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ci/official/containers/linux_arm64/jax.requirements.txt
# JAX requirements, passed into container by defining the ARG # REQUIREMENTS_FILE=jax.requirements.txt setuptools wheel cloudpickle colorama>=0.4.4 matplotlib pillow>=9.1.0 rich absl-py portpicker six opt-einsum auditwheel typing_extensions importlib_metadata>=4.6 numpy==1.26.0;python_version=="3.12" numpy==1.23.4;python_version=="3.11" numpy==1.22.4;python_version<"3.11" scipy==1.11.2;python_version=="3.12"
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ci/official/containers/linux_arm64/build.sh
else TAG="pr-${KOKORO_GITHUB_PULL_REQUEST_NUMBER}" fi fi # Build for both JAX and TF usage. We do these in one place because they share # almost all of the same cache layers export DOCKER_BUILDKIT=1 for target in jax tf; do IMAGE="gcr.io/tensorflow-sigs/build-arm64:$target-$TAG" docker pull "$IMAGE" || true
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ci/official/containers/linux_arm64/Dockerfile
RUN echo $CACHEBUSTER # Setup build and environment COPY devel.usertools /usertools COPY devel.bashrc /root/.bashrc COPY ld.so.conf /dt10/etc/ # Setup JAX Python environment. FROM devel as jax RUN /setup.packages.sh /cuda.packages.txt COPY jax.requirements.txt /devel.requirements.txt COPY setup.python.sh /setup.python.sh RUN /setup.python.sh python3.9 devel.requirements.txt
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requirements_lock_3_12.txt
# h5py # jax # keras-nightly # ml-dtypes # opt-einsum # scipy # tb-nightly opt-einsum==3.3.0 \ --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \ --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549 # via # -r requirements.in # jax packaging==23.2 \
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requirements_lock_3_9.txt
# h5py # jax # keras-nightly # ml-dtypes # opt-einsum # scipy # tb-nightly opt-einsum==3.3.0 \ --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \ --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549 # via # -r requirements.in # jax packaging==23.2 \
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requirements_lock_3_10.txt
# h5py # jax # keras-nightly # ml-dtypes # opt-einsum # scipy # tb-nightly opt-einsum==3.3.0 \ --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \ --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549 # via # -r requirements.in # jax packaging==23.2 \
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ci/official/requirements_updater/requirements.in
keras-nightly ~= 3.0.0.dev tb-nightly ~= 2.17.0.a # Test dependencies grpcio >= 1.24.3, < 2.0 portpicker == 1.6.0 scipy == 1.11.3 requests == 2.31.0 packaging==23.2 setuptools==68.2.2
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.github/workflows/osv-scanner-scheduled.yml
--lockfile=requirements.txt:./requirements_lock_3_12.txt --lockfile=requirements.txt:./ci/official/containers/linux_arm64/devel.requirements.txt --lockfile=requirements.txt:./ci/official/containers/linux_arm64/jax.requirements.txt
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requirements_lock_3_11.txt
# h5py # jax # keras-nightly # ml-dtypes # opt-einsum # scipy # tb-nightly opt-einsum==3.3.0 \ --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \ --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549 # via # -r requirements.in # jax packaging==23.2 \
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tensorflow/BUILD
"//tensorflow/compiler/mlir/lite/python:flatbuffer_to_mlir", "//tensorflow/compiler/mlir/lite/python:graphdef_to_tfl_flatbuffer", "//tensorflow/compiler/mlir/lite/python:jax_to_tfl_flatbuffer", "//tensorflow/compiler/mlir/lite/python:saved_model_to_tfl_flatbuffer", "//tensorflow/compiler/mlir/lite/quantization/lite:quantize_model",
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