.. _l-GaussianProcessRegressor-~b-reg-NF-cov-64-expsine-cdist-o17:

GaussianProcessRegressor - ~b-reg-NF-cov-64 - expsine - cdist
=============================================================

Fitted on a problem type *~b-reg-NF-cov-64*
(see :func:`find_suitable_problem
<mlprodict.onnxrt.validate.validate_problems.find_suitable_problem>`),
method `predict` matches output .
Model was converted with additional parameter: ``<class 'sklearn.gaussian_process._gpr.GaussianProcessRegressor'>={'optim': 'cdist'}``.

::

        GaussianProcessRegressor(alpha=20.0,
                             kernel=ExpSineSquared(length_scale=1, periodicity=1),
                             random_state=42)

+-----------------------+----------+
| index                 | 0        |
+=======================+==========+
| skl_nop               | 1        |
+-----------------------+----------+
| onx_size              | 1407     |
+-----------------------+----------+
| onx_nnodes            | 18       |
+-----------------------+----------+
| onx_ninits            | 5        |
+-----------------------+----------+
| onx_doc_string        |          |
+-----------------------+----------+
| onx_ir_version        | 8        |
+-----------------------+----------+
| onx_domain            | ai.onnx  |
+-----------------------+----------+
| onx_model_version     | 0        |
+-----------------------+----------+
| onx_producer_name     | skl2onnx |
+-----------------------+----------+
| onx_producer_version  | 1.13.1   |
+-----------------------+----------+
| onx_                  | 17       |
+-----------------------+----------+
| onx_op_Identity       | 3        |
+-----------------------+----------+
| onx_subgraphs         | 1        |
+-----------------------+----------+
| onx_op_Identity_optim | 1        |
+-----------------------+----------+
| onx_subgraphs_optim   | 1        |
+-----------------------+----------+
| onx_size_optim        | 1282     |
+-----------------------+----------+
| onx_nnodes_optim      | 16       |
+-----------------------+----------+
| onx_ninits_optim      | 5        |
+-----------------------+----------+


.. gdot::

        digraph{
      size=7;
      ranksep=0.25;
      nodesep=0.05;
      orientation=portrait;

      X [shape=box color=red label="X\ndouble((0, 4))" fontsize=10];

      GPmean [shape=box color=green label="GPmean\ndouble((0, 1))" fontsize=10];
      GPcovstd [shape=box color=green label="GPcovstd\ndouble(('?',))" fontsize=10];

      Re_ReduceSumcst [shape=box label="Re_ReduceSumcst\nint64((1,))\n[1]" fontsize=10];
      Di_Divcst [shape=box label="Di_Divcst\nfloat64((1,))\n[1.]" fontsize=10];
      Mu_Mulcst [shape=box label="Mu_Mulcst\nfloat64((1,))\n[3.14159265]" fontsize=10];
      Po_Powcst [shape=box label="Po_Powcst\nfloat64((1,))\n[2.]" fontsize=10];
      Mu_Mulcst1 [shape=box label="Mu_Mulcst1\nfloat64((1,))\n[-2.]" fontsize=10];

      Sh_shape0 [shape=box label="Sh_shape0" fontsize=10];
      Sh_Shape [shape=box style="filled,rounded" color=orange label="Shape\n(Sh_Shape)" fontsize=10];
      X -> Sh_Shape;
      Sh_Shape -> Sh_shape0;

      UU002UU [shape=box label="UU002UU" fontsize=10];
      UU003UU [shape=box label="UU003UU" fontsize=10];
      subgraph cluster_Scan139904363595712_139908381009904 {
        label="Scan\n(Sc_Scan)\nbody=node {\n  input: 'next_in'...\nnum_scan_inputs=1";
        fontsize=10;
        color=black;
        B_next_in [shape=box color=red label="next_in\ndouble((0, 0))" fontsize=10];
        B_next [shape=box color=red label="next\ndouble((0,))" fontsize=10];
  
        B_next_out [shape=box color=green label="next_out\ndouble((0, 0))" fontsize=10];
        B_scan_out [shape=box color=green label="scan_out\ndouble((0,))" fontsize=10];
  
  
        B_cdistd_2_Identity [shape=box style="filled,rounded" color=orange label="Identity\n(cdistd_2_Identity)" fontsize=10];
        B_next_in -> B_cdistd_2_Identity;
        B_cdistd_2_Identity -> B_next_out;
  
        B_cdistdf_2_C0 [shape=box label="cdistdf_2_C0" fontsize=10];
        B_cdistdf_2_Sub [shape=box style="filled,rounded" color=orange label="Sub\n(cdistdf_2_Sub)" fontsize=10];
        B_next_in -> B_cdistdf_2_Sub;
        B_next -> B_cdistdf_2_Sub;
        B_cdistdf_2_Sub -> B_cdistdf_2_C0;
  
        B_cdistdf_2_reduced0 [shape=box label="cdistdf_2_reduced0" fontsize=10];
        B_cdistdf_2_ReduceSumSquare [shape=box style="filled,rounded" color=orange label="ReduceSumSquare\n(cdistdf_2_ReduceSumSquare)\naxes=[1]\nkeepdims=0" fontsize=10];
        B_cdistdf_2_C0 -> B_cdistdf_2_ReduceSumSquare;
        B_cdistdf_2_ReduceSumSquare -> B_cdistdf_2_reduced0;
  
        B_cdistdf_2_Identity [shape=box style="filled,rounded" color=orange label="Identity\n(cdistdf_2_Identity)" fontsize=10];
        B_cdistdf_2_reduced0 -> B_cdistdf_2_Identity;
        B_cdistdf_2_Identity -> B_scan_out;
      }
      X -> B_next_in;
      X -> B_next;
      B_next_out -> UU002UU;
      B_scan_out -> UU003UU;
      Sc_Scan -> B_cdistd_2_Identity [lhead=cluster_Scan139904363595712_139908381009904];
      X -> Sc_Scan;
      X -> Sc_Scan;
      Sc_Scan -> UU002UU;
      Sc_Scan -> UU003UU;

      Co_output0 [shape=box label="Co_output0" fontsize=10];
      Co_ConstantOfShape [shape=box style="filled,rounded" color=orange label="ConstantOfShape\n(Co_ConstantOfShape)\nvalue=[0.]" fontsize=10];
      Sh_shape0 -> Co_ConstantOfShape;
      Co_ConstantOfShape -> Co_output0;

      Tr_transposed0 [shape=box label="Tr_transposed0" fontsize=10];
      Tr_Transpose [shape=box style="filled,rounded" color=orange label="Transpose\n(Tr_Transpose)\nperm=[1 0]" fontsize=10];
      UU003UU -> Tr_Transpose;
      Tr_Transpose -> Tr_transposed0;

      Re_ReduceSum [shape=box style="filled,rounded" color=orange label="ReduceSum\n(Re_ReduceSum)\nkeepdims=1" fontsize=10];
      Co_output0 -> Re_ReduceSum;
      Re_ReduceSumcst -> Re_ReduceSum;
      Re_ReduceSum -> GPmean;

      Sq_Y0 [shape=box label="Sq_Y0" fontsize=10];
      Sq_Sqrt [shape=box style="filled,rounded" color=orange label="Sqrt\n(Sq_Sqrt)" fontsize=10];
      Tr_transposed0 -> Sq_Sqrt;
      Sq_Sqrt -> Sq_Y0;

      Di_C01 [shape=box label="Di_C01" fontsize=10];
      Di_Div [shape=box style="filled,rounded" color=orange label="Div\n(Di_Div)" fontsize=10];
      Sq_Y0 -> Di_Div;
      Di_Divcst -> Di_Div;
      Di_Div -> Di_C01;

      Mu_C01 [shape=box label="Mu_C01" fontsize=10];
      Mu_Mul [shape=box style="filled,rounded" color=orange label="Mul\n(Mu_Mul)" fontsize=10];
      Di_C01 -> Mu_Mul;
      Mu_Mulcst -> Mu_Mul;
      Mu_Mul -> Mu_C01;

      Si_output0 [shape=box label="Si_output0" fontsize=10];
      Si_Sin [shape=box style="filled,rounded" color=orange label="Sin\n(Si_Sin)" fontsize=10];
      Mu_C01 -> Si_Sin;
      Si_Sin -> Si_output0;

      Di_C0 [shape=box label="Di_C0" fontsize=10];
      Di_Div1 [shape=box style="filled,rounded" color=orange label="Div\n(Di_Div1)" fontsize=10];
      Si_output0 -> Di_Div1;
      Di_Divcst -> Di_Div1;
      Di_Div1 -> Di_C0;

      Po_Z0 [shape=box label="Po_Z0" fontsize=10];
      Po_Pow [shape=box style="filled,rounded" color=orange label="Pow\n(Po_Pow)" fontsize=10];
      Di_C0 -> Po_Pow;
      Po_Powcst -> Po_Pow;
      Po_Pow -> Po_Z0;

      Mu_C0 [shape=box label="Mu_C0" fontsize=10];
      Mu_Mul1 [shape=box style="filled,rounded" color=orange label="Mul\n(Mu_Mul1)" fontsize=10];
      Po_Z0 -> Mu_Mul1;
      Mu_Mulcst1 -> Mu_Mul1;
      Mu_Mul1 -> Mu_C0;

      Ex_output0 [shape=box label="Ex_output0" fontsize=10];
      Ex_Exp [shape=box style="filled,rounded" color=orange label="Exp\n(Ex_Exp)" fontsize=10];
      Mu_C0 -> Ex_Exp;
      Ex_Exp -> Ex_output0;

      Id_Identity [shape=box style="filled,rounded" color=orange label="Identity\n(Id_Identity)" fontsize=10];
      Ex_output0 -> Id_Identity;
      Id_Identity -> GPcovstd;
    }