Download Built-in model parameters from ASE_ANI (#481)

* download resources from ASE_ANI

* update gitignore

* get resources with request

* fix flke8

* rm svn checkout for resources

* update

* fix flake8

torchani/resources/ani-1ccx_8x/train6/inputtrain.ipt

-!InputFile for Force Prediction Network
-sflparamsfile=rHCNO-5.2R_16-3.5A_a4-8.params
-ntwkStoreDir=networks/
-atomEnergyFile=sae_linfit.dat
-nmax=0! Maximum number of iterations (0 = inf)
-tolr=200! Tolerance - early stopping
-emult=0.5!Multiplier by eta after tol switch
-eta=0.001! Eta -- Learning rate
-tcrit=1.0E-6! Eta termination criterion
-tmax=0! Maximum time (0 = inf)
-tbtchsz=2560
-vbtchsz=2560
-gpuid=0
-ntwshr=0
-nkde=2
-energy=1
-freezelayer=0,2
-force=0
-fmult=0.0
-pbc=0
-cmult =0.001
-runtype=ANNP_CREATE_HDNN_AND_TRAIN!Create and train a HDN network
-network_setup {
-  inputsize=384;
-  atom_net H $
-    layer [
-          nodes=160;
-          activation=9;
-          type=0;
-    ]
-    layer [
-          nodes=128;
-          activation=9;
-          type=0;
-          l2norm=1;
-          l2valu=0.00001;
-    ]
-    layer [
-          nodes=96;
-          activation=9;
-          type=0;
-          l2norm=1;
-          l2valu=0.000001;
-    ]
-    layer [
-          nodes=1;
-          activation=6;
-          type=0;
-    ]
-    $
-  atom_net C $
-    layer [
-          nodes=144;
-          activation=9;
-          type=0;
-    ]
-    layer [
-          nodes=112;
-          activation=9;
-          type=0;
-          l2norm=1;
-          l2valu=0.00001;
-    ]
-    layer [
-          nodes=96;
-          activation=9;
-          type=0;
-          l2norm=1;
-          l2valu=0.000001;
-    ]
-    layer [
-          nodes=1;
-          activation=6;
-          type=0;
-    ]
-    $
-  atom_net N $
-    layer [
-          nodes=128;
-          activation=9;
-          type=0;
-    ]
-    layer [
-          nodes=112;
-          activation=9;
-          type=0;
-          l2norm=1;
-          l2valu=0.00001;
-    ]
-    layer [
-          nodes=96;
-          activation=9;
-          type=0;
-          l2norm=1;
-          l2valu=0.000001;
-    ]
-    layer [
-          nodes=1;
-          activation=6;
-          type=0;
-    ]
-    $
-  atom_net O $
-    layer [
-          nodes=128;
-          activation=9;
-          type=0;
-    ]
-    layer [
-          nodes=112;
-          activation=9;
-          type=0;
-          l2norm=1;
-          l2valu=0.00001;
-    ]
-    layer [
-          nodes=96;
-          activation=9;
-          type=0;
-          l2norm=1;
-          l2valu=0.000001;
-    ]
-    layer [
-          nodes=1;
-          activation=6;
-          type=0;
-    ]
-    $
-
-}
-adptlrn=OFF ! Adaptive learning (OFF,RMSPROP)
-decrate=0.9 !Decay rate of RMSPROP
-moment=ADAM! Turn on momentum or nesterov momentum (OFF,CNSTTEMP,TMANNEAL,REGULAR,NESTEROV)
-mu=0.99 ! Mu factor for momentum
-

torchani/resources/ani-1ccx_8x/train6/networks/ANN-C.nnf-l4.bparam

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torchani/resources/ani-1ccx_8x/train6/networks/ANN-C.nnf-l4.wparam

-,==6>bl<Ga=aEV3Fm=|0HWg=BGJB:}k=/=2eH):II'<%<X\>1>!-)<#+=G.E=)@=<NB<b.,0=i=ᘽ_̼ldL]1s=7>~=d==-=~N =o>g'	/=-\"idnQ==c_=%G-<]=aG}ຊ&>
-;<=[=\ʼ73q=az<[<G~?8v<ƣn!===DӼç$=.*M<2KOz
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torchani/resources/ani-1ccx_8x/train6/networks/ANN-H.nnf-l1.bparam

-C8-9giC;98暪mb{7?98d9>948?]#NP9Ѯ9M3za妹9<9_1129bhq8Ruzڽ8Lo6"5V47`7?80;C'8[e83@9q
-
-u;ُ8@gqӸ9S%85;5;O80#3	W;88`:OG5ԚM>vp5}1{56cָ._≸1ø,d8@EW
-rF$8y qfK8l#Rj8p99vJ8m6;Gc
6T8P89:6=]8$OHt/dJ船뙸5787@W>9`85"7 f q8Jl
ι5ùo@f8P8B89918&7ci78(@<
b.޸U*͏޸uX#37{P8:>97'87뉸
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torchani/resources/ani-1ccx_8x/train6/networks/ANN-H.nnf-l4.bparam

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