INFO:root:Namespace(input_file='data/uniform.npy', output_dir='outputs/622', architecture='full', number_of_states=2, log_f='trainig_log', no_mean=1, threads=1, fit='d', training_opt=[10, 500, 100], opt_options=[1e-06, 1e-06, 15000.0, 10.0])
INFO:root:Best Optimization Result for iteration 0 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.3021681134648397
        x: [-2.251e+00]
      nit: 7
      jac: [ 4.308e-06]
     nfev: 22
     njev: 11
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 1 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.302168113476854
        x: [-2.251e+00]
      nit: 8
      jac: [ 6.262e-06]
     nfev: 22
     njev: 11
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 2 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.3021681134665393
        x: [-2.251e+00]
      nit: 7
      jac: [ 4.707e-06]
     nfev: 22
     njev: 11
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 3 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 3.3021681134551337
        x: [-2.251e+00]
      nit: 7
      jac: [ 8.438e-07]
     nfev: 22
     njev: 11
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 4 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.3021681134910126
        x: [-2.251e+00]
      nit: 7
      jac: [-8.038e-06]
     nfev: 20
     njev: 10
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 5 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.3021681134700485
        x: [-2.251e+00]
      nit: 7
      jac: [-5.329e-06]
     nfev: 20
     njev: 10
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 6 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 3.3021681134548166
        x: [-2.251e+00]
      nit: 7
      jac: [-4.441e-08]
     nfev: 20
     njev: 10
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 7 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 3.3021681134552034
        x: [-2.251e+00]
      nit: 5
      jac: [-9.326e-07]
     nfev: 18
     njev: 9
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 8 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 3.30216811345488
        x: [-2.251e+00]
      nit: 7
      jac: [-2.220e-07]
     nfev: 20
     njev: 10
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 9 :   message: CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH
  success: True
   status: 0
      fun: 3.302168113535366
        x: [-2.251e+00]
      nit: 7
      jac: [-1.199e-05]
     nfev: 20
     njev: 10
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
