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ci/official/wheel_test/README.md
to the `../wheel_test/` directory. ### How it Works in the Presubmit Job `_requirements_lock` files will be generated by the presubmit job. A detailed description will be provided once it's integrated into presubmit. ### test_import_api_packages This Python test verifies whether the API v2 packages can be imported from the current build. It utilizes the `_api/v2/api_packages.txt` list of packages from
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tensorflow/c/experimental/gradients/nn_grad_test.cc
// Although, `ops::SparseSoftmaxCrossEntropyWithLogits` returns 2 tensors, the // second tensor isn't needed for computing gradient so we could safely drop // it. outputs[0] = loss; backprop->Unref(); return absl::OkStatus(); } Status BiasAddModel(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 8.3K bytes - Viewed (0) -
ci/official/envs/rbe
# 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 # check This script checks for such errors early
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tensorflow/c/c_test.c
// just nice to know that it compiles. void* create(TF_OpKernelConstruction* ctx) { TF_DataType type; TF_Status* s = TF_NewStatus(); TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s); TF_DeleteStatus(s); return NULL; } // A compute function. This will never actually get called in this test, it's // just nice to know that it compiles.
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ci/official/README.md
# # Docker is enabled by default on Linux. You may disable it if you prefer: # export TFCI=py311,linux_x86,no_docker # Advanced: Use Remote Build Execution (RBE) (internal developers only) # # RBE dramatically speeds up builds and testing. It also gives you a # public URL to share your build results with collaborators. However, # it is only available to a limited set of internal TensorFlow developers. #
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ci/official/debug_tfci.sh
# limitations under the License. # ============================================================================== # This script dumps some information about the environment. It's most useful # for verifying changes to the TFCI scripts system, and most users won't need # to interact with it at all. source "${BASH_SOURCE%/*}/utilities/setup.sh" echo "==TFCI== env outside of tfrun:" env echo "==TFCI== env inside of tfrun:"
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ci/official/requirements_updater/README.md
updating requirements for multiple minor versions of Python. It takes in a file with a set of dependencies, and produces a more detailed requirements file for each version, with hashes specified for each dependency required, as well as their sub-dependencies. ### How to update/add requirements By default, the name of the base requirements file is `requirements.in`, but it can be set using the `REQUIREMENTS_FILE_NAME` variable. \ For example:
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.github/bot_config.yml
* It has an added advantage since you can you easily switch to different hardware accelerators (cpu, gpu, tpu) as per the task. * All you need is a good internet connection and you are all set. * Try to build TF from sources by changing CPU optimization flags. *Please let us know if this helps.* windows_comment: >
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Oct 17 11:48:07 GMT 2023 - 4K bytes - Viewed (0) -
SECURITY.md
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. For performance reasons, the default TensorFlow server does not include any authorization protocol and sends messages unencrypted. It accepts connections from anywhere, and executes the graphs it is sent without performing any checks.
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ci/official/containers/linux_arm64/cuda.packages.txt
libcudnn8=8.9.6.50-1+cuda12.2 libcudnn8-dev=8.9.6.50-1+cuda12.2 # This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image. # For now it ensures that we install at least version 12.3.107 of PTXAS, # since 12.3.103 has a bug.
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