Add softmin, hardshrink, hardtanh (#1180)

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Co-authored-by: Nikhil Mehta <nikmehta@tesla.com>

benchmarks/python/compile_bench.py

@@ -9,7 +9,6 @@ from time_utils import time_fn
 
 
 def bench_gelu():
-
     def gelu(x):
         return x * (1 + mx.erf(x / math.sqrt(2))) / 2
 
@@ -51,7 +50,6 @@ def bench_gelu():
 
 
 def bench_layernorm():
-
     weight = mx.random.uniform(shape=(4096,)).astype(mx.float16)
     bias = mx.random.uniform(shape=(4096,)).astype(mx.float16)
     mx.eval(weight, bias)

benchmarks/python/conv_bench.py

@@ -54,7 +54,6 @@ def make_pt_conv_2D(strides=(1, 1), padding=(0, 0), groups=1):
 
 
 def bench_shape(N, H, W, C, kH, kW, O, strides, padding, groups, np_dtype):
-
     scale = 1.0 / math.sqrt(kH * kH * C)
     a_np = np.random.uniform(0, 0.5, (N, H, W, C)).astype(np_dtype)
     b_np = np.random.uniform(-scale, scale, (O, kH, kW, int(C / groups))).astype(

benchmarks/python/fft_bench.py

@@ -35,7 +35,6 @@ def run_bench(system_size):
 
 
 def time_fft():
-
     with mx.stream(mx.cpu):
         cpu_bandwidths = run_bench(system_size=int(2**22))
 

benchmarks/python/sdpa_bench.py

@@ -10,7 +10,6 @@ SEQ_INCREMENT = 50
 
 
 def time_self_attention_primitives():
-
     mx.random.seed(3)
     B = 2
     H = 38
@@ -32,7 +31,6 @@ def time_self_attention_primitives():
 
 
 def time_self_attention_sdpa():
-
     mx.random.seed(3)
     B = 2
     H = 38