selectHighestVersion()
        }
    }
}

fun readCapabilitiesFromJson() {
    val capabilitiesFile = repoRoot().file("gradle/dependency-management/capabilities.json").asFile
    val capabilities: List<CapabilitySpec> = readCapabilities(capabilitiesFile)
    capabilities.forEach {
        it.configure(dependencies.components, configurations)
    }
}

fun readCapabilities(source: File): List<CapabilitySpec> {

        client.execute(action, request, listener);
    }

    /**
     * Prepares a field capabilities request builder.
     *
     * @param indices the indices to check field capabilities for
     * @return the field capabilities request builder
     */
    @Override
    public FieldCapabilitiesRequestBuilder prepareFieldCaps(final String... indices) {

common:cuda_clang --config=cuda
common:cuda_clang --@local_config_cuda//:cuda_compiler=clang
common: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

*   Added warmup capabilities to `tf.keras.optimizers.schedules.CosineDecay` learning rate scheduler. You can now specify an initial and target learning rate, and our scheduler will perform a linear interpolation between the two after which it will begin a decay phase.