Apply suggestions from code review

Co-authored-by: Copilot <[email protected]>

Author: ricardoV94

.github/copilot-instructions.md

@@ -13,9 +13,9 @@ Emulate NumPy user-facing API as much as possible.
 
 1. **Lazy evaluation**: Expressions are symbolic until `pytensor.function()` compiles or `.eval()` evaluates
 2. **Pure semantics**: `new_x = x[idx].set(y)` instead of `x[idx] = y`
-3. **Immutable/hashable**: PyTensor variables are hashable. `a == b` tests identity (`a is b`), not elemntwise equality.
+3. **Immutable/hashable**: PyTensor variables are hashable. `a == b` tests identity (`a is b`), not elementwise equality.
 4. **Static shapes**: Broadcasting requires static shape of 1. Valid: `pt.add(pt.vector("x", shape=(1,)), pt.vector("y"))`. Invalid: `pt.add(pt.vector("x", shape=(None,)), pt.vector("y"))` with x.shape=1.
-5. **Static rank and type**. PyTensor functions accepts variables with a specfic dtype and number of dimensions. Length of each dimension can be static or dynamic.
+5. **Static rank and type**. PyTensor functions accepts variables with a specific dtype and number of dimensions. Length of each dimension can be static or dynamic.
 
 ## Code Style