Fix doc issues in mlx.nn.init.he_normal and mlx.nn.hard_tanh (#2968)

Co-authored-by: Awni Hannun <awni@apple.com>

Author: Redempt1onzzZZ

python/mlx/nn/init.py

@@ -100,7 +100,7 @@ def identity(dtype: mx.Dtype = mx.float32) -> Callable[[mx.array], mx.array]:
     r"""An initializer that returns an identity matrix.
 
     Args:
-        dtype (Dtype, optional): The data type of the array. Defaults:
+        dtype (Dtype, optional): The data type of the array. Default:
           ``float32``.
 
     Returns:
@@ -253,7 +253,7 @@ def he_normal(
     <https://arxiv.org/abs/1502.01852>`_
 
     Args:
-        dtype (Dtype, optional): The data type of the array. Defaults to mx.float32.
+        dtype (Dtype, optional): The data type of the array. Default: ``float32``.
 
     Returns:
         Callable[[array, str, float], array]: An initializer that returns an

python/mlx/nn/layers/activations.py

@@ -299,7 +299,7 @@ def hardswish(x):
 def hard_tanh(x, min_val=-1.0, max_val=1.0):
     r"""Applies the HardTanh function.
 
-    Applies :math:`\max(\min(x, \text{max\_val}), \text{min\_val})` element-wise.
+    Applies :math:`\max(\min(x, \mathrm{max\_val}), \mathrm{min\_val})` element-wise.
     """
     return mx.minimum(mx.maximum(x, min_val), max_val)