# Test dependencies
grpcio >= 1.68.1, < 2.0
portpicker == 1.6.0
# Scipy 15.x and above have misc.derivative removed, but we still use it
scipy >= 1.13.0, < 1.15.0
requests >= 2.31.0
packaging==23.2
setuptools==78.1.1
jax==0.4.7
zstandard==0.23.0
# The dependencies below are needed for TF wheel testing.
tensorflow-io-gcs-filesystem==0.37.1 ; python_version <= "3.12"
libclang >= 13.0.0
google_pasta ~= 0.2

    #   keras-nightly
idna==3.10 \
    --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
    # via requests
jax==0.4.7 \
    --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8
    # via -r ci/official/requirements_updater/requirements.in
keras-nightly==3.10.0.dev2025072304 \

# For wheel verification, and uploading
auditwheel ~= 6.1.0
twine ~= 6.1.0
id
urllib3
requests

# For JAX
build ~= 1.2.2
# uv is faster than pip for installing Python packages.
uv ~= 0.5.30

# For running wheel verification script

importlib-metadata==8.6.1 \
    --hash=sha256:02a89390c1e15fdfdc0d7c6b25cb3e62650d0494005c97d6f148bf5b9787525e \
    --hash=sha256:310b41d755445d74569f993ccfc22838295d9fe005425094fad953d7f15c8580
    # via markdown
jax==0.4.7 \
    --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8
    # via -r ci/official/requirements_updater/requirements.in
keras-nightly==3.10.0.dev2025052003 \

    #   keras-nightly
idna==3.10 \
    --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
    # via requests
jax==0.4.7 \
    --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8
    # via -r ci/official/requirements_updater/requirements.in
keras-nightly==3.10.0.dev2025072304 \

    #   keras-nightly
idna==3.10 \
    --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
    # via requests
jax==0.4.7 \
    --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8
    # via -r ci/official/requirements_updater/requirements.in
keras-nightly==3.10.0.dev2025072304 \

    #   keras-nightly
idna==3.10 \
    --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
    # via requests
jax==0.4.7 \
    --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8
    # via -r ci/official/requirements_updater/requirements.in
keras-nightly==3.10.0.dev2025072304 \

reachable and exploitable through production-grade, benign models.

### Compilation

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)
documentation should be safe, while some of the testing and debugging tools that
come with the compiler are not designed to be used with untrusted data and

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

    #   keras-nightly
idna==3.10 \
    --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
    # via requests
jax==0.4.7 \
    --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8
    # via -r ci/official/requirements_updater/requirements.in
keras-nightly==3.10.0.dev2025072304 \