2023-10-09 00:11:16.187541: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
EF: 0.9
----------------------------------------------------------------------------------------------------
Experiment:  [WellingNormalized(), EffectiveResistance()]
Layers: 2
Dataset: facebook
Dataset:  facebook
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:76: UserWarning: Edge Weights are set to 1 automatically
  warnings.warn("Edge Weights are set to 1 automatically")
Train Mask:  0.6001485586166382
Val Mask:  0.2000495195388794
Test Mask:  0.19980193674564362
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
/home/ubuntu/graph-neural-networks/gnn/sparsify/call_julia_sparsify.py:77: UserWarning: Total Edges: 180507
  warnings.warn(f"Total Edges: {np.count_nonzero(adj)}")
/home/ubuntu/graph-neural-networks/gnn/sparsify/call_julia_sparsify.py:78: UserWarning: Total Edges: 16580
  warnings.warn(f"Total Edges: {np.count_nonzero(sparsified)}")
/home/ubuntu/graph-neural-networks/gnn/sparsify/call_julia_sparsify.py:79: UserWarning: Reduction: 0.9081476064640153
  warnings.warn(f"Reduction: {1 - np.count_nonzero(sparsified) / np.count_nonzero(adj)}")
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
Adj shape (4039, 4039)
Number of Edges: 16494
NONLINEAR: True
SIGMA_W: 1 SIGMA_B: 0
Find best regularization using val_mask
gnngp finished
Find best regularization using val_mask
gntk finished
+-------+-------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+---------------------------------------------------------------------------------------+
|       |                         |                                   |                                |                |                           |                     | Dataset: ffacebook Layer: 2 Adjacency: [WellingNormalized(), EffectiveResistance()]   |
+=======+=========================+===================================+================================+================+===========================+=====================+=======================================================================================+
| gnngp | ('kernel_fro', 3420.15) | ('train_loss_best_perf', 263.523) | ('train_loss_no_reg', 430.847) | ('reg', 0.052) | ('best_acc_train', 0.645) | ('Test acc', 0.651) | ('time', 2.65)                                                                        |
+-------+-------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+---------------------------------------------------------------------------------------+
| gntk  | ('kernel_fro', 5752.79) | ('train_loss_best_perf', 261.797) | ('train_loss_no_reg', 534.248) | ('reg', 0.091) | ('best_acc_train', 0.647) | ('Test acc', 0.649) | ('time', 2.65)                                                                        |
+-------+-------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+---------------------------------------------------------------------------------------+
Total Time : 0.9
----------------------------------------------------------------------------------------------------
Experiment:  [WellingNormalized(), EffectiveResistance()]
Layers: 2
Dataset: cora
Dataset:  cora
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:76: UserWarning: Edge Weights are set to 1 automatically
  warnings.warn("Edge Weights are set to 1 automatically")
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:181: UserWarning: test_val_split is ignored because train_mask and test_mask are provided by the dataset. Some datasets like Cora could not have labels for all nodes!
  warnings.warn(
Train Mask:  0.05169866979122162
Val Mask:  0.184638112783432
Test Mask:  0.369276225566864
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
Adj shape (2708, 2708)
Number of Edges: 8244
NONLINEAR: True
SIGMA_W: 1 SIGMA_B: 0
Find best regularization using val_mask
gnngp finished
Find best regularization using val_mask
gntk finished
+-------+------------------------+-----------------------------------+--------------------------------+----------------+--------------------------+---------------------+-----------------------------------------------------------------------------------+
|       |                        |                                   |                                |                |                          |                     | Dataset: fcora Layer: 2 Adjacency: [WellingNormalized(), EffectiveResistance()]   |
+=======+========================+===================================+================================+================+==========================+=====================+===================================================================================+
| gnngp | ('kernel_fro', 868.82) | ('train_loss_best_perf', 178.362) | ('train_loss_no_reg', 276.673) | ('reg', 2.754) | ('best_acc_train', 0.77) | ('Test acc', 0.771) | ('time', 1.16)                                                                    |
+-------+------------------------+-----------------------------------+--------------------------------+----------------+--------------------------+---------------------+-----------------------------------------------------------------------------------+
| gntk  | ('kernel_fro', 1181.5) | ('train_loss_best_perf', 166.632) | ('train_loss_no_reg', 247.97)  | ('reg', 1.738) | ('best_acc_train', 0.77) | ('Test acc', 0.778) | ('time', 1.16)                                                                    |
+-------+------------------------+-----------------------------------+--------------------------------+----------------+--------------------------+---------------------+-----------------------------------------------------------------------------------+
Total Time : 0.97
----------------------------------------------------------------------------------------------------
Experiment:  [WellingNormalized(), EffectiveResistance()]
Layers: 2
Dataset: citeseer
Dataset:  citeseer
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:76: UserWarning: Edge Weights are set to 1 automatically
  warnings.warn("Edge Weights are set to 1 automatically")
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:181: UserWarning: test_val_split is ignored because train_mask and test_mask are provided by the dataset. Some datasets like Cora could not have labels for all nodes!
  warnings.warn(
Train Mask:  0.03606852889060974
Val Mask:  0.150285542011261
Test Mask:  0.300571084022522
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
Adj shape (3327, 3327)
Number of Edges: 7642
NONLINEAR: True
SIGMA_W: 1 SIGMA_B: 0
Find best regularization using val_mask
gnngp finished
Find best regularization using val_mask
gntk finished
+-------+------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+---------------------------------------------------------------------------------------+
|       |                        |                                   |                                |                |                           |                     | Dataset: fciteseer Layer: 2 Adjacency: [WellingNormalized(), EffectiveResistance()]   |
+=======+========================+===================================+================================+================+===========================+=====================+=======================================================================================+
| gnngp | ('kernel_fro', 336.44) | ('train_loss_best_perf', 197.539) | ('train_loss_no_reg', 350.248) | ('reg', 3.02)  | ('best_acc_train', 0.684) | ('Test acc', 0.685) | ('time', 1.92)                                                                        |
+-------+------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+---------------------------------------------------------------------------------------+
| gntk  | ('kernel_fro', 433.97) | ('train_loss_best_perf', 198.154) | ('train_loss_no_reg', 320.944) | ('reg', 3.631) | ('best_acc_train', 0.684) | ('Test acc', 0.689) | ('time', 1.92)                                                                        |
+-------+------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+---------------------------------------------------------------------------------------+
Total Time : 1.06
----------------------------------------------------------------------------------------------------
Experiment:  [WellingNormalized(), EffectiveResistance()]
Layers: 2
Dataset: pubmed
Dataset:  pubmed
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:76: UserWarning: Edge Weights are set to 1 automatically
  warnings.warn("Edge Weights are set to 1 automatically")
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:181: UserWarning: test_val_split is ignored because train_mask and test_mask are provided by the dataset. Some datasets like Cora could not have labels for all nodes!
  warnings.warn(
Train Mask:  0.0030430592596530914
Val Mask:  0.02535882778465748
Test Mask:  0.05071765556931496
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
Adj shape (19717, 19717)
Number of Edges: 60800
NONLINEAR: True
SIGMA_W: 1 SIGMA_B: 0
Find best regularization using val_mask
gnngp finished
Find best regularization using val_mask
gntk finished
+-------+------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+-------------------------------------------------------------------------------------+
|       |                        |                                   |                                |                |                           |                     | Dataset: fpubmed Layer: 2 Adjacency: [WellingNormalized(), EffectiveResistance()]   |
+=======+========================+===================================+================================+================+===========================+=====================+=====================================================================================+
| gnngp | ('kernel_fro', 395.8)  | ('train_loss_best_perf', 146.308) | ('train_loss_no_reg', 472.451) | ('reg', 0.437) | ('best_acc_train', 0.784) | ('Test acc', 0.767) | ('time', 114.94)                                                                    |
+-------+------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+-------------------------------------------------------------------------------------+
| gntk  | ('kernel_fro', 526.65) | ('train_loss_best_perf', 145.246) | ('train_loss_no_reg', 403.0)   | ('reg', 0.479) | ('best_acc_train', 0.784) | ('Test acc', 0.774) | ('time', 114.94)                                                                    |
+-------+------------------------+-----------------------------------+--------------------------------+----------------+---------------------------+---------------------+-------------------------------------------------------------------------------------+
Total Time : 3.81
----------------------------------------------------------------------------------------------------
Experiment:  [WellingNormalized(), EffectiveResistance()]
Layers: 2
Dataset: chameleon
Dataset:  chameleon
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:76: UserWarning: Edge Weights are set to 1 automatically
  warnings.warn("Edge Weights are set to 1 automatically")
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:181: UserWarning: test_val_split is ignored because train_mask and test_mask are provided by the dataset. Some datasets like Cora could not have labels for all nodes!
  warnings.warn(
Train Mask:  0.4795784056186676
Val Mask:  0.32015809416770935
Test Mask:  0.20026350021362305
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
Adj shape (2277, 2277)
One hot encoding not working probably regression problem
Number of Edges: 8218
NONLINEAR: True
SIGMA_W: 1 SIGMA_B: 0.1
Find best regularization using val_mask
gnngp finished
Find best regularization using val_mask
gntk finished
+-------+-------------------------+-----------------------------------+---------------------------------+----------------+----------------------------+----------------------+----------------------------------------------------------------------------------------+
|       |                         |                                   |                                 |                |                            |                      | Dataset: fchameleon Layer: 2 Adjacency: [WellingNormalized(), EffectiveResistance()]   |
+=======+=========================+===================================+=================================+================+============================+======================+========================================================================================+
| gnngp | ('kernel_fro', 5391.35) | ('train_loss_best_perf', 869.87)  | ('train_loss_no_reg', 3562.674) | ('reg', 0.158) | ('R_squared_train', 0.447) | ('R_squared', 0.452) | ('time', 0.94)                                                                         |
+-------+-------------------------+-----------------------------------+---------------------------------+----------------+----------------------------+----------------------+----------------------------------------------------------------------------------------+
| gntk  | ('kernel_fro', 8898.04) | ('train_loss_best_perf', 871.871) | ('train_loss_no_reg', 3412.722) | ('reg', 0.209) | ('R_squared_train', 0.446) | ('R_squared', 0.445) | ('time', 0.94)                                                                         |
+-------+-------------------------+-----------------------------------+---------------------------------+----------------+----------------------------+----------------------+----------------------------------------------------------------------------------------+
Total Time : 3.98
----------------------------------------------------------------------------------------------------
Experiment:  [WellingNormalized(), EffectiveResistance()]
Layers: 2
Dataset: squirrel
Dataset:  squirrel
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:76: UserWarning: Edge Weights are set to 1 automatically
  warnings.warn("Edge Weights are set to 1 automatically")
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:181: UserWarning: test_val_split is ignored because train_mask and test_mask are provided by the dataset. Some datasets like Cora could not have labels for all nodes!
  warnings.warn(
Train Mask:  0.47990772128105164
Val Mask:  0.3199384808540344
Test Mask:  0.20015381276607513
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
Adj shape (5201, 5201)
One hot encoding not working probably regression problem
Number of Edges: 21590
NONLINEAR: True
SIGMA_W: 1 SIGMA_B: 0.1
Find best regularization using val_mask
gnngp finished
Find best regularization using val_mask
gntk finished
+-------+--------------------------+------------------------------------+---------------------------------+----------------+----------------------------+----------------------+---------------------------------------------------------------------------------------+
|       |                          |                                    |                                 |                |                            |                      | Dataset: fsquirrel Layer: 2 Adjacency: [WellingNormalized(), EffectiveResistance()]   |
+=======+==========================+====================================+=================================+================+============================+======================+=======================================================================================+
| gnngp | ('kernel_fro', 10377.66) | ('train_loss_best_perf', 1977.488) | ('train_loss_no_reg', 4720.149) | ('reg', 0.275) | ('R_squared_train', 0.235) | ('R_squared', 0.275) | ('time', 4.58)                                                                        |
+-------+--------------------------+------------------------------------+---------------------------------+----------------+----------------------------+----------------------+---------------------------------------------------------------------------------------+
| gntk  | ('kernel_fro', 17190.36) | ('train_loss_best_perf', 1974.109) | ('train_loss_no_reg', 5536.554) | ('reg', 0.363) | ('R_squared_train', 0.236) | ('R_squared', 0.272) | ('time', 4.58)                                                                        |
+-------+--------------------------+------------------------------------+---------------------------------+----------------+----------------------------+----------------------+---------------------------------------------------------------------------------------+
Total Time : 4.81
----------------------------------------------------------------------------------------------------
Experiment:  [WellingNormalized(), EffectiveResistance()]
Layers: 2
Dataset: crocodile
Dataset:  crocodile
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:76: UserWarning: Edge Weights are set to 1 automatically
  warnings.warn("Edge Weights are set to 1 automatically")
/home/ubuntu/graph-neural-networks/gnn/transforms/basic_transforms.py:181: UserWarning: test_val_split is ignored because train_mask and test_mask are provided by the dataset. Some datasets like Cora could not have labels for all nodes!
  warnings.warn(
Train Mask:  0.49110135436058044
Val Mask:  0.3124409019947052
Test Mask:  0.19645774364471436
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
┌ Warning: Calling sparsify with ep > 1 can produce a disconnected graph.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/sparsify.jl:18
┌ Warning: The matrix should not have any nonzero diagonal entries.
└ @ Laplacians ~/.julia/packages/Laplacians/G7S6S/src/solverInterface.jl:217
Adj shape (11631, 11631)
One hot encoding not working probably regression problem
Number of Edges: 51412
NONLINEAR: True
SIGMA_W: 1 SIGMA_B: 0.1
Find best regularization using val_mask
gnngp finished
Find best regularization using val_mask
gntk finished
+-------+---------------------------+------------------------------------+----------------------------------+--------------+----------------------------+----------------------+----------------------------------------------------------------------------------------+
|       |                           |                                    |                                  |              |                            |                      | Dataset: fcrocodile Layer: 2 Adjacency: [WellingNormalized(), EffectiveResistance()]   |
+=======+===========================+====================================+==================================+==============+============================+======================+========================================================================================+
| gnngp | ('kernel_fro', 344936.29) | ('train_loss_best_perf', 4989.113) | ('train_loss_no_reg', 15427.098) | ('reg', 0.1) | ('R_squared_train', 0.463) | ('R_squared', 0.422) | ('time', 33.8)                                                                         |
+-------+---------------------------+------------------------------------+----------------------------------+--------------+----------------------------+----------------------+----------------------------------------------------------------------------------------+
| gntk  | ('kernel_fro', 589596.38) | ('train_loss_best_perf', 5200.957) | ('train_loss_no_reg', 18681.955) | ('reg', 0.1) | ('R_squared_train', 0.44)  | ('R_squared', 0.383) | ('time', 33.8)                                                                         |
+-------+---------------------------+------------------------------------+----------------------------------+--------------+----------------------------+----------------------+----------------------------------------------------------------------------------------+
Total Time : 9.34