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tensorflow/c/eager/parallel_device/parallel_device_remote_test.cc
TensorHandlePtr value_one(FloatTensorHandle(3., status.get())); ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get()); TensorHandlePtr value_two(FloatTensorHandle(-2., status.get())); ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get()); std::array<TFE_TensorHandle*, 2> in_components{value_one.get(),
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ci/official/containers/linux_arm64/devel.usertools/setup_venv_test.sh
# ============================================================================== set -euxo pipefail # Run this from inside the tensorflow github directory. # Usage: setup_venv_test.sh venv_and_symlink_name "glob pattern for one wheel file" # Example: setup_venv_test.sh bazel_pip "/tf/pkg/*.whl" # # This will create a venv with that wheel file installed in it, and a symlink # in ./venv_and_symlink_name/tensorflow to ./tensorflow. We use this for the
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CONTRIBUTING.md
airtime before a decision is made regarding whether they are to be migrated to the core. * As every PR requires several CPU/GPU hours of CI testing, we discourage submitting PRs to fix one typo, one warning,etc. We recommend fixing the same issue at the file level at least (e.g.: fix all typos in a file, fix all compiler warnings in a file, etc.) * Tests should follow the
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.github/ISSUE_TEMPLATE/tflite-converter-issue.md
- TensorFlow installation (pip package or built from source): - TensorFlow library (version, if pip package or github SHA, if built from source): ### 2. Code Provide code to help us reproduce your issues using one of the following options: #### Option A: Reference colab notebooks
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tensorflow/c/experimental/filesystem/filesystem_interface.h
/// same filesystem and the malicious one loads before the legimitate one - /// but we consider this to be something that users should care about and /// manage themselves). In both of these cases, core TensorFlow looks for /// the `TF_InitPlugin` symbol and calls this function. /// /// For every filesystem URI scheme that this plugin supports, the plugin must /// add one `TF_FilesystemPluginInfo` entry in `plugin_info->ops` and call
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ci/official/wheel_test/update_requirements.sh
# script to run pip-compile for keras, tensorboard, estimator deps. # if there is a change in requirements.in then all lock files will be updated # accordingly. # -e: abort script if one command fails # -u: error if undefined variable used # -o pipefail: entire command fails if pipe fails. watch out for yes | ... # -o history: record shell history set -euo pipefail -o history # Check for required arguments
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tensorflow/c/eager/gradients.h
// watched inputs. void Watch(const AbstractTensorHandle*); // Records an operation with given inputs and outputs // on the tape and marks all its outputs as watched if at // least one input of the op is watched and has a trainable dtype. // op_name is optional and is used for debugging only. void RecordOperation(absl::Span<AbstractTensorHandle* const> inputs,
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
bazel query --keep_going 'kind(py_test, //tensorflow/python/...) - attr("tags", "no_pip|manual", //tensorflow/python/...)' | grep -v -f $BATS_TEST_TMPDIR/ignore_deps_for_these_packages | paste -sd "+" - > $BATS_TEST_TMPDIR/deps # Find all one-step dependencies of those tests which are from //tensorflow # (since external deps will come from Python-level pip dependencies), # excluding dependencies and files that are known to be unneccessary.
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SECURITY.md
implement, and therefore security issues deriving from their absence are not considered a vulnerability in TensorFlow. ### Resource allocation A denial of service caused by one model could bring down the entire server, but we don't consider this as a vulnerability, given that models can exhaust resources in many different ways and solutions exist to prevent this from
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tensorflow/c/eager/c_api_unified_experimental.h
int TF_OutputListNumOutputs(TF_OutputList* o); // Return the `i`th output in the list. TF_AbstractTensor* TF_OutputListGet(TF_OutputList* o, int i); // Append a tensor at the end of the output list, growing its size by one. void TF_OutputListPushBack(TF_OutputList* o, TF_AbstractTensor* tensor, TF_Status*); // TF_ExecuteOperation will, if in eager mode, execute, if in graph mode, maybe
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