*
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software distributed under the License
 * is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
 * or implied. See the License for the specific language governing permissions and limitations under
 * the License.
 */

package com.google.common.io;

 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

    with path.open("rb") as file:
        response = client.post("/files/", files={"file": file})
    assert response.status_code == 200, response.text
    assert response.json() == {"file_size": 14}


def test_post_upload_file(tmp_path):
    path = tmp_path / "test.txt"
    path.write_bytes(b"<file content>")

    client = TestClient(app)
    with path.open("rb") as file:

    attributes:
      label: Self-contained Reproducer Project
      description: |
        Provide a [minimal, self-contained example](https://en.wikipedia.org/wiki/Minimal_reproducible_example) project demonstrating the problem as a GitHub repository or an attached archive.
        You can use [the template](https://github.com/gradle/gradle-issue-reproducer) with a Gradle GitHub action set up to showcase your problem.

   * @throws ArithmeticException of the next-higher power of two is not representable as a {@code
   *     long}, i.e. when {@code x > 2^62}
   * @since 20.0
   */
  public static long ceilingPowerOfTwo(long x) {
    checkPositive("x", x);
    if (x > MAX_SIGNED_POWER_OF_TWO) {
      throw new ArithmeticException("ceilingPowerOfTwo(" + x + ") is not representable as a long");
    }
    return 1L << -Long.numberOfLeadingZeros(x - 1);
  }

cluster for this to work. If you'd rather use `emptyDir`, disable PersistentVolumeClai by: ```bash helm install --set persistence.enabled=false minio/minio ``` > *"An emptyDir volume is first created when a Pod is assigned to a Node, and exists as long as that Pod is running on that node. When a Pod is removed from a node for any reason, the data in the emptyDir is deleted forever."* ### Existing PersistentVolumeClai If a Persistent Volume Claim already exists, specify it during installation. 1....

cluster for this to work. If you'd rather use `emptyDir`, disable PersistentVolumeClai by: ```bash helm install --set persistence.enabled=false minio/minio ``` > *"An emptyDir volume is first created when a Pod is assigned to a Node, and exists as long as that Pod is running on that node. When a Pod is removed from a node for any reason, the data in the emptyDir is deleted forever."* ### Existing PersistentVolumeClai If a Persistent Volume Claim already exists, specify it during installation. 1....

	case int64:
		return x, nil
	case string:
		// Parse as number, truncate floating point if
		// needed.
		// String might contain trimming spaces, which
		// needs to be trimmed.
		res, ok := strToInt(strings.TrimSpace(x))
		if !ok {
			return 0, errCastFailure("could not parse as int")
		}
		return res, nil
	case []byte:
		// Parse as number, truncate floating point if
		// needed.

  return result;
}

// Used as an argument to TFE_NewCustomDeviceTensorHandle, indicating how
// ParallelTensors wrapped in TFE_TensorHandles should be cleaned up once their
// reference counts drop to zero.
void ParallelTensorDeallocator(void* data) {
  delete reinterpret_cast<ParallelTensor*>(data);
}

// Used as an argument to TFE_NewCustomDeviceTensorHandle, for computing the