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Results 1 - 2 of 2 for dx (0.24 sec)

  1. tensorflow/c/experimental/gradients/math_grad.cc

         *
         *    dX = U / Y
         *    dY = -U*X / Y^2 = (X/Y) * -U / Y = -U*Z / Y
         *
         */
    
        AbstractTensorHandle* upstream_grad = grad_outputs[0];
        AbstractTensorHandle* Y = forward_inputs_[1];
        AbstractTensorHandle* Z = forward_outputs_[0];
    
        // Calculate dX =  U / Y
        std::string name = "Div_Grad_X";
        TF_RETURN_IF_ERROR(
    C++
    - Registered: Tue Mar 26 12:39:09 GMT 2024
    - Last Modified: Wed Feb 28 13:53:47 GMT 2024
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  2. tensorflow/c/eager/tape.h

      op_tape_.erase(op_it);
    }
    
    // Terminology:
    //
    //  - op: a possibly composite operation, which has an entry in the tape
    //  - target: dy in dx/dy
    //  - source: dx in dx/dy
    //  - tensor: one of the many inputs or outputs of an operation
    //
    // Below here we do the gradient algorithm. It works as follows:
    //
    C
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Tue Apr 02 12:40:29 GMT 2024
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