Add kitchen-sink base test

Author: lantiga

test/base.py

@@ -0,0 +1,44 @@
+import torch
+from torch.autograd import Variable
+import torch.nn as nn
+import torch.nn.functional as F
+
+import os
+import uuid
+import torch2c
+
+
+def base_test():
+
+    fc1 = nn.Linear(10,20)
+    fc1.weight.data.normal_(0.0,1.0)
+    fc1.bias.data.normal_(0.0,1.0)
+
+    fc2 = nn.Linear(20,2)
+    fc2.weight.data.normal_(0.0,1.0)
+    fc2.bias.data.normal_(0.0,1.0)
+
+    model_0 = lambda x: F.log_softmax(fc2(F.relu(fc1(x))))
+
+    fc3 = nn.Linear(10,2)
+    fc3.weight.data.normal_(0.0,1.0)
+    fc3.bias.data.normal_(0.0,1.0)
+
+    model_1 = lambda x: F.softmax(F.relu(fc3(x)))
+
+    data = Variable(torch.rand(10,10))
+
+    out = model_0(data) + model_1(data) + 1
+
+    out_path = 'out'
+    if not os.path.isdir(out_path):
+        os.mkdir(out_path)
+    uid = str(uuid.uuid4())
+
+    torch2c.compile(out,'base',os.path.join(out_path,uid),compile_test=True)
+ 
+
+if __name__=='__main__':
+
+    base_test()
+