Supporting materials for the PR4

Author: ASvyatkovskiy

examples/compare_batch_iterators.py

@@ -0,0 +1,75 @@
+#!/usr/bin/env python
+from functools import partial
+from itertools import tee
+
+class Loader():
+    def example_batch_generator(self,n):
+        for batch in range(n):
+            yield batch
+
+class MPIModel():
+    def __init__(self,batch_generator):
+        self.batch_iterator = batch_generator
+
+    def train_epochs(self,M):
+        num_total = 8
+        for epoch in range(M):
+            num_so_far = 0
+            print ("Batch iter. summary: {}{}".format(self,self.batch_iterator))
+            for batch in self.batch_iterator():
+                num_so_far += 1
+
+                whatever=batch
+                print ("Next batch id: {}".format(batch))
+                if num_so_far > num_total: break
+            print "+++++++"
+
+
+class MPIModel_default():
+    def __init__(self,batch_generator):
+        self.batch_iterator = batch_generator
+
+    def train_epochs(self,M):
+        num_total = 8 #number of samples per epoch
+        batch_generator_func = self.batch_iterator()
+
+        for iepoch in range(M):
+            #print ("Batch iter. summary: {}{} epoch: {}".format(self,self.batch_iterator,iepoch))
+            num_so_far = 0
+
+            while num_so_far < num_total:
+                num_so_far += 1
+
+                try:
+                    batch = batch_generator_func.next()
+                except:
+                    batch_generator_func = self.batch_iterator()
+                    batch = batch_generator_func.next()
+                print ("Next batch id: {}".format(batch))
+
+            print "+++++++"
+
+
+
+def main():
+    num_batches = 10
+    epochs = 3
+
+    loader = Loader()
+    batch_generator = partial(loader.example_batch_generator,n=num_batches)
+    my_example_class = MPIModel(batch_generator)
+    my_example_class.train_epochs(epochs)
+
+def main_default():
+    num_batches = 10
+    epochs = 3
+
+    loader = Loader()
+    batch_generator = partial(loader.example_batch_generator,n=num_batches)
+    my_example_class = MPIModel_default(batch_generator)
+    my_example_class.train_epochs(epochs)
+
+if __name__=='__main__':
+    import timeit
+    #print min(timeit.Timer(setup=main).repeat(7, 1000))
+    print min(timeit.Timer(setup=main_default).repeat(7, 1000))