Adding a test for generator support (#171)

* Add a test for generators

* Remove output annotations from decorators

Also guarded torch imports for better compatibility with
requirements.txt

* Add flag to the main meta class to skip the typecheck

* Return to the old solution

* Make async tests work

* Minor adjustments/fixing typos

* Correct Python path for new tests

* Remove some jax-dependent code

* Implement equality for MetaArrays

* Make all Dim variations frozen dataclasses

* Shorten AbstractArray methods

* Final touches

* Removing get_origin use

* Update tests with @jaxtyp

test/test_serialisation.py

@@ -1,16 +1,25 @@
 import cloudpickle
 import numpy as np
-import torch
+
+
+try:
+    import torch
+except ImportError:
+    torch = None
 
 from jaxtyping import AbstractArray, Array, Shaped
 
 
 def test_pickle():
     x = cloudpickle.dumps(Shaped[Array, ""])
-    y = cloudpickle.dumps(AbstractArray)
-    z = cloudpickle.dumps(Shaped[np.ndarray, ""])
-    w = cloudpickle.dumps(Shaped[torch.Tensor, ""])
     cloudpickle.loads(x)
+
+    y = cloudpickle.dumps(AbstractArray)
     cloudpickle.loads(y)
+
+    z = cloudpickle.dumps(Shaped[np.ndarray, ""])
     cloudpickle.loads(z)
-    cloudpickle.loads(w)
+
+    if torch is not None:
+        w = cloudpickle.dumps(Shaped[torch.Tensor, ""])
+        cloudpickle.loads(w)