Moved all mliappy files in to src/MLIAP and examples/mliap

examples/mliap/convert_mliap_Ta06A.py

@@ -0,0 +1,33 @@
+import sys
+import numpy as np
+import torch
+import pickle
+import os
+import shutil
+
+shutil.copyfile('../../src/MLIAP/mliappy_pytorch.py','./mliappy_pytorch.py')
+
+import mliappy_pytorch
+
+# Read coefficients
+coeffs = np.genfromtxt("Ta06A.mliap.model",skip_header=6)
+
+# Write coefficients to a pytorch linear model
+bias = coeffs[0]
+weights = coeffs[1:]
+lin = torch.nn.Linear(weights.shape[0],1)
+lin.to(torch.float64)
+with torch.autograd.no_grad():
+    lin.weight.set_(torch.from_numpy(weights).unsqueeze(0))
+    lin.bias.set_(torch.as_tensor(bias,dtype=torch.float64).unsqueeze(0))
+
+# Wrap the pytorch model for usage with MLIAPPY
+model = mliappy_pytorch.IgnoreElems(lin)
+n_descriptors = lin.weight.shape[1]
+n_params = mliappy_pytorch.calc_n_params(model)
+n_types = 1
+linked_model = mliappy_pytorch.TorchWrapper64(model,n_descriptors=n_descriptors,n_elements=n_types)
+
+# Save the result.
+with open("Ta06A.mliap.pytorch.model.pkl",'wb') as pfile:
+    pickle.dump(linked_model,pfile)