INFO:root:Namespace(input_file='data/gaussian.npy', output_dir='outputs/93', architecture='chain', number_of_states=2, log_f='trainig_log', no_mean=0, 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: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 4.002803775605156
        x: [ 2.978e+00]
      nit: 0
      jac: [-1.776e-07]
     nfev: 2
     njev: 1
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 1 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 4.002803775605156
        x: [ 2.978e+00]
      nit: 0
      jac: [ 0.000e+00]
     nfev: 2
     njev: 1
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 2 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 4.002803775605157
        x: [ 2.978e+00]
      nit: 0
      jac: [-8.882e-08]
     nfev: 2
     njev: 1
 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: 4.002803775605155
        x: [ 2.978e+00]
      nit: 0
      jac: [-8.882e-08]
     nfev: 2
     njev: 1
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 4 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 4.002803775605156
        x: [ 2.978e+00]
      nit: 0
      jac: [ 8.882e-08]
     nfev: 2
     njev: 1
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 5 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 4.002803775605155
        x: [ 2.978e+00]
      nit: 0
      jac: [ 8.882e-08]
     nfev: 2
     njev: 1
 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: 4.002803775605154
        x: [ 2.978e+00]
      nit: 0
      jac: [ 1.776e-07]
     nfev: 2
     njev: 1
 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: 4.002803775605156
        x: [ 2.978e+00]
      nit: 0
      jac: [-8.882e-08]
     nfev: 2
     njev: 1
 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: 4.002803775605155
        x: [ 2.978e+00]
      nit: 0
      jac: [ 8.882e-08]
     nfev: 2
     njev: 1
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
INFO:root:Best Optimization Result for iteration 9 :   message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL
  success: True
   status: 0
      fun: 4.002803775605157
        x: [ 2.978e+00]
      nit: 0
      jac: [-8.882e-08]
     nfev: 2
     njev: 1
 hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>
