# TF now has `cc_shared_library` targets, so it needs the experimental flag
# TODO(rostam): Remove when `cc_shared_library` is enabled by default
build --experimental_cc_shared_library

# cc_shared_library ensures no library is linked statically more than once.
build --experimental_link_static_libraries_once=false

# Prevent regressions on those two incompatible changes
# TODO: remove those flags when they are flipped in the default Bazel version TF uses.

        "//conditions:default": [],
    }),
    tags = [
        "no_cuda_asan",  # TODO(b/181771536)
        "no_windows",  # TODO(b/155444728)
    ],
    # We must ensure that the dependencies can be dynamically linked since
    # the shared library must be able to use core:framework.
    deps = [
        ":c_api",
        ":c_api_internal",
        ":c_test_util",
        ":test_op_kernel",
        ":tf_buffer",

  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  TF_GraphCopyFunction(host_graph_, grad_func, nullptr, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Check that functions are added but not linked
  GraphDef gdef;
  GetGraphDef(host_graph_, &gdef);
  std::vector<string> func_names = GetFuncNames(gdef);
  ASSERT_EQ(2, func_names.size());
  ASSERT_EQ("FooFunc", func_names[0]);

                "//tensorflow/core:lib_internal_impl",
                "//tensorflow/core/profiler:profiler_impl",
                "//tensorflow/core/util:determinism",  # Must be linked and exported to libtensorflow_framework.so.
                "//tensorflow/lite/kernels/shim:tf_kernel_shim",
                "@local_xla//xla/stream_executor:stream_executor_impl",

    format(`tf.contrib.saved_model.save_keras_model()`) and used with Tensorflow
    Serving.
*   Keras models now support evaluating with a `tf.data.Dataset`.
*   TensorFlow binaries are built with XLA support linked in by default.
*   Ignite Dataset added to contrib/ignite that allows to work with Apache
    Ignite.

## Bug Fixes and Other Changes

*   tf.data: