1 files changed, 203 insertions, 0 deletions
diff --git a/regmtl.py b/regmtl.py
new file mode 100755
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+++ b/regmtl.py
@@ -0,0 +1,203 @@
+#!/usr/bin/env python2.6
+
+"""
+mmert v0.2
+multi-task mert
+Copyright 2011
+Patrick Simianer
+Heidelberg University, ICL
+"""
+
+# This file is part of MMERT.
+#
+# MMERT is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# MMERT is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with MMERT.  If not, see <http://www.gnu.org/licenses/>.
+
+
+import os, sys, shutil
+
+
+def read_vec_from_file(fname):
+    """ File looks like: "w1 w2 ... wn" (on one line). """
+    return [float(el) for el in open(fname, 'r').read().strip().split()]
+
+def vec2str(vector):
+    """ vec looks like: [0., 1.1, 2.2, ..., d] """
+    return " ".join([str(el) for el in vector])
+
+def get_biggest_change(vector1, vector2):
+    """ Biggest difference of two vectors (element-wise) in abs value. """
+    biggest = 0
+    idx_ = 0
+    for element in vector1:
+        diff = abs(element - vector2[idx_])
+        if diff > biggest:
+            biggest = diff
+        idx_ += 1
+    return biggest
+
+def get_avg_vec(vecs, vec_len):
+    """ 'vecs' is a list of vectors; calc arithmetic mean element-wise. """
+    avg_vec = []
+    num_vecs = len(vecs)
+    for idx_ in range(vec_len):
+        mysum = 0.
+        for vector in vecs:
+            mysum += vector[idx_]
+        avg = mysum/num_vecs
+        avg_vec.append(avg)
+    return avg_vec
+
+def get_best_points_line_idx(lines):
+    """ Line number where to find best point in a mert.log. """
+    idx_ = 0
+    for line in lines:
+        if line.startswith("Best point: "):
+            break
+        idx_ += 1
+    return idx_
+
+def get_weights_from_log(fname):
+    """ Get weights from a mert.log. """
+    logfile = open(fname, "r")
+    lines = logfile.readlines()
+    logfile.close()
+    idx_ = get_best_points_line_idx(lines)
+    return [float(el) for el in \
+      lines[idx_].split("Best point: ")[1].split("=>")[0].split()]
+
+def write_new_log_file(fname, vec_):
+    """ Write a new mert.log file with weights found in vec. """
+    logfile = open(fname, "r")
+    lines = logfile.readlines()
+    logfile.close()
+    idx_ = get_best_points_line_idx(lines)
+    log = "".join(lines[0:idx_])
+    log += "Best point: "+vec2str(vec_)+" => 99\n"
+    log += "".join(lines[idx_+1:])
+    open(fname, "w+").write(log)
+
+
+
+
+# parameters
+DIR_PREFIX      = sys.argv[1]            # directory prefix
+                                         # (for task specific directories)
+WORKDIR         = sys.argv[2]            # work directory
+TASKS           = sys.argv[3].split(",") # task list "a,b,c..."
+CUR_IT          = int(sys.argv[4])       # current (global) iteration
+NUM_WEIGHTS     = int(sys.argv[5])       # dimensionality of a weight vector?
+MIN_CHANGE      = float(sys.argv[6])     # min change in a vector
+                                         # to still continue
+LAMBDA          = float(sys.argv[7])     # lambda for regularization
+FIRST_AVERAGE   = bool(int(sys.argv[8])) # first average vector,
+                                         # 0 or self provided
+
+print " CUR_IT %s" % str(CUR_IT)
+if CUR_IT == 1:
+    print " DIR_PREFIX %s" % DIR_PREFIX
+    print " WORKDIR %s" % WORKDIR
+    print " TASKS %s" % str(TASKS)
+    print " NUM_WEIGHTS %s" % str(NUM_WEIGHTS)
+    print " MIN_CHANGE %s" % str(MIN_CHANGE)
+    print " LAMBDA %s" % str(LAMBDA)
+    print " FIRST_AVERAGE %s" % str(FIRST_AVERAGE)
+    if not FIRST_AVERAGE:
+        print " first average is 0 vector, creating file.."
+        open(WORKDIR+"/run0.avector.txt", "w+").write(\
+          " ".join(["0.0" for i in range(NUM_WEIGHTS)]))
+    else:
+        print " looking for pre-defined first average.."
+        if not os.path.exists(WORKDIR+"/run0.avector.txt"):
+            sys.stderr.write(sys.argv[0] + \
+            " ERROR: You have to provide your own run0.avector.txt \
+            containing the first average vector! arg FIRST_AVERAGE=" \
+            +str(FIRST_AVERAGE)+"\n")
+            sys.exit (1)
+
+ITERATIONS = {} # current iteration(s)
+CUR_VECS   = {} # current weight vectors (from latest mert iteration)
+VEC_LEN    = 0  # check vector length
+for t in TASKS:
+    print " reading vector from task %s" % t
+    ITERATIONS[t] = int(open(DIR_PREFIX + "_" + t +\
+      "/finished_step.txt").read().strip())
+    cur = get_weights_from_log(DIR_PREFIX+"_"+t+"/run"+str((ITERATIONS[t])) + \
+                               ".mert.log")
+    print cur
+    VEC_LEN = len(cur)
+    if VEC_LEN != NUM_WEIGHTS:
+        sys.stderr.write(sys.argv[0] + \
+        " ERROR: vector lengths differ! (task: "+t+", len: "+str(VEC_LEN) + \
+        ", expected: "+str(NUM_WEIGHTS)+")\n")
+    CUR_VECS[t] = cur
+
+# get previous average vector
+PREV_AVG_VEC = read_vec_from_file(WORKDIR+"/run"+str(CUR_IT-1)+".avector.txt")
+print " Previous average vector (clip against):"
+print PREV_AVG_VEC 
+
+# new weight vecs
+print " Calculating new weight vectors (clipping).."
+NEXT_VECS = {}
+for (t, vec) in CUR_VECS.items():
+    print " Task %s, before (current)" % t
+    print vec
+    idx = 0
+    nxt = []
+    for w in vec:
+        if w == 0:
+            nxt.append(0.0)
+            idx += 1
+            continue
+        if (w - PREV_AVG_VEC[idx] > 0):
+            nxt.append(max(PREV_AVG_VEC[idx], w - LAMBDA))
+        elif (w - PREV_AVG_VEC[idx] < 0):
+            nxt.append(min(PREV_AVG_VEC[idx], w + LAMBDA))
+        else:
+            nxt.append(w)
+        idx += 1
+    NEXT_VECS[t] = nxt
+    print " Task %s, after (next)" % t
+    print nxt
+
+# get current average vector
+AVG_VEC = get_avg_vec(NEXT_VECS.values(), VEC_LEN)
+
+print " Current average vector (after clipping):"
+print AVG_VEC
+
+# convergence?
+print " Previous average:", PREV_AVG_VEC
+print "  Current average:", AVG_VEC
+BIGGEST_CHANGE = get_biggest_change(PREV_AVG_VEC, AVG_VEC)
+print "  Biggest change:", BIGGEST_CHANGE 
+# note: use weights from latest mert.log for eval!
+if BIGGEST_CHANGE < MIN_CHANGE:
+    print " Converged!"
+    open(WORKDIR+"/CONVERGED", "w+").close()
+
+# overwrite (and backup) mert.log
+for t in TASKS:
+    logfilename = DIR_PREFIX+"_"+t+"/run"+str(ITERATIONS[t])+".mert.log"
+    shutil.copy(logfilename, logfilename+".bak")
+    write_new_log_file(logfilename, NEXT_VECS[t])
+    open(DIR_PREFIX+"_"+t+"/weightshist", "a+").write(str(ITERATIONS[t])+"\n"+ \
+      "cur      "+str(CUR_VECS[t])+"\n"+ \
+      "prev avg "+str(PREV_AVG_VEC)+"\n"+ \
+      "next     "+str(NEXT_VECS[t])+"\n"+ \
+      "cur avg  "+str(AVG_VEC)+"\n---\n")
+    
+# write out current avg vector
+open(WORKDIR+"/run"+str(CUR_IT)+".avector.txt", "w+").write(vec2str(AVG_VEC))
+