// The new graph construction API, still under development.

// Represents a computation graph.  Graphs may be shared between sessions.
// Graphs are thread-safe when used as directed below.
typedef struct TF_Graph TF_Graph;

// Return a new graph object.
TF_CAPI_EXPORT extern TF_Graph* TF_NewGraph(void);

// Destroy an options object. Graph will be deleted once no more

 *
 * <p>Usage example:
 *
 * {@snippet :
 * LoadingCache<Key, Graph> graphs = CacheBuilder.newBuilder()
 *     .maximumSize(10000)
 *     .expireAfterWrite(Duration.ofMinutes(10))
 *     .removalListener(MY_LISTENER)
 *     .build(
 *         new CacheLoader<Key, Graph>() {
 *           public Graph load(Key key) throws AnyException {
 *             return createExpensiveGraph(key);
 *           }

  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Create a simple graph.
  Placeholder(graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_TRUE(TF_GraphOperationByName(graph, "feed") != nullptr);
  TF_Operation* oper = ScalarConst(3, graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_TRUE(TF_GraphOperationByName(graph, "scalar") != nullptr);
  Neg(oper, graph, s);

/*!
  * Bootstrap v5.3.0 (https://getbootstrap.com/)
  * Copyright 2011-2023 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)
  * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)
  */

/*!
  * Bootstrap v4.6.2 (https://getbootstrap.com/)
  * Copyright 2011-2022 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)
  * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)
  */

  // Verify that functions and their gradients are in host graph's GraphDef
  GraphDef gdef;
  GetGraphDef(host_graph_, &gdef);
  std::vector<std::pair<string, string>> grads = GetGradDefs(gdef);
  ASSERT_EQ(2, grads.size());
  ASSERT_EQ("FooFunc1", grads[0].first);
  ASSERT_EQ("MyGrad", grads[0].second);
  ASSERT_EQ("FooFunc2", grads[1].first);
  ASSERT_EQ("MyGrad", grads[1].second);

  TF_DeleteFunction(func1);

				"application/vnd.oasis.opendocument.database",
				"application/vnd.oasis.opendocument.formula",
				"application/vnd.oasis.opendocument.formula-template",
				"application/vnd.oasis.opendocument.graphics",
				"application/vnd.oasis.opendocument.graphics-template",
				"application/vnd.oasis.opendocument.image",
				"application/vnd.oasis.opendocument.image-template",
				"application/vnd.oasis.opendocument.presentation",

    private static final String META_NAME_THUMBNAIL_CONTENT = "//META[@name=\"thumbnail\" or @name=\"THUMBNAIL\"]/@content";

    /** XPath expression for extracting Open Graph image content from meta tags */
    private static final String META_PROPERTY_OGIMAGE_CONTENT = "//META[@property=\"og:image\"]/@content";

    /** XPath expression for extracting robots content from meta tags */

build:cuda_clang --config=cuda
build:cuda_clang --@local_config_cuda//:cuda_compiler=clang
build:cuda_clang --copt=-Qunused-arguments
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX

 * article on <a href="https://github.com/google/guava/wiki/ListenableFutureExplained">{@code
 * ListenableFuture}</a>.
 *
 * <p>The main purpose of {@code ListenableFuture} is to help you chain together a graph of
 * asynchronous operations. You can chain them together manually with calls to methods like {@link
 * Futures#transform(ListenableFuture, Function, Executor) Futures.transform}, but you will often