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tensorflow/c/eager/c_api_unified_experimental_test.cc
TF_AbstractFunction* func = TF_FinalizeFunction(graph_ctx, add_outputs, status.get()); ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get()); // Note: TF_OutputList does not own the underlying AbstractTensors, those // need to be deleted explicitly. TF_DeleteAbstractTensor(TF_OutputListGet(add_outputs, 0)); // Build eager context.
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CONTRIBUTING.md
for details. #### Running doctest for testable docstring There are two ways to test the code in the docstring locally: 1. If you are only changing the docstring of a class/function/method, then you can test it by passing that file's path to [tf_doctest.py](https://www.tensorflow.org/code/tensorflow/tools/docs/tf_doctest.py). For example: ```bash
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tensorflow/c/eager/tfe_op_attrs_internal.h
typedef struct TFE_Context TFE_Context; typedef struct TFE_Op TFE_Op; namespace tensorflow { DEFINE_CONVERSION_FUNCTIONS(tensorflow::AbstractOpAttrs, TFE_OpAttrs); // Set an AttrValue on the op. Doesn't handle the list types. void SetOpAttrValueScalar(TFE_Context* ctx, TFE_Op* op, const tensorflow::AttrValue& default_value, const char* attr_name, TF_Status* status);
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ci/official/requirements_updater/README.md
dependencies are always used. \ See https://github.com/bazelbuild/rules_python/ for more details. ### Specifying the Python version Note: Only a number of minor Python versions are supported at any given time. By default, the lowest supported version is used. To set a different version, use the `TF_PYTHON_VERSION` environment variable, e.g. ``` export TF_PYTHON_VERSION=3.11 ```
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
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 \ --experimental_cc_shared_library \ --@local_config_cuda//:enable_cuda \ "somepath(//tensorflow/tools/pip_package:build_pip_package, " \
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.github/workflows/sigbuild-docker-presubmit.yml
Re-apply the `build and push to gcr.io for staging` label to rebuild and push again. This comment will only be posted once. - name: Print image digest
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RELEASE.md
constructed with argument `reuse=True`. * Deprecated contrib/distributions `pmf`, `pdf`, `log_pmf`, `log_pdf`. * Moved `bayesflow.special_math` to distributions. * `tf.contrib.tensor_forest.python.tensor_forest.RandomForestDeviceAssigner` removed. * Changed some MVN classes and parameters: * `tf.contrib.distributions.MultivariateNormalFull` replaced by
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ci/official/utilities/repack_libtensorflow.sh
# into a srcjar directly under the root. There doesn't appear to be a # simple way to parameterize this from bazel, hence this helper to # "normalize" the srcjar layout. # # Arguments: # src_jar - path to the original srcjar # dest_jar - path to the destination # Returns: # None function cp_normalized_srcjar() { src_jar="$1" dest_jar="$2" tmp_dir=$(mktemp -d) cp "${src_jar}" "${tmp_dir}/orig.jar"
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.github/workflows/update-rbe.yml
- name: Update the RBE Configs run: | function map() { # The "digest" that allows us to pull an image is not the digest as # returned by the API, but a sha256sum of the entire chunk of image # metadata. gcr.io helpfully includes it in the header of the response # as docker-content-digest: sha256:[digest]. Note we use egrep to # match exactly sha256:<hash> because curl may include a ^M symbol at
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.github/workflows/sigbuild-docker.yml
cache-from: type=registry,ref=tensorflow/build:latest-${{ matrix.python-version }} cache-to: type=inline - name: Image digest
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