the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)
and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as a
non-guaranteed backward compatible API for
[other languages](https://www.tensorflow.org/api_docs).

};

struct TF_DeprecatedSession {
  tensorflow::Session* session;
};

struct TF_Library {
  void* lib_handle;
  TF_Buffer op_list;
};

struct TF_Graph {
  TF_Graph();

  mutable tensorflow::mutex mu;
  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.

        };
    Map<String, Map<Integer, Character>> backingMap = new LinkedHashMap<>();
    Table<String, Integer, Character> table = newCustomTable(backingMap, factory);
    populate(table, data);
    return table;
  }

  public void testRowKeySetOrdering() {
    table = create("foo", 3, 'a', "bar", 1, 'b', "foo", 2, 'c');
    assertThat(table.rowKeySet()).containsExactly("foo", "bar").inOrder();
  }

  public void testRowOrdering() {

        "<p>text</p>   <p>text</p>"                        | "<p>text</p><p>text</p>"
        "<p>text</p>   <h2>text</h2> <table/>"             | "<p>text</p><h2>text</h2><table></table>"
        "  <table>  <tr>  <td>text</td> </tr>\r\n</table>" | "<table><tr><td>text</td></tr></table>"
    }

    def "does not discard whitespace around inline elements"() {
        expect:
        parse(source) == transformed

    AtomicReferenceArray<ReferenceEntry<Object, Object>> table = segment.table;
    int index = hash & (table.length() - 1);

    // already loading
    DummyEntry<Object, Object> entry = DummyEntry.create(key, hash, null);
    DummyValueReference<Object, Object> valueRef = DummyValueReference.create(null);
    valueRef.setLoading(true);
    entry.setValueReference(valueRef);
    table.set(index, entry);

    AtomicReferenceArray<ReferenceEntry<Object, Object>> table = segment.table;
    int index = hash & (table.length() - 1);

    // already loading
    DummyEntry<Object, Object> entry = DummyEntry.create(key, hash, null);
    DummyValueReference<Object, Object> valueRef = DummyValueReference.create(null);
    valueRef.setLoading(true);
    entry.setValueReference(valueRef);
    table.set(index, entry);

#             ; code=[code]; name=[name]; alias=[alias]; comment=[comment]
#             ; sisterCode=[code or code-list]; subItemMap=map:{[free-map]}
#         }
#         # settings for table classification
#         ; map:{
#             ; table=[table-name]
#             ; code=[column-name for code]; name=[column-name for name]
#             ; alias=[column-name for alias]; comment=[column-name for comment]}

 * Immutable empty instances are returned for collection types; {@code ""} for string; {@code 0} for
 * number types; reasonable default instance for other stateless types. For mutable types, a fresh
 * instance is created each time {@code get()} is called.
 *
 * @author Kevin Bourrillion
 * @author Ben Yu
 * @since 12.0
 */
@GwtIncompatible
@J2ktIncompatible
@NullMarked

Starlette (and **FastAPI**) are based on <a href="https://anyio.readthedocs.io/en/stable/" class="external-link" target="_blank">AnyIO</a>, which makes it compatible with both Python's standard library <a href="https://docs.python.org/3/library/asyncio-task.html" class="external-link" target="_blank">asyncio</a> and <a href="https://trio.readthedocs.io/en/stable/" class="external-link" target="_blank">Trio</a>.

#result .title {
	margin: 1.0em 0 0.5em 0;
	font-size: 120%;
	font-weight: 600;
}

section.content table {
	display: table;
	table-layout: fixed;
	width: 100%;
}

section.content table td {
	display: table-cell;
	word-wrap: break-word;
	overflow-wrap: break-word;
}

section.content table .label {
	color: #fff;
}

textarea.systemInfoData {
	height: 22em;
	line-height: 1.5em;
}