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ci/official/utilities/code_check_changed_files.bats
# Note: this is excluded on the full code base, since any submitted code must # have passed Google's internal style guidelines. @test "Check buildifier formatting on BUILD files" { echo "buildifier formatting is recommended. Here are the suggested fixes:" echo "=============================" grep -e 'BUILD' $BATS_FILE_TMPDIR/changed_files \ | xargs buildifier -v -mode=diff -diff_command="git diff --no-index" }
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ci/official/envs/rbe
# TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX. "Available" means there is # an entry in tensorflow/.bazelrc for build:rbe_TFCI_BAZEL_TARGET... # ^^^^ # This env is only valid when RBE is available on the selected platform, since # it enables a derived --config setting. If RBE is not available (i.e. there # is no --config setting), bazel would fail and quit. This script does a quick
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ci/official/requirements_updater/requirements.in
astor == 0.7.1 typing_extensions == 4.8.0 gast == 0.4.0 termcolor == 2.3.0 wrapt == 1.16.0 tblib == 2.0.0 # Install tensorboard, and keras # Note that here we want the latest version that matches TF major.minor version # Note that we must use nightly here as these are used in nightly jobs # For release jobs, we will pin these on the release branch keras-nightly ~= 3.0.0.dev tb-nightly ~= 2.17.0.a # Test dependencies
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ci/official/requirements_updater/README.md
be required before going through the steps below. This is due to the new Python versions becoming available through `rules-python`. \ See [here](https://github.com/tensorflow/tensorflow/commit/f91457f258fdd78f693044a57efa63a38335d1de), and [here](https://github.com/tensorflow/tensorflow/commit/052445e04ce20fd747657e0198a1bcec2b6dff5b), for an example. See
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ci/official/README.md
against a pending change. Search for "MLCI" internally to find it. You may invoke a CI script of your choice by following these instructions: ```bash cd tensorflow-git-dir # Here is a single-line example of running a script on Linux to build the # GPU version of TensorFlow for Python 3.12, using the public TF bazel cache and # a local build cache:
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tensorflow/c/eager/dlpack.cc
} dlm_tensor->dl_tensor.shape = shape_arr->data(); // There are two ways to represent compact row-major data // 1) nullptr indicates tensor is compact and row-majored. // 2) fill in the strides array as the real case for compact row-major data. // Here we choose option 2, since some frameworks didn't handle the strides // argument properly.
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tensorflow/c/experimental/gradients/array_grad_test.cc
}; TEST_P(CppGradients, TestIdentityNGrad) { // This test is interesting because the current implementation of GradientTape // would return [0, 1] whereas we use build_default_zeros_grads=false here // so we get back [nullptr, 1]. AbstractTensorHandlePtr x1; { AbstractTensorHandle* x1_raw = nullptr; status_ = TestScalarTensorHandle<float, TF_FLOAT>(
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ci/official/utilities/code_check_full.bats
cat <<EOF There was a path found connecting //tensorflow/tools/pip_package:wheel to a banned CUDA dependency when '--define framework_shared_object=false' is set. This means that a CUDA target was probably included via an is_static condition, used when targeting platforms like Windows where we build statically instead of dynamically. Here's the output from bazel query: EOF cat $BATS_TEST_TMPDIR/out
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tensorflow/api_template.__init__.py
def _running_from_pip_package(): return any( _current_file_location.startswith(dir_) for dir_ in _site_packages_dirs) if _running_from_pip_package(): # TODO(gunan): Add sanity checks to loaded modules here. # Load first party dynamic kernels. _tf_dir = _os.path.dirname(_current_file_location) _kernel_dir = _os.path.join(_tf_dir, "core", "kernels") if _os.path.exists(_kernel_dir):
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tensorflow/c/eager/c_api.cc
// TODO(b/175427838): It would be nice to be able to use tensorflow::isa here. if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) { return tensorflow::down_cast<tensorflow::CustomDeviceTensorHandle*>( unwrapped_handle) ->DevicePointer(); } // TODO(b/175427838): It would be nice to be able to use tensorflow::isa here. if (!tensorflow::TensorHandle::classof(unwrapped_handle)) {
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