doc: fix warnings

Author: mariogeiger

e3nn_jax/_src/linear_flax.py

@@ -31,7 +31,7 @@ class Linear(flax.linen.Module):
             0/1 corresponds to a normalization where each element/path has an equal contribution to the learning.
         num_indexed_weights (optional int): number of indexed weights. See example below.
         weights_per_channel (bool): whether to have one set of weights per channel.
-        force_irreps_out (bool): whether to force the output irreps to be the one specified in `irreps_out`.
+        force_irreps_out (bool): whether to force the output irreps to be the one specified in ``irreps_out``.
 
     Examples:
         Vanilla::

e3nn_jax/_src/linear_haiku.py

@@ -32,7 +32,7 @@ class Linear(hk.Module):
         get_parameter (optional Callable): function to get the parameters.
         num_indexed_weights (optional int): number of indexed weights. See example below.
         weights_per_channel (bool): whether to have one set of weights per channel.
-        force_irreps_out (bool): whether to force the output irreps to be the one specified in `irreps_out`.
+        force_irreps_out (bool): whether to force the output irreps to be the one specified in ``irreps_out``.
         name (optional str): name of the module.
 
     Examples:

e3nn_jax/_src/utils/test.py

@@ -93,7 +93,7 @@ def assert_(x, y):
 
 
 def assert_output_dtype_matches_input_dtype(fun: Callable, *args, **kwargs):
-    """Checks that the dtype of fun(*args, **kwargs) matches that of the input (*args, **kwargs).
+    """Checks that the dtype of ``fun(*args, **kwargs)`` matches that of the input ``(*args, **kwargs)``.
 
     Args:
         fun: function to test