[Docs] Add docstrings for nn.Module classes and core APIs in relax.frontend.nn

python/tvm/relax/frontend/nn/core.py

@@ -123,7 +123,25 @@ def from_scalar(data: int | float, dtype: str) -> "Tensor":
 
     @staticmethod
     def from_struct_info(struct_info: rx.TensorStructInfo, name: str = "tensor") -> "Tensor":
-        """Construct a nn.Tensor from relax TensorStructInfo"""
+        """Construct a nn.Tensor from a Relax TensorStructInfo.
+
+        TensorStructInfo is the Relax type-level description of a tensor, carrying its shape
+        and dtype without holding actual data. This factory creates an unbound placeholder
+        ``nn.Tensor`` that can be used as a symbolic input when tracing an ``nn.Module``.
+
+        Parameters
+        ----------
+        struct_info : rx.TensorStructInfo
+            The struct info describing the tensor's shape and dtype.
+
+        name : str
+            Name hint for the underlying Relax variable.
+
+        Returns
+        -------
+        tensor : Tensor
+            A symbolic ``nn.Tensor`` backed by a ``relax.Var`` with the given struct info.
+        """
         return Tensor(
             _expr=rx.Var(
                 name_hint=name,
@@ -492,7 +510,36 @@ def jit(  # pylint: disable=too-many-arguments
         out_format: str = "torch",
         debug: bool = False,
     ) -> Any:
-        """Just-in-time compilation of a nn.model to an executable"""
+        """Just-in-time compile an ``nn.Module`` into a callable executable.
+
+        The method exports the module to a Relax IRModule, applies the given compilation
+        pipeline, builds a Relax VM executable, and wraps the result so it can be called
+        directly (e.g. with PyTorch tensors when ``out_format="torch"``).
+
+        Parameters
+        ----------
+        spec : _spec.ModuleSpec
+            A specification mapping each module input to its shape and dtype.
+
+        device : Union[str, Device]
+            The device to compile and run on (e.g. ``"cpu"``, ``"cuda"``).
+
+        pipeline : Union[None, str, Pass]
+            The Relax compilation pipeline to apply. ``"default_build"`` uses the standard
+            optimization pipeline; ``None`` skips pipeline passes.
+
+        out_format : str
+            Output wrapper format. ``"torch"`` returns a ``TorchModule`` whose ``forward``
+            accepts and returns PyTorch tensors.
+
+        debug : bool
+            If ``True``, enable effect-based debugging (e.g. printing) in the compiled graph.
+
+        Returns
+        -------
+        module : Any
+            A callable wrapper (type depends on *out_format*) around the compiled VM.
+        """
 
         def _compile(spec, device, pipeline, debug):
             # pylint: disable=import-outside-toplevel