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ci/official/containers/linux_arm64/devel.usertools/squash_testlogs.py
p.text += "\n Most TF jobs run tests three times to root out flakes." if seen[key] == 3: p.text += ( "\n Since there were three failures, this is not flaky, and it" ) p.text += "\n probably caused the Kokoro invocation to fail." else: p.text += ( "\n Since there were not three failures, this is probably a flake." ) p.text += (
Python - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Mon Sep 18 19:00:37 GMT 2023 - 4.8K bytes - Viewed (0) -
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
Plain Text - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Jan 10 19:39:41 GMT 2024 - 2K bytes - Viewed (0) -
.github/ISSUE_TEMPLATE/tflite-other.md
build/installation issues on GitHub. - type: markdown attributes: value: |
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ci/official/wheel_test/README.md
These tests use hermetic Python. They also require a built TensorFlow wheel file and a requirements_lock file. The requirements_lock file is generated by the [requirements_updater](https://github.com/tensorflow/tensorflow/tree/master/ci/official/requirements_updater) tool using the path to this wheel file. ### Hermetic Python For details about hermetic Python and setting its toolchain version, see
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tensorflow/api_template.__init__.py
_tf2.enable() # API IMPORTS PLACEHOLDER # WRAPPER_PLACEHOLDER # Make sure directory containing top level submodules is in # the __path__ so that "from tensorflow.foo import bar" works. # We're using bitwise, but there's nothing special about that. _API_MODULE = _sys.modules[__name__].bitwise _tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__)) _current_module = _sys.modules[__name__]
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 05 06:27:59 GMT 2024 - 6.7K bytes - Viewed (3) -
ci/official/requirements_updater/updater.sh
# limitations under the License. # ============================================================================== # script to run pip-compile for each requirement. # if there is a change in requirements.in then all lock files will be updated # accordingly # All commands run relative to this directory cd "$(dirname "${BASH_SOURCE[0]}")" mv BUILD.bazel BUILD
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ci/official/utilities/cleanup_summary.sh
# and don't print duplicates awk '/Streaming build results to/ {print $NF}' "$TFCI_OUTPUT_DIR/script.log" | uniq } # Print out any ResultStore URLs for Bazel invocations' results. # Each failed target there will have its own representation, making failures # easier to find and read. function resultstore_extract { local \ XML_PATH="$TFCI_OUTPUT_DIR/Bazel_Test_and_Build_Results/sponge_log.xml" python3 \
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Nov 08 17:50:27 GMT 2023 - 1.8K bytes - Viewed (0) -
ci/official/wheel_test/update_requirements.sh
# limitations under the License. # ============================================================================== # 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
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tensorflow/api_template_v1.__init__.py
Otherwise your code may be broken by the change. """) # Make sure directory containing top level submodules is in # the __path__ so that "from tensorflow.foo import bar" works. # We're using bitwise, but there's nothing special about that. _API_MODULE = _sys.modules[__name__].bitwise # pylint: disable=undefined-variable _current_module = _sys.modules[__name__] _tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__))
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Jan 23 02:14:00 GMT 2024 - 7.4K bytes - Viewed (0) -
SECURITY.md
targets of those operations, which could result in arbitrary read/write/executions. ### Running a TensorFlow server TensorFlow is a platform for distributed computing, and as such there is a TensorFlow server (`tf.train.Server`). The TensorFlow server is intended for internal communication only. It is not built for use in untrusted environments or networks.
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