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tensorflow/c/eager/c_api_experimental.h
// 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 // than separately calling it because if the existing op has the same
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Feb 21 22:37:46 GMT 2024 - 39.5K bytes - Viewed (0) -
tensorflow/c/eager/c_api.cc
status->status = tensorflow::errors::InvalidArgument("Unparseable AttrValue proto"); return; } if (op == nullptr) { status->status = tensorflow::errors::InvalidArgument( "Got a null or uninitialized `op` argument"); return; } tensorflow::EagerOperation* operation = OperationFromInterface(tensorflow::unwrap(const_cast<TFE_Op*>(op)));
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 12 20:00:09 GMT 2024 - 43.9K bytes - Viewed (2) -
tensorflow/c/eager/tape.h
// between calls to ShouldRecord and Accumulator), and its outputs // (`output_tensors`). // // If provided, a non-null `forward_function` will be used instead of the // backward function (`backward_function_getter` / // `backward_function_deleter`) to compute jvps for this operation. If // `forward_function` is null, a GradientTape is used on the backward function // to compute the jvp, which will waste computation when executing eagerly.
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ci/official/utilities/code_check_full.bats
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tensorflow/c/c_api_experimental.cc
return ret; } // On success, returns a set of TF_Function instances from `text_proto` of // GraphDef type. These functions must be deleted by calling TF_DeleteFunction. // // If `mutate_proto_func` is non-NULL, run it over each FunctionDef proto, // before creating a TF_Function out of the possibly mutated proto. static std::vector<UniqueFuncPtr> CreateFunctionsFromTextProto( const char* text_proto,
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tensorflow/c/c_api_function.cc
const TF_Function* grad, TF_Status* status) { if (func == nullptr) { status->status = InvalidArgument( "'func' argument to TF_GraphCopyFunction cannot be null"); return; } tensorflow::mutex_lock l(g->mu); status->status = g->graph.AddFunctionDef(func->record->fdef(), func->record->stack_traces());
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