Add in some changes to get benchmarks working

Author: Olivia W Hsu

numpy/conftest.py

@@ -1,11 +1,13 @@
 import pytest
 @pytest.fixture
 def tacoBench(benchmark):
-    def f(func, extra_info = None):
+    def f(func, extra_info = None, save_ret_val = False):
         # Take statistics based on 10 rounds.
         if extra_info is not None:
             for k, v in extra_info.items():
                 benchmark.extra_info[k] = v
+        if save_ret_val:
+            benchmark.extra_info["return"] = func()
         benchmark.pedantic(func, rounds=10, iterations=1, warmup_rounds=1)
     return f
 

numpy/minmax.py

@@ -14,19 +14,19 @@ def bench_pydata_minmax(tacoBench, dims):
     #       and not just sparse uniform sampling
 
     matrix = loader.tensor(dims_list)
+    extra_info = dict()
+    extra_info["nnz"] = matrix.nnz
     def bench():
         reduced = matrix
         for m in range(len(dims_list)):   
             if m % 2 == 0: 
                 reduced = np.max(reduced, -1)
             else:
                 reduced = np.min(reduced, -1)     
-            print(reduced)
         return reduced
-    tacoBench(bench)
-    red = bench()
-    print("reduced value for", dims, "is", red)
+    tacoBench(bench, extra_info, True)
 
+@pytest.mark.skip(reason="Only to get matrix statistics")
 @pytest.mark.parametrize("dims", [1, 3, 5])
 def bench_minmax_statistics(tacoBench, dims):
     loader = MinMaxPydataSparseTensorLoader()

numpy/util.py

@@ -450,7 +450,7 @@ def construct_minmax_tensor_key(dims, variant=None):
     return os.path.join(path, name, key)
 
 def generate_crds_helper(shape, level, crds):
-    sampling = 0.4
+    sampling = 0.1
     num = 4
     std = 2 
 

scripts/minimax_runner.sh

@@ -15,4 +15,4 @@ mkdir -p "data/minmax"
 
 jsonout="$out/statistics-numpy.json"
 
-LANKA=ON NUMPY_JSON="$jsonout" make python-bench BENCHES="numpy/minmax.py::bench_minmax_statistics"
+LANKA=ON NUMPY_JSON="$jsonout" make python-bench BENCHES="numpy/minmax.py::bench_pydata_minmax" 

taco/minimax.cpp

@@ -81,6 +81,7 @@ static void bench_minimax(benchmark::State& state) {
 
   std::vector<int> dims = {20, 20, 43, 43, 43, 43, 43};
   dims.resize(order);
+  double return_value;
   // TODO (rohany, owhsu): We need to actually generate the input game state.
   for (auto _ : state) {
     state.PauseTiming();
@@ -91,8 +92,9 @@ static void bench_minimax(benchmark::State& state) {
 //    std::cout << result.getSource() << std::endl;
     state.ResumeTiming();
     result.compute();
-//    state.PauseTiming();
-//    cout << "Reduced value" << result << endl;
+    state.PauseTiming();
+    return_value = result();
   }
+  state.counters["return"] = return_value;
 }
 TACO_BENCH(bench_minimax);