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Results 1 - 2 of 2 for dx (0.24 sec)
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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 - 15.2K bytes - Viewed (0) -
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 - 47.2K bytes - Viewed (1)