# This bazelrc can build a CPU-supporting TF package.

# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false

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Follow either of the two links above to access the appropriate CLA and instructions for how to sign and return it. Once we receive it, we'll be able to accept your pull requests.

code in context of the TensorFlow service, it is important to design isolation
mechanisms that prevent unwanted access to the data from other tenants.

Network isolation between different models is also important not only to prevent
unauthorized access to data or models, but also to prevent malicious users or
tenants sending graphs to execute under another tenant’s identity.

        mode. In this mode, the table resource can only be accessed via resource
        handles (not resource names) and will be deleted automatically when all
        resource handles pointing to it are gone.
*   `tf.data`:
    *   Introduce the `tf.data.experimental.at` API which provides random access
        for input pipelines that consist of transformations that support random

# This bazelrc can build a CPU-supporting TF package.

# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false