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tensorflow/c/eager/c_api.h
// graph mode). Calling this on a context tells it to start a step. TF_CAPI_EXPORT extern void TFE_ContextStartStep(TFE_Context* ctx); // Ends a step. When there is no active step (that is, every started step has // been ended) step containers will be cleared. Note: it is not safe to call // TFE_ContextEndStep while ops that rely on the step container may be running.
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# This bazelrc can build a CPU-supporting TF package. # Convenient cache configurations # Use a cache directory mounted to /tf/cache. Very useful! build:sigbuild_local_cache --disk_cache=/tf/cache # Use the public-access TF DevInfra cache (read only) build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false
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tensorflow/c/eager/c_api_experimental.h
#ifdef __cplusplus extern "C" { #endif // Resets `op_to_reset` with `op_or_function_name` and `raw_device_name`. This // is for performance optimization by reusing an exiting unused op rather than // creating a new op every time. If `raw_device_name` is `NULL` or empty, it // does not set the device name. If it's not `NULL`, then it attempts to parse // and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster
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tensorflow/c/eager/parallel_device/parallel_device_lib.cc
: status_(TF_NewStatus()), // If the context's default exector is set to async, re-using that in // each thread would cause collectives to deadlock. For consistency we // create a new sync executor for every thread. // // TODO(allenl): We should have an async API that works with the // parallel device. device_(device), executor_(
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tensorflow/c/c_api.h
// reference types inside function's body to support legacy code. Do not // use them in new code. // - Every node in the function's body must have all of its inputs (including // control inputs). In other words, for every node in the body, each input // must be either listed in `inputs` or must come from another node in
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tensorflow/c/eager/parallel_device/parallel_device_lib.h
Status Shape(const std::vector<int64_t>** shape) const; TF_DataType dtype() const { return dtype_; } // Sets its output argument to a summary of the values of this tensor on every // component device. Status SummarizeValue(std::string& summary); std::vector<TensorHandlePtr> release_tensors() { return std::move(tensors_); } std::vector<TFE_TensorHandle*> tensors() const {
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tensorflow/c/c_api.cc
} else { return ToOperation(iter->second); } } TF_Operation* TF_GraphNextOperation(TF_Graph* graph, size_t* pos) { if (*pos == 0) { // Advance past the first sentinel nodes in every graph (the source & sink). *pos += 2; } else { // Advance to the next node. *pos += 1; } mutex_lock l(graph->mu);
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RELEASE.md
* Added a new `rerandomize_each_iteration` argument for the `tf.data.Dataset.sample_from_datasets()` operation, which controls whether the...
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ci/official/envs/versions_upload
# See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== # Release jobs are very basic. They don't use any caching or RBE, # but they do upload logs to resultstore. # IMPORTANT: trailing slash is required on GCS URIs, as it tells gcloud to # pretend the path is a directory. TFCI_ARTIFACT_FINAL_GCS_ENABLE=1
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# This bazelrc can build a CPU-supporting TF package. # Convenient cache configurations # Use a cache directory mounted to /tf/cache. Very useful! build:sigbuild_local_cache --disk_cache=/tf/cache # Use the public-access TF DevInfra cache (read only) build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false
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