X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=svrtset.py;h=8bfdde199bd1c858d30ee42fe3e0ebbe30eeb860;hb=faac6461d3482204898ad97f811f58889cc37e1d;hp=cbc71a373237356007bca386de4890036ac902e5;hpb=b6cc25f4622917b0025d613d617b5ce9e23f07e9;p=pysvrt.git

diff --git a/svrtset.py b/svrtset.py
index cbc71a3..8bfdde1 100755
--- a/svrtset.py
+++ b/svrtset.py
@@ -41,17 +41,18 @@ def generate_one_batch(s):
 
 class VignetteSet:
 
-    def __init__(self, problem_number, nb_samples, batch_size, cuda = False):
+    def __init__(self, problem_number, nb_samples, batch_size, cuda = False, logger = None):
 
         if nb_samples%batch_size > 0:
             print('nb_samples must be a multiple of batch_size')
             raise
 
         self.cuda = cuda
-        self.batch_size = batch_size
         self.problem_number = problem_number
-        self.nb_batches = nb_samples // batch_size
-        self.nb_samples = self.nb_batches * self.batch_size
+
+        self.batch_size = batch_size
+        self.nb_samples = nb_samples
+        self.nb_batches = self.nb_samples // self.batch_size
 
         seeds = torch.LongTensor(self.nb_batches).random_()
         mp_args = []
@@ -61,6 +62,7 @@ class VignetteSet:
         self.data = []
         for b in range(0, self.nb_batches):
             self.data.append(generate_one_batch(mp_args[b]))
+            if logger is not None: logger(self.nb_batches * self.batch_size, b * self.batch_size)
 
         # Weird thing going on with the multi-processing, waiting for more info
 
@@ -88,17 +90,19 @@ class VignetteSet:
 ######################################################################
 
 class CompressedVignetteSet:
-    def __init__(self, problem_number, nb_samples, batch_size, cuda = False):
+    def __init__(self, problem_number, nb_samples, batch_size, cuda = False, logger = None):
 
         if nb_samples%batch_size > 0:
             print('nb_samples must be a multiple of batch_size')
             raise
 
         self.cuda = cuda
-        self.batch_size = batch_size
         self.problem_number = problem_number
-        self.nb_batches = nb_samples // batch_size
-        self.nb_samples = self.nb_batches * self.batch_size
+
+        self.batch_size = batch_size
+        self.nb_samples = nb_samples
+        self.nb_batches = self.nb_samples // self.batch_size
+
         self.targets = []
         self.input_storages = []
 
@@ -111,6 +115,7 @@ class CompressedVignetteSet:
             acc_sq += input.float().pow(2).sum() /  input.numel()
             self.targets.append(target)
             self.input_storages.append(svrt.compress(input.storage()))
+            if logger is not None: logger(self.nb_batches * self.batch_size, b * self.batch_size)
 
         self.mean = acc / self.nb_batches
         self.std = sqrt(acc_sq / self.nb_batches - self.mean * self.mean)