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.gitignore
.DS_Store .ipynb_checkpoints node_modules /.bazelrc.user /.tf_configure.bazelrc /xla_configure.bazelrc /bazel-* /bazel_pip /tools/python_bin_path.sh /tensorflow/tools/git/gen /pip_test /_python_build *.pyc __pycache__ *.swp .vscode/ cmake_build/ tensorflow/contrib/cmake/_build/ .idea/** /build/ [Bb]uild/ /build_output/ /tensorflow/core/util/version_info.cc /tensorflow/python/framework/fast_tensor_util.cpp
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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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RELEASE.md
data, or by relaxing `Input` shape assumptions (note that you can pass shapes with `None` entries for axes that are meant to be dynamic). You can also disable the input checking entirely by setting `model.input_spec = None`. * Several changes have been made to `tf.keras.mixed_precision.experimental`. Note that it is now recommended to use the non-experimental `tf.keras.mixed_precision` API.
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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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tensorflow/BUILD
# 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"}, visibility = ["//visibility:public"], ) # Non-configurable setting to indicate open source build. bool_setting( name = "oss_setting",
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tensorflow/c/BUILD
"//tensorflow/cc:while_loop", "//tensorflow/cc/saved_model:loader_lite", "//tensorflow/compiler/mlir/tfr:graph_decompose_pass", "//tensorflow/compiler/mlir/tfr:node_expansion_pass", "//tensorflow/core:core_cpu", "//tensorflow/core:core_cpu_internal", "//tensorflow/core:framework", "//tensorflow/core:lib",
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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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tensorflow/c/eager/BUILD
"//tensorflow/core/common_runtime/eager:attr_builder", "//tensorflow/core/common_runtime/eager:context", "//tensorflow/core/common_runtime/eager:copy_to_device_node", "//tensorflow/core/common_runtime/eager:eager_executor", "//tensorflow/core/common_runtime/eager:eager_operation", "//tensorflow/core/common_runtime/eager:execute",
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ci/devinfra/docker_windows/Dockerfile
[Environment]::SetEnvironmentVariable(\"PATH\", $old_path + \";C:\VS\VC\Tools\MSVC\14.33.31629\bin\Hostx64\x64;C:\VS\Common7\Tools;C:\VS\MSBuild\Current\Bin\", \"Machine\"); # Add signtool.exe to the PATH. Note this path may need to be edited if updates # are made to the Windows 10 SDK. RUN $old_path = [Environment]::GetEnvironmentVariable(\"PATH\", \"Machine\"); \
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