Let's check back those deployment concepts from before:

* Security - HTTPS
* Running on startup
* Restarts
* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

Up to this point, with all the tutorials in the docs, you have probably been running a **server program**, for example, using the `fastapi` command, that runs Uvicorn, running a **single process**.

   - sanjoy
# filesystem path
filesystem_path:
   - tensorflow/c/experimental/filesystem
# security path
security_path:
   - tensorflow/security
# words checklist
segfault_memory:
   - segfault
   - memory leaks
# assignees
filesystem_security_assignee:
   - mihaimaruseac
   
# Cuda Comment
cuda_comment: >
   From the template it looks like you are installing **TensorFlow** (TF) prebuilt binaries:

//     in `input_shapes`.
//
// The results are returned in `output_shapes` and
// `output_resource_shapes_and_types`. The caller is responsible for freeing the
// memory in these buffers by calling `TF_DeleteShapeAndTypeList`.
TF_CAPI_EXPORT extern void TFE_InferShapes(
    TFE_Op* op, TF_ShapeAndTypeList* input_shapes, TF_Tensor** input_tensors,
    TF_ShapeAndTypeList* input_tensor_as_shapes,

    private int length; // 4 bytes: Length of buffer

    /**
     * Create SMB2 RDMA Transform
     *
     * @param offset offset within registered buffer
     * @param token RDMA provider token (steering tag/memory handle)
     * @param length length of buffer
     */
    public Smb2RdmaTransform(long offset, int token, int length) {
        this.offset = offset;
        this.token = token;
        this.length = length;
    }

 * <p>This class should not be assumed to be universally superior to {@code java.util.HashMap}.
 * Generally speaking, this class reduces object allocation and memory consumption at the price of
 * moderately increased constant factors of CPU. Only use this class when there is a specific reason
 * to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 * @author Jon Noack
 */
@GwtIncompatible // not worth using in GWT for now

 * }
 * public void testFooLeak() {
 *   GcFinalization.awaitClear(fooWeakRef());
 * }
 * }
 *
 * <p>This class cannot currently be used to test soft references, since this class does not try to
 * create the memory pressure required to cause soft references to be cleared.
 *
 * <p>This class only provides testing utilities. It is not designed for direct use in production or
 * for benchmarking.
 *
 * @author mike nonemacher

	}

	cache := store.lock()
	defer store.unlock()

	// We should only update the in-memory cache if there were no changes
	// to the in-memory cache since the disk loading began. If there
	// were changes to the in-memory cache we should wait for the next
	// cycle until we can safely update the in-memory cache.
	//
	// An in-memory cache must be replaced only if we know for sure that the

   * 2^n}, its memory usage is only {@code O(n)}. When the power set is constructed, the input set
   * is merely copied. Only as the power set is iterated are the individual subsets created, and
   * these subsets themselves occupy only a small constant amount of memory.
   *
   * @param set the set of elements to construct a power set from

   * triggered by cancel(). For details, see the comments on the fields of TimeoutFuture.
   *
   * <p>{@code volatile} is required for j2objc transpiling:
   * https://developers.google.com/j2objc/guides/j2objc-memory-model#atomicity
   */
  private volatile @Nullable InterruptibleTask<?> task;

  TrustedListenableFutureTask(Callable<V> callable) {
    this.task = new TrustedFutureInterruptibleTask(callable);
  }

    int NT_STATUS_NOT_IMPLEMENTED = 0xC0000002;
    /** The specified information class is invalid */
    int NT_STATUS_INVALID_INFO_CLASS = 0xC0000003;
    /** Invalid access to memory location */
    int NT_STATUS_ACCESS_VIOLATION = 0xC0000005;
    /** The handle is invalid */
    int NT_STATUS_INVALID_HANDLE = 0xC0000008;
    /** The parameter is incorrect */