fixes

utils/similarity/__main__.py

@@ -11,7 +11,7 @@ from .test     import test
 from .train    import train
 
 logging.basicConfig()
-logger = logging.getLogger("Slither")
+logger = logging.getLogger("Slither-simil")
 
 slither_simil_usage = "USAGE" # TODO 
 modes = ["info", "test", "train"]

utils/similarity/cache.py

@@ -19,4 +19,4 @@ def load_cache(infile, model, ext=None, solc='solc'):
     return cache
 
 def save_cache(cache, outfile):
-    np.savez(outfile,[np.array(list(cache.items()))])
+    np.savez(outfile,[np.array(cache)])

utils/similarity/encode.py

@@ -172,7 +172,7 @@ def encode_contract(filename, solc):
                 if function.nodes == []:
                     continue
 
-                x = "-".join([filename,contract.name,function.name]) 
+                x = (filename,contract.name,function.name) 
 
                 r[x] = []
 

utils/similarity/test.py

@@ -23,6 +23,7 @@ def test(args):
         solc = args.solc
         infile = args.input
         ext = args.filter
+
         if filename is None or contract is None or fname is None or infile is None:
             logger.error('The test mode requires filename, contract, fname and input parameters.')
             sys.exit(-1)
@@ -31,8 +32,7 @@ def test(args):
         if len(irs) == 0:
             sys.exit(-1)
 
-        x = "-".join([filename,contract,fname])
-        y = " ".join(irs[x])
+        y = " ".join(irs[(filename,contract,fname)])
         
         fvector = model.get_sentence_vector(y)
         cache = load_cache(infile, model, ext=ext, solc=solc)

utils/similarity/train.py

@@ -3,9 +3,11 @@ import logging
 import sys
 import traceback
 import operator
+import os
 
 from fastText import train_unsupervised
-from .encode import encode_contract, load_contracts
+from .encode  import encode_contract, load_contracts
+from .cache   import save_cache
 
 logger = logging.getLogger("Slither-simil")
 
@@ -25,15 +27,26 @@ def train(args):
 
         contracts = load_contracts(dirname, ext=ext, nsamples=nsamples)
         logger.info('Saving extracted data into', last_data_train_filename)
+        cache = []
         with open(last_data_train_filename, 'w') as f:
-            for contract in contracts: 
-                for function,ir in encode_contract(contract,solc).items():
+            for filename in contracts:
+                #cache[filename] = dict()
+                for (filename, contract, function), ir in encode_contract(filename,solc).items():
                     if ir != []:
-                        f.write(" ".join(ir)+"\n")
-    
+                        x = " ".join(ir)
+                        f.write(x+"\n")
+                        cache.append((os.path.split(filename)[-1], contract, function, x))
+
+        logger.info('Starting training')
         model = train_unsupervised(input=last_data_train_filename, model='skipgram')
+        logger.info('Training complete')
         model.save_model(model_filename)
-        print(model.get_words())
+
+        for i,(filename, contract, function, irs) in enumerate(cache):
+            cache[i] = ((filename, contract, function), model.get_sentence_vector(irs))
+
+        logger.info('Saved cache in cache.npz')
+        save_cache(cache, "cache.npz")
  
     except Exception:
         logger.error('Error in %s' % args.filename)