fix: overload resolution bug

crates/erg_compiler/context/inquire.rs

@@ -1126,7 +1126,15 @@ impl Context {
                     _ => {}
                 }
                 if self.subtype_of(ty, &input_t) {
-                    return Ok(ty.clone());
+                    if let Ok(instance) = self.instantiate(ty.clone(), obj) {
+                        let subst = self
+                            .substitute_call(obj, &None, &instance, pos_args, kw_args, self)
+                            .is_ok();
+                        let eval = self.eval_t_params(instance, self.level, obj).is_ok();
+                        if subst && eval {
+                            return Ok(ty.clone());
+                        }
+                    }
                 }
             }
             let Type::Subr(subr_t) = input_t else {

crates/erg_compiler/lib/external/matplotlib.d/image.d.er

@@ -0,0 +1,4 @@
+_ImageBase: ClassType
+
+.AxesImage!: ClassType
+.AxesImage! <: _ImageBase

crates/erg_compiler/lib/external/matplotlib.d/pyplot.d/__init__.d.er

@@ -6,9 +6,12 @@ legend = pyimport "../legend"
 .style = pyimport "../style"
 figure = pyimport "../figure"
 axes = pyimport "../axes"
+image = pyimport "../image"
 
 .plot!: (*args: Obj, scaleX := Bool, scaleY := Bool) => [Obj; _]
+.imshow!: (X: Obj, cmap := Str, interpolation := Str) => image.AxesImage!
 .show!: () => NoneType
+.text!: (x: Float, y: Float, s: Str, fontdict := {Str: Obj}, fontsize := Nat) => text.Text
 .title!: (title: Str) => text.Text
 .xlabel!: (label: Str) => text.Text
 .ylabel!: (label: Str) => text.Text

crates/erg_compiler/lib/external/torch.d/__init__.d.er

@@ -1,3 +1,5 @@
+np = pyimport "numpy"
+
 .backends = pyimport "./backends"
 .cuda = pyimport "./cuda"
 .nn = pyimport "./nn"
@@ -33,9 +35,17 @@
 .Tensor!(T, S)|<: IrregularEq|.
     Output: {Tensor!(Bool, S)}
     __eq__: (self: .Tensor!(T, S), other: .Tensor!(T, S)) -> .Tensor!(Bool, S)
+.Tensor!(T, S)|<: Indexable(Nat, .Tensor!(T, _))|.
+    __getitem__: (self: .Tensor!(T, S), index: Nat or [Nat; _]) -> .Tensor!(T, _)
+.Tensor!(T, S).
+    data: .Tensor!(T, S)
 .Tensor!(_, _).
     dtype: .DType
     shape: .Size
+    clone: |T, S: [Nat; _]|(self: .Tensor!(T, S)) -> .Tensor!(T, S)
+    cpu: |T, S: [Nat; _]|(self: .Tensor!(T, S)) -> .Tensor!(T, S)
+    detach: |T, S: [Nat; _]|(self: .Tensor!(T, S)) -> .Tensor!(T, S)
+    numpy: |T, S: [Nat; _]|(self: .Tensor!(T, S)) -> np.NDArray(T, S)
     view: (|T, Old: [Nat; _], S: {A: [Nat; _] | A.prod() == Old.prod()}|(
         self: .Tensor!(T, Old),
         shape: {S},
@@ -64,6 +74,7 @@
         and (|T|(self: .Tensor!(T, _), dim: Nat) -> .Tensor!(T, _))
 
 .relu: |T, S: [Nat; _]|(x: .Tensor!(T, S)) -> .Tensor!(T, S)
+.softmax: |T, S: [Nat; _]|(x: .Tensor!(T, S), dim: Nat) -> .Tensor!(T, S)
 .max: (|T|(input: .Tensor!(T, _), dim: Nat, keepdim := Bool) -> (.Tensor!(T, _)), .Tensor!(T, _)) \
     and (|T|(input: .Tensor!(T, _)) -> .Tensor!(T, _))
 .min: (|T|(input: .Tensor!(T, _), dim: Nat, keepdim := Bool) -> (.Tensor!(T, _)), .Tensor!(T, _)) \

crates/erg_compiler/lib/external/torchvision.d/datasets.d/vision.d.er

@@ -1,7 +1,10 @@
 dataset = pyimport "torch/utils/data/dataset"
+{Tensor!;} = pyimport "torch"
 
 .VisionDataset: ClassType
 .VisionDataset <: dataset.Dataset
+.VisionDataset|<: Indexable(Nat, (Tensor!(Float, _), Tensor!(Float, _)))|.
+    __getitem__: (index: Nat) -> (Tensor!(Float, _), Tensor!(Float, _))
 .VisionDataset.
     __call__: (
         root: Str,