstractTensorHandle* TapeVSpace::AggregateGradients(

    per_device_output_tensors.push_back(device_thread->Join(status));
    // We will run every Join even if there are bad statuses in case the user
    // wants to recover and continue running ops on the parallel device (which
    // would otherwise deadlock).
    if (TF_GetCode(status) != TF_OK &&
        (first_bad_status == nullptr

op":"bottom"),this.$widget.addClass("timepicker-orient-"+q),"top"===q?n+=k:n-=d+parseInt(this.$widget.css("padding-top"),10),this.$widget.css({top:n,left:m,zIndex:i})}},remove:function(){a("document").off(".timepicker"),this.$widget&&this.$widget.remove(),delete this.$element.data().timepicker},setDefaultTime:function(a){if(this.$element.val())this.updateFromElementVal();else if("current"===a){var b=new Date,c=b.getHours(),d=b.getMinutes(),e=b.getSeconds(),f="AM";0!==e&&(e=Math.ceil(b.getSeconds...

        # This expects that GenerateJsonSchema was already used to generate the definitions
        json_schema = field_mapping[(field, override_mode or field.mode)]
        if "$ref" not in json_schema:
            # TODO remove when deprecating Pydantic v1
            # Ref: https://github.com/pydantic/pydantic/blob/d61792cc42c80b13b23e3ffa74bc37ec7c77f7d1/pydantic/schema.py#L207
            json_schema["title"] = (