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tensorflow/api_template_v1.__init__.py
# The "app" module will be imported as part of the placeholder section above. _current_module.app.flags = flags # pylint: disable=undefined-variable setattr(_current_module, "flags", flags) _major_api_version = 1 # Add module aliases from Keras to TF. # Some tf endpoints actually lives under Keras. _current_module.layers = _KerasLazyLoader( globals(), submodule="__internal__.legacy.layers",
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CONTRIBUTING.md
and [tensorflow/python](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python). TensorFlow has passed version 1.0 and hence cannot make non-backward-compatible API changes without a major release. Reviewers of your pull request will comment on any API compatibility issues [following API review practices](https://github.com/tensorflow/community/blob/master/governance/api-reviews.md).
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ci/official/requirements_updater/requirements.in
dill == 0.3.7 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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tensorflow/c/eager/tfe_tensor_debug_info_internal.h
#include <vector> #include "tensorflow/core/platform/types.h" struct TFE_TensorDebugInfo { explicit TFE_TensorDebugInfo(const std::vector<int64_t>& dims) : dev_dims(dims) {} // Fully-padded, minor-to-major. std::vector<int64_t> dev_dims; };
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.github/workflows/arm-ci-extended.yml
run: | is_nightly=0 && tf_project_name='tf_ci_ext' && ${{ github.event_name == 'schedule' }} && is_nightly=1 && tf_project_name='tf_nightly_ci_ext' CI_DOCKER_BUILD_EXTRA_PARAMS="--build-arg py_major_minor_version=${{ matrix.pyver }} --build-arg is_nightly=${is_nightly} --build-arg tf_project_name=${tf_project_name}" \
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RELEASE.md
### Known Caveats * <CAVEATS REGARDING THE RELEASE (BUT NOT BREAKING CHANGES).> * <ADDING/BUMPING DEPENDENCIES SHOULD GO HERE> * <KNOWN LACK OF SUPPORT ON SOME PLATFORM, SHOULD GO HERE> ### Major Features and Improvements * <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX> * <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER> ### Bug Fixes and Other Changes
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tensorflow/c/experimental/filesystem/filesystem_interface.h
/// as well. Here is a short summary of what changes are allowed: /// * adding a new method at the end of a table is allowed at any time; /// * any other change to these tables is only allowed on a major TensorFlow /// version change (e.g., from 2.x to 3.0). This is provided as an escape /// hatch to allow cleaning up these tables. Since any of these changes
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tensorflow/BUILD
load("@bazel_skylib//rules:common_settings.bzl", "bool_flag", "bool_setting") load("@local_config_cuda//cuda:build_defs.bzl", "if_cuda") load( "//tensorflow:tensorflow.bzl", "VERSION", "VERSION_MAJOR", "check_deps", "if_google", "if_oss", "if_xla_available", "tf_cc_shared_object", "tf_custom_op_library_additional_deps_impl", "tf_monitoring_python_deps", "tf_native_cc_binary",
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.github/workflows/sigbuild-docker.yml
run: | # [[:digit:]] searches for numbers and \+ joins them together major_version=$(grep "^#define TF_MAJOR_VERSION" ./tensorflow/core/public/version.h | grep -o "[[:digit:]]\+") minor_version=$(grep "^#define TF_MINOR_VERSION" ./tensorflow/core/public/version.h | grep -o "[[:digit:]]\+") echo "TF_VERSION=${major_version}.${minor_version}" >> "$GITHUB_OUTPUT"
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configure.py
if not python_lib_path: python_lib_path = default_python_lib_path environ_cp['PYTHON_LIB_PATH'] = python_lib_path python_major_version = get_python_major_version(python_bin_path) if python_major_version == '2': write_to_bazelrc('build --host_force_python=PY2') # Convert python path to Windows style before writing into bazel.rc if is_windows() or is_cygwin():
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