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tensorflow/c/eager/parallel_device/parallel_device_lib.h
// Blocks until the previous `StartExecute` has run `TFE_Execute` on each // device. If is_async=false (constructor argument) this means the ops have // run and have results. If is_async=true it means that all of the // device-specific executors have scheduled the op. // // Accepts inferred shapes for outputs (`expected_output_shapes`), which if
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tensorflow/c/c_api.h
#include "tensorflow/c/tf_status.h" #include "tensorflow/c/tf_tensor.h" #include "tensorflow/c/tf_tstring.h" // -------------------------------------------------------------------------- // C API for TensorFlow. // // The API leans towards simplicity and uniformity instead of convenience // since most usage will be by language specific wrappers. // // Conventions: // * We use the prefix TF_ for everything in the API.
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tensorflow/c/eager/tape.h
std::function<void(BackwardFunction*)> backward_function_deleter; }; // Map from tensor_id to internally-defined operation-id of the operation which // produced this tensor. A value of -1 means that the tensor was directly // watched and not the result of any operation in the tape. using TensorTape = std::unordered_map<int64_t, int64_t>; // Map from operation-id to tape entry.
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Apr 02 12:40:29 GMT 2024 - 47.2K bytes - Viewed (1) -
tensorflow/c/experimental/filesystem/plugins/gcs/expiring_lru_cache.h
/// max item age (in seconds) and max entries. /// /// This class is thread safe. template <typename T> class ExpiringLRUCache { public: /// A `max_age` of 0 means that nothing is cached. A `max_entries` of 0 means /// that there is no limit on the number of entries in the cache (however, if /// `max_age` is also 0, the cache will not be populated). ExpiringLRUCache(uint64_t max_age, size_t max_entries,
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tensorflow/c/eager/immediate_execution_operation.h
virtual ImmediateExecutionContext* GetContext() const = 0; // Following two methods are used to support custom device. // Return true if the inputs contain custom device tensor handle. It means // that the argument need to be handled by a custom device. virtual bool HasCustomDeviceInput() const = 0; virtual const tensorflow::OpDef* OpDef() const = 0;
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