Updating nn example and mliap .rst

doc/src/pair_mliap.rst

@@ -16,7 +16,7 @@ Syntax
   .. parsed-literal::
 
        *model* values = style filename
-         style = *linear* or *quadratic* or *mliappy*
+         style = *linear* or *quadratic* or *nn* or *mliappy*
          filename = name of file containing model definitions
        *descriptor* values = style filename
          style = *sna*
@@ -45,7 +45,7 @@ pair style currently supports just one descriptor style, but it is
 is straightforward to add new descriptor styles.
 The SNAP descriptor style *sna* is the same as that used by :doc:`pair_style snap <pair_snap>`,
 including the linear, quadratic, and chem variants.
-The available models are *linear*, *quadratic*, and *mliappy*.
+The available models are *linear*, *quadratic*, *nn*, and *mliappy*.
 The *mliappy* style can be used to couple python models,
 e.g. PyTorch neural network energy models, and requires building
 LAMMPS with the PYTHON package (see below).
@@ -77,13 +77,32 @@ line must contain two integers:
 * nelems  = Number of elements
 * nparams = Number of parameters
 
-This is followed by one block for each of the *nelem* elements.
+When the *model* keyword is *linear* or *quadratic*,
+this is followed by one block for each of the *nelem* elements.
 Each block consists of *nparams* parameters, one per line.
 Note that this format is similar, but not identical to that used
 for the :doc:`pair_style snap <pair_snap>` coefficient file.
 Specifically, the line containing the element weight and radius is omitted,
 since these are handled by the *descriptor*.
 
+When the *model* keyword is *nn* (neural networks), the model file can contain 
+blank and comment lines (start with #) anywhere. The second non-blank non-comment
+line must contain the string NET, followed by two integers:
+
+* ndescriptors = Number of descriptors
+* nlayers      = Number of layers (including the hidden layers and the output layer)
+
+and followed by a sequence of a string and an integer for each layer:
+
+* Activation function (linear, sigmoid, tanh or relu)
+* nnodes = Number of nodes
+
+This is followed by one block for each of the *nelem* elements. Each block consists
+of *scale0* minimum values, *scale1* (maximum - minimum) values,
+in order to normalize the descriptors, followed by *nparams* parameters, 
+including *bias* and *weights* of the model, starting with the first node of the first layer
+and so on, max. 30 parameters per line. 
+
 Notes on mliappy models:
 When the *model* keyword is *mliappy*, the filename should end in '.pt',
 '.pth' for pytorch models, or be a pickle file. To load a model from

examples/mliap/Cu_nn.mliap.model

@@ -0,0 +1,41 @@
+# DATE: 2021-03-03 UNITS: metal CONTRIBUTOR: Pedro Antonio Santos Florez pedroantoniosantosf@gmail.com  CITATION: none
+# Neural networks weights generated in PyXtal_FF 
+
+# total_species nparams 
+1 71 
+
+# NET ndescriptors nlayers activation_func for layer 1, number of nodes for layer 1, ..., ..., ...., 
+NET 30 3 tanh 2 tanh 2 linear 1 
+
+# Scale0 
+    98.5564567301067      0.1817576370006     -5.0513436999162      0.0453581866073     -4.4382278670569 
+    -2.6985391112026     -4.9445068940273      7.8840372041149    -12.8729456412560     -2.9748781222888 
+    -1.7702149043285     -4.6911979511282     -1.8167140506334     67.7067032503211    -12.5675074252146 
+   -10.3889411514447     -2.6194029974308      1.8750503488944     -5.0934919399232      4.2037760919263 
+    20.6488797181668     -8.2381178902428     -3.1311436510232     -1.1570117080256      2.1652328079269 
+     0.0854872341687     73.5970916724043     -5.3230176040510     -5.3409170596296     -6.4491186818574 
+
+# Scale1 
+   783.0204659783215     33.6453931227955      7.9068346594951     32.2509031640463      5.6624925894670 
+     5.6511565657016      8.2175114613285    108.9434600935519     16.3162547782998      6.4485086884047 
+     9.5767453287024     24.1576638495153     25.1723098340896    202.6741688060115     26.3843102888906 
+    19.7937707236334     13.9016635198379     14.1399097533048     72.7078614093291     39.8358080634714 
+   370.1745750951991     21.6864533954642     14.6554778261065     18.6456437491491     43.2946309680355 
+    68.9168418942695    481.9819429675007     14.5585849595560     61.9026061535013    112.5968384702330 
+
+# Coefficients
+  -0.2503221860648    0.4607794046378    0.4080552184108    0.0043328332206    0.2778722163950 
+  -0.0050555739235    0.0406748042003   -0.1188215011883    0.4669700426246    0.4050949681583 
+   0.3004118858813   -0.3937378155782    0.5165632847373    0.1381866719908   -0.3996533578004 
+   0.1330571447244    0.1124773980921    0.1548275555377   -0.6221152970188   -0.7813275942231 
+  -0.4320969824072    0.2045533448767   -0.1687644566507   -0.0424066840175   -0.1981208883936 
+  -0.3406471991751    0.1272788573915   -0.1236220514264    0.6482374783971   -0.0590428211363 
+   0.1326060235944    0.1890472518561   -0.5428894028577    0.0229420637813    0.0750842032804 
+  -0.2443049940974    0.5265826743321   -0.1802773940492    0.0309737044359   -0.4987806786020 
+  -0.6233577810656   -0.9910225261357    0.3430680860751    0.2918559145139    0.0666915892882 
+  -0.2558026088950    0.0417769401952   -0.2582828540822   -0.3685977011673    0.4793473883461 
+   1.0290706767456    0.0400544448686   -0.1474888333296    0.2403156153173    0.1050109023846 
+   0.1413378531949    0.0907250056918   -0.1185878739508    0.1471942864979   -0.2829701766758 
+   0.1137318187684    0.0476123438306    0.8040349098084   -0.5432518550512    0.2312003570779 
+   0.6886872913686   -0.1247049894693    0.6848986783339   -2.6353147047309   -0.7173579584864 
+  -1.0543148168289 

examples/mliap/Cu_snap.mliap.descriptor

@@ -0,0 +1,21 @@
+# DATE: 2021-03-03 UNITS: metal CONTRIBUTOR: Pedro Antonio Santos Florez pedroantoniosantosf@gmail.com  CITATION: none
+
+# LAMMPS SNAP parameters for Cu
+
+# required
+rcutfac 5.0
+twojmax 6
+
+# elements
+
+nelems 1
+elems Cu
+radelems 0.5
+welems 1.0
+
+# optional
+
+rfac0 0.99363
+rmin0 0
+bzeroflag 0
+switchflag 1

examples/mliap/in.mliap.snap.nn.Cu

@@ -0,0 +1,55 @@
+
+# Demonstrate MLIAP interface to SNAP nn Cu potential
+
+# Initialize simulation
+
+variable nsteps index 100
+variable nrep equal 4
+variable a equal 3.621262
+units           metal
+
+
+# generate the box and atom positions using a BCC lattice
+
+variable nx equal ${nrep}
+variable ny equal ${nrep}
+variable nz equal ${nrep}
+
+boundary        p p p
+
+lattice         fcc $a
+region          box block 0 ${nx} 0 ${ny} 0 ${nz}
+create_box      1 box
+create_atoms    1 box
+
+mass 1 63.546
+
+# choose potential
+
+pair_style mliap model nn Cu_nn.mliap.model descriptor sna Cu_snap.mliap.descriptor
+pair_coeff * * Cu Cu
+
+# Setup output
+
+compute  eatom all pe/atom
+compute  energy all reduce sum c_eatom
+
+compute  satom all stress/atom NULL
+compute  str all reduce sum c_satom[1] c_satom[2] c_satom[3]
+variable press equal (c_str[1]+c_str[2]+c_str[3])/(3*vol)
+
+thermo_style    custom step temp epair c_energy etotal press v_press
+thermo          10
+thermo_modify norm yes
+
+# Set up NVE run
+
+timestep 0.5e-3
+neighbor 1.0 bin
+neigh_modify once no every 1 delay 0 check yes
+
+# Run MD
+
+velocity all create 300.0 4928459 loop geom
+fix 1 all nve
+run             ${nsteps}