parameterize functions tests by batch size

benchmarks/functions/pooling/average_pooling_2d.py

@@ -2,15 +2,16 @@
 
 from benchmarks.functions import FunctionBenchmark
 from benchmarks.utils import backends
+from benchmarks.utils import parameterize
 
 
 @backends('gpu', 'gpu-cudnn', 'cpu', 'cpu-ideep')
+@parameterize([('batches', [1, 16])])
 class AveragePooling2D(FunctionBenchmark):
-    def setup(self):
+    def setup(self, batches):
         xp = self.xp
 
         # Prepare test data.
-        batches = 16
         channels = 4
         x_size = (128, 128)
         ksize = 4
@@ -25,8 +26,8 @@ def setup(self):
         # Setup benchmark.
         self.setup_benchmark(F.average_pooling_2d, (x, ksize), gy)
 
-    def time_forward(self):
+    def time_forward(self, batches):
         self.forward()
 
-    def time_backward(self):
+    def time_backward(self, batches):
         self.backward()

benchmarks/functions/pooling/average_pooling_nd.py

@@ -2,15 +2,16 @@
 
 from benchmarks.functions import FunctionBenchmark
 from benchmarks.utils import backends
+from benchmarks.utils import parameterize
 
 
 @backends('gpu', 'gpu-cudnn', 'cpu')
+@parameterize([('batches', [1, 16])])
 class AveragePoolingND(FunctionBenchmark):
-    def setup(self):
+    def setup(self, batches):
         xp = self.xp
 
         # Prepare test data.
-        batches = 16
         channels = 4
         x_size = (32, 32, 16, 16)
         ksize = 4
@@ -25,8 +26,8 @@ def setup(self):
         # Setup benchmark.
         self.setup_benchmark(F.average_pooling_nd, (x, ksize), gy)
 
-    def time_forward(self):
+    def time_forward(self, batches):
         self.forward()
 
-    def time_backward(self):
+    def time_backward(self, batches):
         self.backward()

benchmarks/functions/pooling/max_pooling_2d.py

@@ -2,15 +2,16 @@
 
 from benchmarks.functions import FunctionBenchmark
 from benchmarks.utils import backends
+from benchmarks.utils import parameterize
 
 
 @backends('gpu', 'gpu-cudnn', 'cpu', 'cpu-ideep')
+@parameterize([('batches', [1, 16])])
 class MaxPooling2D(FunctionBenchmark):
-    def setup(self):
+    def setup(self, batches):
         xp = self.xp
 
         # Prepare test data.
-        batches = 16
         channels = 4
         x_size = (128, 128)
         ksize = 4
@@ -25,8 +26,8 @@ def setup(self):
         # Setup benchmark.
         self.setup_benchmark(F.max_pooling_2d, (x, ksize), gy)
 
-    def time_forward(self):
+    def time_forward(self, batches):
         self.forward()
 
-    def time_backward(self):
+    def time_backward(self, batches):
         self.backward()

benchmarks/functions/pooling/max_pooling_nd.py

@@ -2,15 +2,16 @@
 
 from benchmarks.functions import FunctionBenchmark
 from benchmarks.utils import backends
+from benchmarks.utils import parameterize
 
 
 @backends('gpu', 'gpu-cudnn', 'cpu')
+@parameterize([('batches', [1, 16])])
 class MaxPoolingND(FunctionBenchmark):
-    def setup(self):
+    def setup(self, batches):
         xp = self.xp
 
         # Prepare test data.
-        batches = 16
         channels = 4
         x_size = (32, 32, 16, 16)
         ksize = 4
@@ -25,8 +26,8 @@ def setup(self):
         # Setup benchmark.
         self.setup_benchmark(F.max_pooling_nd, (x, ksize), gy)
 
-    def time_forward(self):
+    def time_forward(self, batches):
         self.forward()
 
-    def time_backward(self):
+    def time_backward(self, batches):
         self.backward()

benchmarks/functions/pooling/roi_pooling_2d.py

@@ -4,15 +4,16 @@
 
 from benchmarks.functions import FunctionBenchmark
 from benchmarks.utils import backends
+from benchmarks.utils import parameterize
 
 
 @backends('gpu', 'cpu')
+@parameterize([('batches', [1, 16])])
 class ROIPooling2D(FunctionBenchmark):
-    def setup(self):
+    def setup(self, batches):
         xp = self.xp
 
         # Prepare test data.
-        batches = 16
         channels = 4
         x_size = (128, 128)
         out_size = (32, 32)
@@ -36,8 +37,8 @@ def setup(self):
         self.setup_benchmark(F.roi_pooling_2d,
                              (x, rois) + out_size + (spatial_scale,), gy)
 
-    def time_forward(self):
+    def time_forward(self, batches):
         self.forward()
 
-    def time_backward(self):
+    def time_backward(self, batches):
         self.backward()

benchmarks/functions/pooling/spatial_pyramid_pooling_2d.py

@@ -4,15 +4,16 @@
 
 from benchmarks.functions import FunctionBenchmark
 from benchmarks.utils import backends
+from benchmarks.utils import parameterize
 
 
 @backends('gpu', 'gpu-cudnn', 'cpu')
+@parameterize([('batches', [1, 16])])
 class SpatialPyramidPooling2D(FunctionBenchmark):
-    def setup(self):
+    def setup(self, batches):
         xp = self.xp
 
         # Prepare test data.
-        batches = 16
         channels = 4
         x_size = (128, 128)
         pyramid_height = 4
@@ -31,8 +32,8 @@ def setup(self):
         self.setup_benchmark(F.spatial_pyramid_pooling_2d,
                              (x, pyramid_height, None, 'max'), gy)
 
-    def time_forward(self):
+    def time_forward(self, batches):
         self.forward()
 
-    def time_backward(self):
+    def time_backward(self, batches):
         self.backward()

benchmarks/functions/pooling/unpooling_2d.py

@@ -6,15 +6,16 @@
 
 from benchmarks.functions import FunctionBenchmark
 from benchmarks.utils import backends
+from benchmarks.utils import parameterize
 
 
 @backends('gpu', 'gpu-cudnn', 'cpu')
+@parameterize([('batches', [1, 16])])
 class Unpooling2D(FunctionBenchmark):
-    def setup(self):
+    def setup(self, batches):
         xp = self.xp
 
         # Prepare test data.
-        batches = 16
         channels = 4
         ih, iw = (128, 128)
         ksize = 4
@@ -32,8 +33,8 @@ def setup(self):
         # Setup benchmark.
         self.setup_benchmark(F.unpooling_2d, (x, ksize), gy)
 
-    def time_forward(self):
+    def time_forward(self, batches):
         self.forward()
 
-    def time_backward(self):
+    def time_backward(self, batches):
         self.backward()

benchmarks/functions/pooling/unpooling_nd.py

@@ -6,15 +6,16 @@
 
 from benchmarks.functions import FunctionBenchmark
 from benchmarks.utils import backends
+from benchmarks.utils import parameterize
 
 
 @backends('gpu', 'gpu-cudnn', 'cpu')
+@parameterize([('batches', [1, 16])])
 class UnpoolingND(FunctionBenchmark):
-    def setup(self):
+    def setup(self, batches):
         xp = self.xp
 
         # Prepare test data.
-        batches = 16
         channels = 4
         in_size = (32, 32, 32)
         ksize = 4
@@ -32,8 +33,8 @@ def setup(self):
         # Setup benchmark.
         self.setup_benchmark(F.unpooling_nd, (x, ksize), gy)
 
-    def time_forward(self):
+    def time_forward(self, batches):
         self.forward()
 
-    def time_backward(self):
+    def time_backward(self, batches):
         self.backward()