# Details: https://github.com/google-ml-infra/rules_ml_toolchain
tf_http_archive(
    name = "rules_ml_toolchain",
    sha256 = "f2c924e85a22ba2eaa0c08657e5f5467fedbc3d0506f9cc0c69dd97ed9fbaf28",
    strip_prefix = "rules_ml_toolchain-99c43dfe995a0e81c767d5b6d686191992672fe6",
    urls = tf_mirror_urls(

        shell: bash
        run: util/gradle_integration_tests.sh

  publish_snapshot:
    name: 'Publish snapshot'
    needs: test
    if: github.event_name == 'push' && github.repository == 'google/guava'
    runs-on: ubuntu-latest
    steps:
      - name: 'Check out repository'
        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
      - name: 'Set up JDKs'

    match_all = [
        ":is_cuda_enabled",
        ":windows",
    ],
)

# Config setting to use in select()s to distinguish open source build from
# google internal build on configurable attributes.
#
# For non-configurable distinction between OSS and Google builds, see
# `if_oss()` and `if_google()` macros in tensorflow.bzl.
config_setting(
    name = "oss",
    flag_values = {":oss_setting": "True"},

researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)

 * limitations under the License.
 */

package com.google.common.graph;

import static com.google.common.base.Preconditions.checkArgument;
import static com.google.common.base.Preconditions.checkNotNull;
import static com.google.common.graph.Graphs.checkNonNegative;

import com.google.errorprone.annotations.CanIgnoreReturnValue;

/**

 * limitations under the License.
 */

package com.google.common.graph;

import static com.google.common.base.Preconditions.checkArgument;
import static com.google.common.base.Preconditions.checkNotNull;
import static com.google.common.graph.Graphs.checkNonNegative;

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import com.google.errorprone.annotations.DoNotMock;

/**

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.common.graph;

import static com.google.common.base.Preconditions.checkNotNull;
import static com.google.common.graph.Graphs.checkNonNegative;

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import org.jspecify.annotations.Nullable;

/**

    /**
     * Storage region for S3.
     * AWS region where the S3 bucket is located.
     */
    @Size(max = 100)
    public String storageRegion;

    /**
     * GCS project ID.
     * Google Cloud project ID for GCS storage.
     */
    @Size(max = 200)
    public String storageProjectId;

    /**
     * Storage credentials file path for GCS.

        [Installing TensorFlow on Ubuntu](https://www.tensorflow.org/install/install_linux#tensorflow_gpu_support)
*   Google Cloud TPU:
    *   Experimental tf.data integration for Keras on Google Cloud TPUs.
    *   Experimental / preview support for eager execution on Google Cloud TPUs.
*   DistributionStrategy:
    *   Add multi-GPU DistributionStrategy support in tf.keras. Users can now

			<artifactId>commonmark-ext-yaml-front-matter</artifactId>
			<version>${commonmark.version}</version>
		</dependency>
		<dependency>
			<groupId>com.google.cloud</groupId>
			<artifactId>google-cloud-storage</artifactId>
			<version>${google.cloud.storage.version}</version>
		</dependency>
		<dependency>
			<groupId>org.junit.jupiter</groupId>
			<artifactId>junit-jupiter</artifactId>