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RELEASE.md
* XLA reduction emitter is deterministic when the environment variable `TF_DETERMINISTIC_OPS` is set to "true" or "1". This extends deterministic `tf.nn.bias_add` back-prop functionality (and therefore also deterministic back-prop of bias-addition in Keras layers) to include when XLA JIT compilation is enabled. * Fix problem, when running on a CUDA GPU and when either environment
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CONTRIBUTING.md
* If you are an individual writing original source code and you're sure you own the intellectual property, then you'll need to sign an [individual CLA](https://code.google.com/legal/individual-cla-v1.0.html). * If you work for a company that wants to allow you to contribute your work, then you'll need to sign a [corporate CLA](https://code.google.com/legal/corporate-cla-v1.0.html).
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ci/official/utilities/setup_macos.sh
fi set -x # When cross-compiling with RBE, we need to copy the macOS sysroot to be # inside the TensorFlow root directory. We then define them as a filegroup # target inside "tensorflow/tools/toolchains/cross_compile/cc" so that Bazel # can register it as an input to compile/link actions and send it to the remote # VMs when needed.
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tensorflow/c/eager/c_api_experimental.h
// APIs for generically dealing with op attributes (e.g. when forwarding them // through custom device implementations). // // TODO(allenl): Currently these are black boxes, but we should have some way to // inspect values. This would let people e.g. copy over most attributes and then // modify some based on their values. // A reference to an op's name -> attribute mapping
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ci/official/README.md
# # Bazel will cache your builds in tensorflow/build_output/cache, # and will also try using public build cache results to speed up # your builds. This usually saves a lot of time, especially when # re-running tests. However, note that: # # - New environments like new CUDA versions, changes to manylinux, # compilers, etc. can cause undefined behavior such as build failures # or tests passing incorrectly.
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WORKSPACE
# # The cascade of load() statements and tf_workspace?() calls works around the # restriction that load() statements need to be at the top of .bzl files. # E.g. we can not retrieve a new repository with http_archive and then load() # a macro from that repository in the same file. load("@//tensorflow:workspace3.bzl", "tf_workspace3") tf_workspace3() load("@//tensorflow:workspace2.bzl", "tf_workspace2") tf_workspace2()
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tensorflow/BUILD
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tensorflow/c/eager/dlpack.cc
#include "tensorflow/core/platform/logging.h" namespace tensorflow { namespace { // Managing context for the DLManagedTensor, will manage the lifetime of // DLManagedTensor. When calling DLManagedTensor::deleter, it will notify the // original framework of destruction, and this context will be deleted also. struct TfDlManagedTensorCtx { TensorReference reference; std::vector<int64_t> shape;
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ci/official/utilities/rename_and_verify_wheels.sh
# Puts new wheel through auditwheel to rename and verify it, deletes the old # one, checks the filesize, and then ensures the new wheel is installable. set -euxo pipefail cd "$TFCI_OUTPUT_DIR" # Move extra wheel files somewhere out of the way. This script # expects just one wheel file to exist. if [[ "$(ls *.whl | wc -l | tr -d ' ')" != "1" ]]; then echo "More than one wheel file is present: moving the oldest to"
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ci/official/wheel.sh
source "${BASH_SOURCE%/*}/utilities/setup.sh" # Record GPU count and CUDA version status if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then tfrun nvidia-smi fi # Update the version numbers for Nightly only if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly # replace tensorflow to tf_nightly in the wheel name
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