WIP on outputting tensors from taco into file for pytest along with example data file that is incorrect

Author: weiya711

data/bench_ufunc_sparse_xor_10_010000_A.txt

@@ -0,0 +1,7 @@
+A (10x10) ({dense},{compressed}; 0,1):
+dense (0): 
+  [10]
+compressed (1): 
+  [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1]
+  [6]
+[1]

data/bench_ufunc_sparse_xor_10_010000_B.txt

@@ -0,0 +1,7 @@
+B (10x10) ({dense},{compressed}; 0,1):
+dense (0): 
+  [10]
+compressed (1): 
+  [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2]
+  [2, 7]
+[1, 1]

data/bench_ufunc_sparse_xor_10_010000_C.txt

@@ -0,0 +1,7 @@
+C (10x10) ({dense},{compressed}; 0,1):
+dense (0): 
+  [10]
+compressed (1): 
+  [0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 3]
+  [2, 6, 7]
+[1, 1, 1]

numpy/ufuncs.py

@@ -39,9 +39,6 @@ def import_tensor(filename, dim):
         lines = f.readlines()
 
         count = 0
-        indptr = 0
-        indices = 0
-        data = 0
         for line in lines:
             count += 1
             if count == 5:
@@ -62,7 +59,13 @@ def import_tensor(filename, dim):
 def get_ufunc_str(ufunc):
     if ufunc == numpy.logical_xor:
         return "xor"
-@pytest.mark.parametrize("dim", [250, 500, 750, 1000, 2500, 5000, 7500, 8000])
+    if ufunc == numpy.right_shift:
+        return ">>"
+    if ufunc == numpy.ldexp:
+        return "2^"
+
+#@pytest.mark.parametrize("dim", [250, 500, 750, 1000, 2500, 5000, 7500, 8000])
+@pytest.mark.parametrize("dim", [10])
 @pytest.mark.parametrize("ufunc", [numpy.logical_xor])
 def bench_pydata_import_ufunc_sparse(tacoBench, dim, ufunc):
     filenameA = "./data/bench_ufunc_sparse_"

taco/ufuncs.cpp

@@ -120,6 +120,9 @@ static void bench_ufunc_sparse(benchmark::State& state, ExtraArgs&&... extra_arg
   A.pack(); B.pack();
 
   // Output tensors to file
+  // FIXME (owhsu): Why for dim == 10, does the CSR dense mode repeat indices?
+  //                This is causing a problem for the format of csr_matrix(...) in pytest
+  //                See <repo>/data/* for examples
   printTensor(A, "./data", __FUNCTION__ , dim, extra_args...);
   printTensor(B, "./data", __FUNCTION__ , dim, extra_args...);
 
@@ -135,11 +138,14 @@ static void bench_ufunc_sparse(benchmark::State& state, ExtraArgs&&... extra_arg
 
     // The actual computation.
     result.compute();
+    state.PauseTiming();
+    printTensor(result, "./data", __FUNCTION__, dim, extra_args...);
+    state.ResumeTiming();
   }
 }
 static void applyBenchSizes(benchmark::internal::Benchmark* b) {
-   b->ArgsProduct({{250, 500, 750, 1000, 2500, 5000, 7500, 8000}});
-  //b->ArgsProduct({{2, 4, 10}});
+  // b->ArgsProduct({{250, 500, 750, 1000, 2500, 5000, 7500, 8000}});
+  b->ArgsProduct({{10}});
 }
 
 TACO_BENCH_ARGS(bench_ufunc_sparse, xor_0.01, 0.01, "xor")->Apply(applyBenchSizes);