Toolchain resolver plugins provide logic to map a link:{javadocPath}/org/gradle/jvm/toolchain/JavaToolchainRequest.html[toolchain request] to a link:{javadocPath}/org/gradle/jvm/toolchain/JavaToolchainDownload.html[download response].
At the moment the download response only contains a download URL, but may be extended in the future.

WARNING: For the download URL only secure protocols like `https` are accepted.

Mais vous devez d'abord lire le **Tutoriel - Guide d'utilisation** (ce que vous êtes en train de lire en ce moment).

 0x6ffffef5 (GNU_HASH)                   0x1b8
 0x00000005 (STRTAB)                     0xd438
 0x00000006 (SYMTAB)                     0x3ec8
 0x0000000a (STRSZ)                      23846 (Bytes)
 0x0000000b (SYMENT)                     16 (Bytes)
 0x00000003 (PLTGOT)                     0x1a8000
 0x00000002 (PLTRELSZ)                   96 (Bytes)
 0x00000014 (PLTREL)                     REL

            package example;
            public class MyTest {
                @org.junit.Test public void foo() throws Exception {
                     Thread.sleep(100);  // sleep for a moment to ensure test duration is > 0 (due to limited clock resolution)
                     org.junit.Assert.assertEquals(1, 1);
                }
            }
        """

        when:

  }

  // Defines target component.
  QuantizationComponent quantization_component = 1;

  // Defines the target tensor type.
  TensorType tensor_type = 2;
}

// Unit-wise (op type and node name at this moment) quantization spec. It
// contains the scope of the unit, and the quantization method for each unit.
// NEXT ID: 7
message UnitWiseQuantizationSpec {
  // Quantization unit granularity.
  // NEXT ID: 4

		return false
	}
	// KEP 4191 explains that multiple filesystems for images and containers is not
	// supported at the moment.
	// See https://github.com/kubernetes/enhancements/tree/master/keps/sig-node/4191-split-image-filesystem#comment-on-future-extensions
	// for work needed to support multiple filesystems.

# relevant. All of the GPU test machines have CUDA installed via other means,
# so I am not sure how to verify that the dependencies themselves are valid for
# the moment.
if [[ "$TFCI_BAZEL_COMMON_ARGS" =~ gpu|cuda ]]; then
  echo "Checking to make sure tensorflow[and-cuda] is installable..."
  "$python" -m pip install "$(echo *.whl)[and-cuda]" $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS

	ThrottleEnable bool
	// ThrottleQPS defines the allowed rate of batches per second sent to the delegate backend.
	ThrottleQPS float32
	// ThrottleBurst defines the maximum number of requests sent to the delegate backend at the same moment in case
	// the capacity defined by ThrottleQPS was not utilized.
	ThrottleBurst int

	// Whether the delegate backend should be called asynchronously.
	AsyncDelegate bool
}

type bufferedBackend struct {

        this.scriptSourceDescription = scriptSourceDescription;
        this.location = location;
    }

    /*
        TODO change this so that we extract all the information at compile time.

        At the moment we use the transform to:

        1. validate/restrict the syntax
        2. transform rules into something more robust (e.g. foo.bar.baz {} into configure("foo.bar.baz", {})) - no dynamic propertyMissing() nonsense

                abstract String getName()
                abstract void setName(String name)
            }

            class RulePlugin extends RuleSource {
                @Model
                void someone(Person person) {
                }

                @Mutate
                void tasks(ModelMap<Task> tasks, Person person) {
                    println person.unknown
                }
            }