X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=expr.py;h=685efd3b9319c87abe0e5c76e9c84e731904c10b;hb=HEAD;hp=d3883d58b55a435c98cd3c12a656d742ef43eb87;hpb=f29d0fa816414f74efed3b9ccdad56fdbd346298;p=picoclvr.git

diff --git a/expr.py b/expr.py
index d3883d5..685efd3 100755
--- a/expr.py
+++ b/expr.py
@@ -1,6 +1,11 @@
 #!/usr/bin/env python
 
-import math
+# Any copyright is dedicated to the Public Domain.
+# https://creativecommons.org/publicdomain/zero/1.0/
+
+# Written by Francois Fleuret <francois@fleuret.org>
+
+import math, re
 
 import torch, torchvision
 
@@ -16,49 +21,56 @@ def random_var(nb_variables=None, variables=None):
         return l[torch.randint(len(l), (1,)).item()]
 
 
-def random_expr(variables, budget):
+def random_expr(variables, operand_max, budget):
     if budget <= 5:
         op = torch.randint(2, (1,)).item()
         if op == 0 and len(variables) > 0:
             return random_var(variables=variables)
         else:
-            return str(torch.randint(10, (1,)).item())
+            return str(torch.randint(operand_max + 1, (1,)).item())
     else:
-        op = torch.randint(4, (1,)).item()
+        op = torch.randint(3, (1,)).item()
         if op == 0:
-            e = random_expr(variables, budget - 2)
+            e = random_expr(variables, operand_max, budget - 2)
             if ("+" in e or "-" in e or "*" in e) and (e[0] != "(" or e[-1] != ")"):
                 return "(" + e + ")"
             else:
                 return e
         else:
             b = 2 + torch.randint(budget - 5, (1,)).item()
-            e1 = random_expr(variables, b)
-            e2 = random_expr(variables, budget - b - 1)
+            e1 = random_expr(variables, operand_max, b)
+            e2 = random_expr(variables, operand_max, budget - b - 1)
             if op == 1:
                 return e1 + "+" + e2
             elif op == 2:
-                return e1 + "+" + e2
-            elif op == 3:
                 return e1 + "*" + e2
 
 
-def generate_program(nb_variables, length):
+def generate_program(nb_variables, operand_max, length):
     s = ""
     variables = set()
+
     while len(s) < length:
         v = random_var(nb_variables=nb_variables)
-        s += v + "=" + random_expr(variables, budget=20) + ";"
+        s += v + "=" + random_expr(variables, operand_max, budget=20) + ";"
         variables.add(v)
+
     return s, variables
 
 
-def generate_sequences(nb, nb_variables=5, length=20):
+def generate_sequences(nb, nb_variables=5, length=20, operand_max=9, result_max=99):
+    assert nb_variables <= 26
     sequences = []
+
     for n in range(nb):
+        # We take length itself half of the time, and uniform between
+        # 1 and length otherwise. The actual length can be slightly
+        # greater
+
+        l = min(length, 1 + torch.randint(length * 2, (1,)).item())
         result = None
-        while result == None or max(result.values()) > 100:
-            p, v = generate_program(nb_variables, length)
+        while result == None or max(result.values()) > result_max:
+            p, v = generate_program(nb_variables, operand_max, l)
             v = ", ".join(['"' + v + '": ' + v for v in v])
             ldict = {}
             exec(p + "result={" + v + "}", globals(), ldict)
@@ -66,17 +78,28 @@ def generate_sequences(nb, nb_variables=5, length=20):
 
         k = list(result.keys())
         k.sort()
-        sequences.append(p + " " + ";".join([v + ":" + str(result[v]) for v in k]))
+        sequences.append(p + " " + "".join([v + ":" + str(result[v]) + ";" for v in k]))
 
     return sequences
 
 
+def extract_results(seq):
+    f = lambda a: (a[0], -1 if a[1] == "" else int(a[1]))
+    results = [
+        dict([f(tuple(x.split(":"))) for x in re.findall("[A-Z]:[0-9]*", s)])
+        for s in seq
+    ]
+    return results
+
+
 if __name__ == "__main__":
     import time
 
     start_time = time.perf_counter()
-    sequences = generate_sequences(1000)
+    sequences = generate_sequences(1000, length=40)
     end_time = time.perf_counter()
     for s in sequences[:10]:
         print(s)
     print(f"{len(sequences) / (end_time - start_time):.02f} samples per second")
+
+    print(extract_results(sequences[:10]))