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.github/workflows/sigbuild-docker-presubmit.yml
- name: Checkout uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0 - name: Set up Docker Buildx uses: docker/setup-buildx-action@8c0edbc76e98fa90f69d9a2c020dcb50019dc325 # v2.2.1 - name: Login to GCR if: contains(github.event.pull_request.labels.*.name, 'build and push to gcr.io for staging')
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Mon Oct 23 18:43:43 GMT 2023 - 4K bytes - Viewed (0) -
.github/workflows/trusted-partners.yml
if: | github.event.pull_request.draft == false && github.event.sender.type == 'User' steps: - name: Checkout repo uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0 - name: Trusted-Partners-PR uses: actions/github-script@d556feaca394842dc55e4734bf3bb9f685482fa0 # v6.3.3 with: github-token: ${{ secrets.GITHUB_TOKEN }} script: |
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Sep 12 14:49:29 GMT 2023 - 2.4K bytes - Viewed (0) -
.github/workflows/arm-ci-extended.yml
- name: Checkout repository for nightly (skipped for releases) if: ${{ github.event_name == 'schedule' }} uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1 with: ref: 'nightly' - name: Checkout repository if: ${{ github.event_name == 'push' }} uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Mar 05 10:24:16 GMT 2024 - 2.6K bytes - Viewed (0) -
SECURITY.md
are working with. When loading untrusted checkpoints, the values of the traced variables from your model are also going to be untrusted. That means that if your code interacts with the filesystem, network, etc. and uses checkpointed variables as part of those interactions (ex: using a string variable to build a filesystem path), a maliciously created checkpoint might be able to change the targets of those operations, which could result in arbitrary
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RELEASE.md
`nodes_and_registration()` method, both of which were previously documented as temporary and to be removed. * Uses of `tensors()` can be replaced by calling the existing methods `tensors_size()` and `tensor(int)`. * Uses of the non-const overload of `nodes_and_registration` can be replaced by calling the existing methods `nodes_size()` and
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tensorflow/c/eager/c_api.cc
} private: TFE_Context* context_; TFE_CustomDevice device_; void* info_; string name_; }; // An adapter which wraps the shape/data produced by C custom devices and uses // it to implement custom device methods. class CAPICustomDeviceTensorHandle : public tensorflow::CustomDeviceTensorHandle { public: CAPICustomDeviceTensorHandle(tensorflow::ImmediateExecutionContext* context,
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tensorflow/c/eager/BUILD
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tensorflow/BUILD
}), ) # ------------------------------------------- # New rules should be added above this target. # ------------------------------------------- # TensorFlow uses several libraries that may also be used by applications # linking against the C and C++ APIs (such as libjpeg). When we create # the shared library, only export the core TF API functions to avoid
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tensorflow/c/eager/c_api_distributed_test.cc
ASSERT_TRUE(worker_server2->Start().ok()); const char dev2_name[] = "/job:localhost/replica:0/task:2/device:CPU:0"; if (inject_error) { // Inject a function optimization pass failure when it sees the // 'read0_maybe_with_graph_error' op having a requested device `dev2_name`. // During execution: // * task:0 processes main function `VariableAddFunctionWithGraphError`
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