Fix some typos in docstrings

lambeq/backend/pennylane.py

@@ -162,7 +162,7 @@ def to_pennylane(diagram: Diagram,
         Probabilities can be used with more PennyLane backpropagation
         methods.
     backend_config : dict, default: None
-        A dictionary of PennyLane backend configration options,
+        A dictionary of PennyLane backend configuration options,
         including the provider (e.g. IBM or Honeywell), the device,
         the number of shots, etc. See the `PennyLane plugin
         documentation <https://pennylane.ai/plugins/>`_

lambeq/backend/quantum.py

@@ -435,13 +435,13 @@ def to_pennylane(self, probabilities=False, backend_config=None,
 
         Parameters
         ----------
-        probabilties : bool, default: False
+        probabilities : bool, default: False
             If True, the PennylaneCircuit will return the normalized
-            probabilties of measuring the computational basis states
+            probabilities of measuring the computational basis states
             when run. If False, it returns the unnormalized quantum
             states in the computational basis.
         backend_config : dict, default: None
-            A dictionary of PennyLane backend configration options,
+            A dictionary of PennyLane backend configuration options,
             including the provider (e.g. IBM or Honeywell), the device,
             the number of shots, etc. See the `PennyLane plugin
             documentation <https://pennylane.ai/plugins/>`_

lambeq/experimental/discocirc/coref_resolver.py

@@ -31,7 +31,7 @@
 
 
 class CoreferenceResolver(ABC):
-    """Class implementing corefence resolution."""
+    """Class implementing coreference resolution."""
 
     @abstractmethod
     def tokenise_and_coref(
@@ -98,7 +98,7 @@ def dict_from_corefs(
 
 
 class MaverickCoreferenceResolver(CoreferenceResolver):
-    """Corefence resolution and tokenisation based on Maverick
+    """Coreference resolution and tokenisation based on Maverick
     (https://github.com/sapienzanlp/maverick-coref)."""
 
     def __init__(
@@ -167,7 +167,7 @@ def tokenise_and_coref(self, text: str) -> tuple[TokenisedTextT,
 
 
 class SpacyCoreferenceResolver(CoreferenceResolver):
-    """Corefence resolution and tokenisation based on spaCy."""
+    """Coreference resolution and tokenisation based on spaCy."""
 
     def __init__(self):
         # Create basic tokenisation pipeline, for POS

lambeq/training/numpy_model.py

@@ -83,7 +83,7 @@ def diagram_output(x: Iterable[ArrayLike]) -> ArrayLike:
                   tn.DefaultBackend('jax')):
                 sub_circuit = self._fast_subs([diagram], x)[0]
                 result = tn.contractors.auto(*sub_circuit.to_tn()).tensor
-                # square amplitudes to get probabilties for pure circuits
+                # square amplitudes to get probabilities for pure circuits
                 assert isinstance(sub_circuit, Circuit)
                 if not sub_circuit.is_mixed:
                     result = backend.abs(result) ** 2
@@ -141,7 +141,7 @@ def get_diagram_output(
         for d in diagrams:
             assert isinstance(d, Circuit)
             result = tn.contractors.auto(*d.to_tn()).tensor
-            # square amplitudes to get probabilties for pure circuits
+            # square amplitudes to get probabilities for pure circuits
             if not d.is_mixed:
                 result = np.abs(result) ** 2
             results.append(self._normalise_vector(result))