BENCH: cover integer max/min and fmax/fmin tests

  also covers variant of strides sizes

2 files changed, 40 insertions, 13 deletions

diff --git a/benchmarks/benchmarks/bench_reduce.py b/benchmarks/benchmarks/bench_reduce.py
index 7b05f4fcc..81316c492 100644
--- a/benchmarks/benchmarks/bench_reduce.py
+++ b/benchmarks/benchmarks/bench_reduce.py
@@ -46,7 +46,8 @@ class AnyAll(Benchmark):
 
 
 class MinMax(Benchmark):
-    params = [np.float32, np.float64, np.intp]
+    params = [np.int8, np.uint8, np.int16, np.uint16, np.int32, np.uint32,
+              np.int64, np.uint64, np.float32, np.float64, np.intp]
     param_names = ['dtype']
 
     def setup(self, dtype):
@@ -58,8 +59,21 @@ class MinMax(Benchmark):
     def time_max(self, dtype):
         np.max(self.d)
 
+class FMinMax(Benchmark):
+    params = [np.float32, np.float64]
+    param_names = ['dtype']
+
+    def setup(self, dtype):
+        self.d = np.ones(20000, dtype=dtype)
+
+    def time_min(self, dtype):
+        np.fmin.reduce(self.d)
+
+    def time_max(self, dtype):
+        np.fmax.reduce(self.d)
+
 class ArgMax(Benchmark):
-    params = [np.float32, bool]
+    params = [np.float32, np.float64, bool]
     param_names = ['dtype']
 
     def setup(self, dtype):
diff --git a/benchmarks/benchmarks/bench_ufunc_strides.py b/benchmarks/benchmarks/bench_ufunc_strides.py
index 75aa510a6..b751e4804 100644
--- a/benchmarks/benchmarks/bench_ufunc_strides.py
+++ b/benchmarks/benchmarks/bench_ufunc_strides.py
@@ -44,27 +44,40 @@ class AVX_UFunc_log(Benchmark):
     def time_log(self, stride, dtype):
         np.log(self.arr[::stride])
 
-avx_bfuncs = ['maximum',
-              'minimum']
 
-class AVX_BFunc(Benchmark):
+binary_ufuncs = [
+    'maximum', 'minimum', 'fmax', 'fmin'
+]
+binary_dtype = ['f', 'd']
 
-    params = [avx_bfuncs, dtype, stride]
-    param_names = ['avx_based_bfunc', 'dtype', 'stride']
+class Binary(Benchmark):
+    param_names = ['ufunc', 'stride_in0', 'stride_in1', 'stride_out', 'dtype']
+    params = [binary_ufuncs, stride, stride, stride_out, binary_dtype]
     timeout = 10
 
-    def setup(self, ufuncname, dtype, stride):
+    def setup(self, ufuncname, stride_in0, stride_in1, stride_out, dtype):
         np.seterr(all='ignore')
         try:
             self.f = getattr(np, ufuncname)
         except AttributeError:
             raise NotImplementedError(f"No ufunc {ufuncname} found") from None
-        N = 10000
-        self.arr1 = np.array(np.random.rand(stride*N), dtype=dtype)
-        self.arr2 = np.array(np.random.rand(stride*N), dtype=dtype)
+        N = 100000
+        self.arr1 = np.array(np.random.rand(stride_in0*N), dtype=dtype)
+        self.arr2 = np.array(np.random.rand(stride_in1*N), dtype=dtype)
+        self.arr_out = np.empty(stride_out*N, dtype)
 
-    def time_ufunc(self, ufuncname, dtype, stride):
-        self.f(self.arr1[::stride], self.arr2[::stride])
+    def time_ufunc(self, ufuncname, stride_in0, stride_in1, stride_out, dtype):
+        self.f(self.arr1[::stride_in0], self.arr2[::stride_in1],
+               self.arr_out[::stride_out])
+
+
+binary_int_ufuncs = ['maximum', 'minimum']
+binary_int_dtype = ['b', 'B', 'h', 'H', 'i', 'I', 'l', 'L', 'q', 'Q']
+
+class BinaryInt(Binary):
+
+    param_names = ['ufunc', 'stride_in0', 'stride_in1', 'stride_out', 'dtype']
+    params = [binary_int_ufuncs, stride, stride, stride_out, binary_int_dtype]
 
 class AVX_ldexp(Benchmark):