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Results 1 - 3 of 3 for We (0.19 sec)

  1. tensorflow/c/eager/immediate_execution_distributed_manager.h

      // 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,
                                                int keep_alive_secs) = 0;
    
    C
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Wed Feb 21 22:37:46 GMT 2024
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  2. tensorflow/c/eager/tape.h

    //
    // Below here we do the gradient algorithm. It works as follows:
    //
    // First we filter the tape to just the subset of operations we want to
    // differentiate. In the process of doing so we count how many times each Tensor
    // is used as an input to an op (so we know when we're done computing gradients
    // for that Tensor). We also count, for each tape entry, how many of its output
    C
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Tue Apr 02 12:40:29 GMT 2024
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  3. tensorflow/c/eager/c_api_experimental.h

    // APIs for generically dealing with op attributes (e.g. when forwarding them
    // through custom device implementations).
    //
    // TODO(allenl): Currently these are black boxes, but we should have some way to
    // inspect values. This would let people e.g. copy over most attributes and then
    // modify some based on their values.
    
    // A reference to an op's name -> attribute mapping
    C
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Wed Feb 21 22:37:46 GMT 2024
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