ENH: Optimize performance of np.atleast_1d

benchmarks/benchmarks/bench_shape_base.py

@@ -152,3 +152,19 @@ def time_scalar_kron(self):
 
     def time_mat_kron(self):
         np.kron(self.large_mat, self.large_mat)
+
+class AtLeast1D(Benchmark):
+    """Benchmarks for np.atleast_1d"""
+
+    def setup(self):
+        self.x = np.array([1, 2, 3])
+        self.zero_d = np.float64(1.)
+
+    def time_atleast_1d(self):
+        np.atleast_1d(self.x, self.x, self.x)
+
+    def time_atleast_1d_reshape(self):
+        np.atleast_1d(self.zero_d, self.zero_d, self.zero_d)
+
+    def time_atleast_1d_single_argument(self):
+        np.atleast_1d(self.x)

numpy/_core/shape_base.py

@@ -60,18 +60,18 @@ def atleast_1d(*arys):
     (array([1]), array([3, 4]))
 
     """
+    if len(arys) == 1:
+        result = asanyarray(arys[0])
+        if result.ndim == 0:
+            result = result.reshape(1)
+        return result
     res = []
     for ary in arys:
-        ary = asanyarray(ary)
-        if ary.ndim == 0:
-            result = ary.reshape(1)
-        else:
-            result = ary
+        result = asanyarray(ary)
+        if result.ndim == 0:
+            result = result.reshape(1)
         res.append(result)
-    if len(res) == 1:
-        return res[0]
-    else:
-        return tuple(res)
+    return tuple(res)
 
 
 def _atleast_2d_dispatcher(*arys):