WIP load tensors from file into python benchmark test for ufunc

Author: weiya711

numpy/ufuncs.py

@@ -1,5 +1,5 @@
 import numpy
-from scipy.sparse import random
+from scipy.sparse import random, csr_matrix
 import sparse
 import pytest
 
@@ -10,6 +10,7 @@ def myfunc(x, y):
 myufunc = numpy.frompyfunc(myfunc, 2, 1, identity=0)
 
 # @pytest.mark.parametrize("dim", [5000, 10000, 20000])
+@pytest.mark.skip(reason="Not testing this right now")
 @pytest.mark.parametrize("dim", [250, 500, 750, 1000, 2500, 5000, 7500, 8000])
 @pytest.mark.parametrize("ufunc", [numpy.logical_xor, numpy.logical_or, numpy.right_shift, numpy.ldexp])
 def bench_ufunc_dense(tacoBench, dim, ufunc):
@@ -21,6 +22,7 @@ def bench():
 
 # TODO (rohany): We can parametrize this over the sparsity as well.
 # @pytest.mark.parametrize("dim", [5000, 10000, 20000])
+@pytest.mark.skip(reason="Not testing this right now")
 @pytest.mark.parametrize("dim", [250, 500, 750, 1000, 2500, 5000, 7500, 8000])
 @pytest.mark.parametrize("ufunc", [numpy.logical_xor, numpy.logical_or, numpy.right_shift, numpy.ldexp])
 def bench_pydata_ufunc_sparse(tacoBench, dim, ufunc):
@@ -29,3 +31,54 @@ def bench_pydata_ufunc_sparse(tacoBench, dim, ufunc):
     def bench():
         C = ufunc(A, B)
     tacoBench(bench)
+
+
+def import_tensor(filename, dim):
+    print(filename)
+    with open(filename, 'r') as f:
+        lines = f.readlines()
+        
+        count = 0
+        indptr = 0
+        indices = 0
+        data = 0
+        for line in lines:
+            count += 1
+            if count == 5:
+                indptr = line
+                indptr = indptr[3: -2]
+            if count == 6:
+                indices = line
+                indices = indices[3: -2]
+            if count == 7:
+                data = line
+                data = data[1: -2]
+        print("indptr", indptr)
+        indptr = numpy.fromstring(indptr, dtype=int, sep=",")
+        indices = numpy.fromstring(indices, dtype=int, sep=",")
+        data = numpy.fromstring(data, dtype=float, sep=",")
+    return indptr, indices, data
+
+def get_ufunc_str(ufunc):
+    if ufunc == numpy.logical_xor:
+        return "xor"
+@pytest.mark.parametrize("dim", [250, 500, 750, 1000, 2500, 5000, 7500, 8000])
+@pytest.mark.parametrize("ufunc", [numpy.logical_xor])
+def bench_pydata_import_ufunc_sparse(tacoBench, dim, ufunc):
+    filenameA = "./data/bench_ufunc_sparse_"
+    filenameA += get_ufunc_str(ufunc)
+    filenameA += "_" + str(dim) + "_" + "010000_A.txt"
+    indptrA, indicesA, dataA = import_tensor(filenameA, dim)
+
+    A = csr_matrix((dataA, indicesA, indptrA), shape=(dim, dim)).toarray()
+
+    filenameB = "./data/bench_ufunc_sparse_"
+    filenameB += get_ufunc_str(ufunc)
+    filenameB += "_" + str(dim) + "_" + "010000_B.txt"
+    indptrB, indicesB, dataB = import_tensor(filenameB, dim)
+    B = csr_matrix((dataB, indicesB, indptrB), shape=(dim, dim)).toarray()
+    def bench():
+        C = ufunc(A, B)
+        return C
+    tacoBench(bench)
+    print("Result", bench())

taco/ufuncs.cpp

@@ -73,10 +73,9 @@ void printTensor(TensorBase tensor,  std::string location, std::string benchName
 
   std::string sparseStr = std::to_string(sparsity);
   sparseStr = sparseStr.substr(2, sparseStr.size());
-  std::string filename = location + "/" + benchName + "_" + tensor.getName() + "_" + opType + "_" + \
-                          std::to_string(dim) + "_" + sparseStr  + ".txt";
+  std::string filename = location + "/" + benchName + "_" + opType + "_" + \
+                          std::to_string(dim) + "_" + sparseStr + "_" + tensor.getName()  + ".txt";
   std::ofstream outfile(filename, std::ofstream::out);
-  std::cout << filename << std::endl;
   outfile << util::toString(tensor);
   outfile.close();
 }
@@ -119,7 +118,7 @@ static void bench_ufunc_sparse(benchmark::State& state, ExtraArgs&&... extra_arg
     }
   }
   A.pack(); B.pack();
-
+  
   // Output tensors to file
   printTensor(A, "./data", __FUNCTION__ , dim, extra_args...);
   printTensor(B, "./data", __FUNCTION__ , dim, extra_args...);
@@ -139,7 +138,8 @@ static void bench_ufunc_sparse(benchmark::State& state, ExtraArgs&&... extra_arg
   }
 }
 static void applyBenchSizes(benchmark::internal::Benchmark* b) {
-  b->ArgsProduct({{250, 500, 750, 1000, 2500, 5000, 7500, 8000}});
+   b->ArgsProduct({{250, 500, 750, 1000, 2500, 5000, 7500, 8000}});
+  //b->ArgsProduct({{2, 4, 10}});
 }
 
 TACO_BENCH_ARGS(bench_ufunc_sparse, xor_0.01, 0.01, "xor")->Apply(applyBenchSizes);