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ci/official/wheel_test/README.md
Example: For Python 3.11, use `3_11` The script performs the following steps: 1. Navigates to the `../requirements_updater` directory. 2. Creates a `requirements_wheel_test.in` file and specifies the path to the actual TensorFlow wheel. 3. Creates a `requirements_lock_<python_version>.txt` file. 4. Updates the `requirements_lock_<python_version>.txt` file using a Bazel command.
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.github/workflows/issue-on-pr-rollback.yml
# See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== name: Creates a GitHub Issue when a PR Rolled back via Commit to Master on: push: branches: - master permissions: {} jobs: create-issue-on-pr-rollback: runs-on: ubuntu-latest
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Sep 12 16:40:29 GMT 2023 - 1.5K bytes - Viewed (0) -
tensorflow/c/eager/c_api_remote_test_util.h
#define TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_ // Run a function containing a MatMul op and check its output. // If heavy_load_on_streaming_rpc is true, send some rpc requests before the one // which creates a remote input, to simulate a scenario that the remote input // is not ready when we start running an op or a function. void TestRemoteExecuteSilentCopies(bool async, bool remote, bool func,
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tensorflow/c/eager/unified_api_testutil.h
#include "tensorflow/core/platform/status.h" namespace tensorflow { // Builds and returns a `TracingContext` using the default tracing impl. AbstractContext* BuildFunction(const char* fn_name); // Creates parameters (placeholders) in the tracing `ctx` using the shape and // dtype of `inputs`. Status CreateParamsForInputs(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
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tensorflow/c/eager/c_api_unified_experimental.h
void TF_SetTracingImplementation(const char* name, TF_Status*); // Creates a new TensorFlow function. A Function is an execution context, and as // such it can trace operations through TF_ExecuteOperation. After completing // tracing, a function can be obtained by TF_FinalizeFunction. TF_ExecutionContext* TF_CreateFunction(const char* fn_name, TF_Status* status); // Creates a context for eager execution of operations.
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tensorflow/c/eager/c_api_unified_experimental.cc
using tensorflow::tracing::TracingTensorHandle; void TF_SetTracingImplementation(const char* name, TF_Status* s) { tsl::Set_TF_Status_from_Status(s, SetDefaultTracingEngine(name)); } // Creates a new TensorFlow function, it is an execution context attached to a // given tracing context. TF_ExecutionContext* TF_CreateFunction(const char* fn_name, TF_Status* s) { return wrap(CreateTracingExecutionContext(fn_name, s));
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ci/official/README.md
values from those `TFCI` paths. - `set -a` / `set -o allexport` exports the variables from `env` files so all scripts can use them. - `utilities/setup_docker.sh` creates a container called `tf` with all `TFCI_` variables shared to it. 3. Top-level scripts (`wheel.sh`, etc.) reference `env` variables and call `utilities/` scripts.
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tensorflow/c/experimental/next_pluggable_device/c_api.h
// if the tensor does not have a `PjRtCApiBuffer`. TF_CAPI_EXPORT extern PJRT_Buffer* TF_GetPjRtCBuffer(TF_Tensor* c_tensor, TF_Status* status); // Creates a `PjRtCApiBuffer` with the `PJRT_Buffer*` passed in and set to the // tensor. TF_CAPI_EXPORT extern void TF_CreatePjRtBuffer(TF_Tensor* c_tensor, PJRT_Buffer* c_buffer,
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tensorflow/c/env.h
// that the system default will be used. size_t guard_size; // The NUMA node to use, -1 implies that there should be no NUMA affinity for // this thread. int numa_node; } TF_ThreadOptions; // Creates the specified directory. Typical status code are: // * TF_OK - successfully created the directory // * TF_ALREADY_EXISTS - directory already exists // * TF_PERMISSION_DENIED - dirname is not writable
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tensorflow/c/eager/parallel_device/parallel_device_testlib.h
// The dtype of the variable's buffer (input dtype for assignments, output // dtype of read operations). TF_DataType type_; }; // Creates a TFE_TensorHandle with value `v`. TensorHandlePtr FloatTensorHandle(float v, TF_Status* status); // Creates a rank-one TFE_TensorHandle with value `v`. TensorHandlePtr VectorFloatTensorHandle(const std::vector<float>& v, TF_Status* status);
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