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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# use the wheel's TensorFlow installation instead of the one made available # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. # # Pass --config=pip to run the same suite of tests. If you want to run just one # test for investigation, you'll need --config=pip_venv instead, and then you
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
# it, and print that list for debugging. Not really clear if this is # helpful since the only examples I've seen are enormous. bazel query "rdeps(kind(py_test, $(cat $BATS_TEST_TMPDIR/deps)), $dep, 1)" done < $BATS_TEST_TMPDIR/missing_deps exit 1 fi } # The Python package is not allowed to depend on any CUDA packages. @test "Pip package doesn't depend on CUDA" { bazel cquery \
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# use the wheel's TensorFlow installation instead of the one made available # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. # # Pass --config=pip to run the same suite of tests. If you want to run just one # test for investigation, you'll need --config=pip_venv instead, and then you
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ci/official/utilities/code_check_full.bats
# it, and print that list for debugging. Not really clear if this is # helpful since the only examples I've seen are enormous. bazel cquery "rdeps(kind(py_test, $(cat $BATS_TEST_TMPDIR/deps)), $dep, 1)" done < $BATS_TEST_TMPDIR/missing_deps exit 1 fi } # The Python package is not allowed to depend on any CUDA packages. @test "Pip package doesn't depend on CUDA" { bazel cquery \
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tensorflow/BUILD
d="$${d#*external/farmhash_archive/src}" d="$${d#*external/$${extname}/}" d="$${d#_virtual_includes/*/}" fi mkdir -p "$@/$${d}" cp "$${f}" "$@/$${d}/" done """, tags = ["manual"], visibility = ["//visibility:public"], ) # copybara:comment_begin(oss-only) copy_file( name = "root_init_gen", src = select({
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RELEASE.md
of built-in training loops such as `tf.keras` `compile` and `fit`, we expect reduction value to be `SUM` or `NONE`. Using `AUTO` in that case will raise an error. * `NONE`: Weighted losses with one dimension reduced (axis=-1, or axis specified by loss function). When this reduction type used with built-in
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.bazelrc
# Do not risk cache corruption. See: # https://github.com/bazelbuild/bazel/issues/3360 build:linux --experimental_guard_against_concurrent_changes # Configure short or long logs build:short_logs --output_filter=DONT_MATCH_ANYTHING build:verbose_logs --output_filter= # Instruction set optimizations # TODO(gunan): Create a feature in toolchains for avx/avx2 to # avoid having to define linux/win separately.
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README.md
**Raspberry Pi 2 and 3** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.html) | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv7l.whl)
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