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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
test --test_timeout=500,900,-1,-1 # Give only the list of failed tests at the end of the log test --test_summary=short # "nonpip" tests are regular py_test tests. # Pass --config=nonpip to run the same suite of tests. If you want to run just # one test for investigation, you don't need --config=nonpip; just run the # bazel test invocation as normal.
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CONTRIBUTING.md
initiates CI/CD tests. - We can't move forward if these tests fail. - In such situations, we may request you to make further changes to your PR for the tests to pass. - Once the tests pass, we now bring all the code into the internal code base, using a job called "copybara". **5. Copy to Google Internal codebase and run internal CI**
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tensorflow/c/BUILD
"//tensorflow/cc:while_loop", "//tensorflow/cc/saved_model:loader_lite", "//tensorflow/compiler/mlir/tfr:graph_decompose_pass", "//tensorflow/compiler/mlir/tfr:node_expansion_pass", "//tensorflow/core:core_cpu", "//tensorflow/core:core_cpu_internal", "//tensorflow/core:framework", "//tensorflow/core:lib",
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
test --test_timeout=500,900,-1,-1 # Give only the list of failed tests at the end of the log test --test_summary=short # "nonpip" tests are regular py_test tests. # Pass --config=nonpip to run the same suite of tests. If you want to run just # one test for investigation, you don't need --config=nonpip; just run the # bazel test invocation as normal.
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RELEASE.md
* Add TensorSpec to represent the specification of Tensors. * Constant folding pass is now deterministic. * Support `float16` `dtype` in `tf.linalg.*`. * Add `tf.estimator.export.TensorServingInputReceiver` that allows `tf.estimator.Estimator.export_savedmodel` to pass raw tensors to model functions. ## Deprecations
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
[[ ! -s $BATS_FILE_TMPDIR/repeats ]] } # It's unclear why, but running this on //tensorflow/... is faster than running # only on affected targets, usually. There are targets in //tensorflow/lite that # don't pass --nobuild, so they're on their own. # # Although buildifier checks for formatting as well, "bazel build nobuild" # checks for cross-file issues like bad includes or missing BUILD definitions. #
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ci/official/utilities/code_check_full.bats
[[ ! -s $BATS_FILE_TMPDIR/repeats ]] } # It's unclear why, but running this on //tensorflow/... is faster than running # only on affected targets, usually. There are targets in //tensorflow/lite that # don't pass --nobuild, so they're on their own. # # Although buildifier checks for formatting as well, "bazel build nobuild" # checks for cross-file issues like bad includes or missing BUILD definitions. #
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.bazelrc
# This is the same as the official TensorFlow builds. # See https://developer.nvidia.com/cuda-gpus#compute # `compute_XY` enables PTX embedding in addition to SASS. PTX # is forward compatible beyond the current compute capability major # release while SASS is only forward compatible inside the current # major release. Example: sm_80 kernels can run on sm_89 GPUs but
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README.md
desired TensorFlow version, for example, branch `r2.8` for version 2.8. * Apply (that is, cherry-pick) the desired changes and resolve any code conflicts. * Run TensorFlow tests and ensure they pass. * [Build](https://www.tensorflow.org/install/source) the TensorFlow pip package from source. ## Continuous build status You can find more community-supported platforms and configurations in the
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