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tensorflow/c/eager/c_api_experimental.h
TF_CAPI_EXPORT extern void TFE_ContextUpdateServerDefWithTimeout( TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len, int64_t init_timeout_in_ms, TF_Status* status); // This API is for experimental usage and may be subject to change. TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeout( TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len, int64_t init_timeout_in_ms, TF_Status* status,
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/c_api.h
// Return a new execution session with the associated graph, or NULL on // error. Does not take ownership of any input parameters. // // *`graph` must be a valid graph (not deleted or nullptr). `graph` will be // kept alive for the lifetime of the returned TF_Session. New nodes can still // be added to `graph` after this call. TF_CAPI_EXPORT extern TF_Session* TF_NewSession(TF_Graph* graph,
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Oct 26 21:08:15 GMT 2023 - 82.3K bytes - Viewed (3) -
tensorflow/c/eager/tape.h
template <typename Gradient, typename BackwardFunction, typename TapeTensor> class GradientTape { public: // If `persistent` is true, GradientTape will not eagerly delete backward // functions (and hence the tensors they keep alive). Instead, everything // is deleted in ~GradientTape. Persistent GradientTapes are useful when // users want to compute multiple gradients over the same tape.
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)