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tensorflow/c/eager/immediate_execution_distributed_manager.h
bool clear_existing_contexts = false) = 0; // Initializes context for the local worker and no contexts will be created // for remote workers. Currently this only works for resetting context. // TODO(b/289445025): Consider removing this when we find a proper fix. virtual Status InitializeLocalOnlyContext(const ServerDef& server_def,
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ci/official/README.md
- Uses `pycpp.sh` - Presubmit jobs (Run on every GitHub PR) - Uses `pycpp.sh`, `code_check_changed_files.sh` These "env" files match up with an environment matrix that roughly covers: - Different Python versions - Linux, MacOS, and Windows machines (these pool definitions are internal) - x86 and arm64 - CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs
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tensorflow/c/eager/c_api_experimental.h
// Dynamic cluster API. // Update an existing context with a new set of servers defined in a ServerDef // proto. Servers can be added to and removed from the list of remote workers // in the context. A New set of servers identified by the ServerDef must be up // when the context is updated. // // This API is for experimental usage and may be subject to change.
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RELEASE.md
* `tf.data`: * Added `target_workers` param to `data_service_ops.from_dataset_id` and `data_service_ops.distribute`. Users can specify `"AUTO"`, `"ANY"`, or `"LOCAL"` (case insensitive). If `"AUTO"`, tf.data service runtime decides which workers to read from. If `"ANY"`, TF workers read from any tf.data service workers. If `"LOCAL"`, TF workers will only read from
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Mon Apr 29 19:17:57 GMT 2024 - 727.7K bytes - Viewed (8) -
.bazelrc
build:rbe_base --remote_timeout=3600 build:rbe_base --spawn_strategy=remote,worker,standalone,local # Attempt to minimize the amount of data transfer between bazel and the remote # workers: build:rbe_base --remote_download_toplevel test:rbe_base --test_env=USER=anon # TODO(kanglan): Check if we want to merge rbe_linux into rbe_linux_cpu. build:rbe_linux --config=rbe_base
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tensorflow/c/eager/c_api_distributed_test.cc
// once (i.e., on the main function side) in running distributed functions. // This test creates a cluster with two workers, create a variable on the // second worker, and run a distributed function (VariableAddFunction) whose ops // span the local and remote workers. If the graph optimization pass is executed // on both the main function side and the component function side, an error will
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