*   XLA reduction emitter is deterministic when the environment variable
        `TF_DETERMINISTIC_OPS` is set to "true" or "1". This extends
        deterministic `tf.nn.bias_add` back-prop functionality (and therefore
        also deterministic back-prop of bias-addition in Keras layers) to
        include when XLA JIT compilation is enabled.
    *   Fix problem, when running on a CUDA GPU and when either environment

Also allowing to have multiple alternative security schemes that are then checked in a single dependency instead of each one verifying and returning the error to the client automatically when not satisfied. PR [#134](https://github.com/tiangolo/fastapi/pull/134).

* Update [SQL Tutorial](https://fastapi.tiangolo.com/tutorial/sql-databases/#create-a-middleware-to-handle-sessions) to close database sessions even when there are exceptions. PR [#89](https://github.com/tiangolo/fastapi/pull/89)...

* Retry 'connection refused' errors when setting up clusters on GCE. ([#57394](https://github.com/kubernetes/kubernetes/pull/57394), [@mborsz](https://github.com/mborsz))
* Retry 'connection refused' errors when setting up clusters on GCE. ([#57394](https://github.com/kubernetes/kubernetes/pull/57394), [@mborsz](https://github.com/mborsz))

        def annotations = []
        jApiType.annotations >> annotations

        when:
        annotations.clear()

        then:
        rule.maybeViolation(jApiType).humanExplanation =~ 'Is not annotated with @Incubating'

        when:
        annotations.add(incubatingAnnotation)

        then:
        rule.maybeViolation(jApiType) == null

        where:
        apiElement    | jApiTypeName

    def canAddMetaData() {
        TestDomainObject value = new TestDomainObject('a')

        when:
        repository.put('class', value)

        then:
        repository.find('class') == value
        repository.get('class') == value
    }

    def findReturnsNullForUnknownClass() {
        expect:

=== Dead Section Links
This section doesn't exist: <<missing_section>>
Also see this one, which is another dead link: <<other_missing_section>>
        """

        when:
        run('checkDeadInternalLinks').buildAndFail()

        then:
        assertFoundDeadSectionLinks(sampleDoc, "missing_section", "other_missing_section")
    }

    def "validates present section links"() {
        given:

   * request, and ensure that (1/QPS) seconds have elapsed since then. For example, for a rate of
   * QPS=5 (5 tokens per second), if we ensure that a request isn't granted earlier than 200ms after
   * the last one, then we achieve the intended rate. If a request comes and the last request was
   * granted only 100ms ago, then we wait for another 100ms. At this rate, serving 15 fresh permits

   * <p>If the dataset contains {@link Double#NaN} then the result is {@link Double#NaN}. If it
   * contains {@link Double#NEGATIVE_INFINITY} and not {@link Double#NaN} then the result is {@link
   * Double#NEGATIVE_INFINITY}. If it contains {@link Double#POSITIVE_INFINITY} and finite values
   * only then the result is the lowest finite value. If it contains {@link
   * Double#POSITIVE_INFINITY} only then the result is {@link Double#POSITIVE_INFINITY}.
   *

fi
set -x

# When cross-compiling with RBE, we need to copy the macOS sysroot to be
# inside the TensorFlow root directory. We then define them as a filegroup
# target inside "tensorflow/tools/toolchains/cross_compile/cc" so that Bazel
# can register it as an input to compile/link actions and send it to the remote
# VMs when needed.

repository. During development in an IDE we would need layered resolution approach that would allow resolution from the workspace, then the local Maven repository and then from any number of remote Maven repositories. During development from the command line we would need a layered resolution approach that would allow resolution from the local Maven repository and then from any number of remote Maven repositories. In production the resolution for the dependencies could also be layered but would depend...