[core] toplevel: Add view functions category
Based on 9e0f636d
: core: categorize np_{transpose,reshape} as 'view
functions'
This commit is contained in:
parent
c7192f861b
commit
297078ed61
@ -373,6 +373,10 @@ impl<'a> BuiltinBuilder<'a> {
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self.build_ndarray_property_getter_function(prim)
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}
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PrimDef::FunNpTranspose | PrimDef::FunNpReshape => {
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self.build_ndarray_view_function(prim)
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}
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PrimDef::FunStr => self.build_str_function(),
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PrimDef::FunFloor | PrimDef::FunFloor64 | PrimDef::FunCeil | PrimDef::FunCeil64 => {
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@ -438,10 +442,6 @@ impl<'a> BuiltinBuilder<'a> {
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| PrimDef::FunNpHypot
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| PrimDef::FunNpNextAfter => self.build_np_2ary_function(prim),
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PrimDef::FunNpTranspose | PrimDef::FunNpReshape => {
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self.build_np_sp_ndarray_function(prim)
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}
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PrimDef::FunNpDot
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| PrimDef::FunNpLinalgCholesky
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| PrimDef::FunNpLinalgQr
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@ -1326,6 +1326,60 @@ impl<'a> BuiltinBuilder<'a> {
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}
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}
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/// Build np/sp functions that take as input `NDArray` only
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fn build_ndarray_view_function(&mut self, prim: PrimDef) -> TopLevelDef {
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debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpTranspose, PrimDef::FunNpReshape]);
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match prim {
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PrimDef::FunNpTranspose => {
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let ndarray_ty = self.unifier.get_fresh_var_with_range(
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&[self.ndarray_num_ty],
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Some("T".into()),
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None,
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);
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create_fn_by_codegen(
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self.unifier,
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&into_var_map([ndarray_ty]),
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prim.name(),
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ndarray_ty.ty,
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&[(ndarray_ty.ty, "x")],
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// TODO(Derppening): Fix this refactor - This currently causes an unresolved TVar
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// self.ndarray_num_ty,
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// &[(self.ndarray_num_ty, "x")],
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Box::new(move |ctx, _, fun, args, generator| {
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let arg_ty = fun.0.args[0].ty;
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let arg_val =
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args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
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Ok(Some(ndarray_transpose(generator, ctx, (arg_ty, arg_val))?))
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}),
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)
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}
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// NOTE: on `ndarray_factory_fn_shape_arg_tvar` and
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// the `param_ty` for `create_fn_by_codegen`.
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//
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// Similar to `build_ndarray_from_shape_factory_function` we delegate the responsibility of typechecking
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// to [`typecheck::type_inferencer::Inferencer::fold_numpy_function_call_shape_argument`],
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// and use a dummy [`TypeVar`] `ndarray_factory_fn_shape_arg_tvar` as a placeholder for `param_ty`.
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PrimDef::FunNpReshape => create_fn_by_codegen(
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self.unifier,
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&VarMap::new(),
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prim.name(),
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self.ndarray_num_ty,
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&[(self.ndarray_num_ty, "x"), (self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
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Box::new(move |ctx, _, fun, args, generator| {
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let x1_ty = fun.0.args[0].ty;
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let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
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let x2_ty = fun.0.args[1].ty;
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let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
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Ok(Some(ndarray_reshape(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?))
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}),
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),
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_ => unreachable!(),
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}
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}
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/// Build the `str()` function.
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fn build_str_function(&mut self) -> TopLevelDef {
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let prim = PrimDef::FunStr;
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@ -1813,57 +1867,6 @@ impl<'a> BuiltinBuilder<'a> {
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}
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}
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/// Build np/sp functions that take as input `NDArray` only
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fn build_np_sp_ndarray_function(&mut self, prim: PrimDef) -> TopLevelDef {
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debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpTranspose, PrimDef::FunNpReshape]);
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match prim {
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PrimDef::FunNpTranspose => {
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let ndarray_ty = self.unifier.get_fresh_var_with_range(
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&[self.ndarray_num_ty],
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Some("T".into()),
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None,
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);
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create_fn_by_codegen(
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self.unifier,
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&into_var_map([ndarray_ty]),
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prim.name(),
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ndarray_ty.ty,
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&[(ndarray_ty.ty, "x")],
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Box::new(move |ctx, _, fun, args, generator| {
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let arg_ty = fun.0.args[0].ty;
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let arg_val =
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args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
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Ok(Some(ndarray_transpose(generator, ctx, (arg_ty, arg_val))?))
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}),
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)
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}
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// NOTE: on `ndarray_factory_fn_shape_arg_tvar` and
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// the `param_ty` for `create_fn_by_codegen`.
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//
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// Similar to `build_ndarray_from_shape_factory_function` we delegate the responsibility of typechecking
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// to [`typecheck::type_inferencer::Inferencer::fold_numpy_function_call_shape_argument`],
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// and use a dummy [`TypeVar`] `ndarray_factory_fn_shape_arg_tvar` as a placeholder for `param_ty`.
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PrimDef::FunNpReshape => create_fn_by_codegen(
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self.unifier,
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&VarMap::new(),
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prim.name(),
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self.ndarray_num_ty,
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&[(self.ndarray_num_ty, "x"), (self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
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Box::new(move |ctx, _, fun, args, generator| {
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let x1_ty = fun.0.args[0].ty;
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let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
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let x2_ty = fun.0.args[1].ty;
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let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
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Ok(Some(ndarray_reshape(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?))
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}),
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),
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_ => unreachable!(),
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}
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}
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/// Build `np_linalg` and `sp_linalg` functions
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///
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/// The input to these functions must be floating point `NDArray`
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@ -59,6 +59,10 @@ pub enum PrimDef {
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FunNpShape,
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FunNpStrides,
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// NumPy ndarray view functions
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FunNpTranspose,
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FunNpReshape,
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// Miscellaneous NumPy & SciPy functions
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FunNpRound,
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FunNpFloor,
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@ -106,8 +110,6 @@ pub enum PrimDef {
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FunNpLdExp,
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FunNpHypot,
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FunNpNextAfter,
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FunNpTranspose,
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FunNpReshape,
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// Linalg functions
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FunNpDot,
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@ -250,6 +252,10 @@ impl PrimDef {
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PrimDef::FunNpShape => fun("np_shape", None),
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PrimDef::FunNpStrides => fun("np_strides", None),
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// NumPy NDArray view functions
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PrimDef::FunNpTranspose => fun("np_transpose", None),
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PrimDef::FunNpReshape => fun("np_reshape", None),
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// Miscellaneous NumPy & SciPy functions
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PrimDef::FunNpRound => fun("np_round", None),
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PrimDef::FunNpFloor => fun("np_floor", None),
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@ -297,8 +303,6 @@ impl PrimDef {
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PrimDef::FunNpLdExp => fun("np_ldexp", None),
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PrimDef::FunNpHypot => fun("np_hypot", None),
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PrimDef::FunNpNextAfter => fun("np_nextafter", None),
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PrimDef::FunNpTranspose => fun("np_transpose", None),
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PrimDef::FunNpReshape => fun("np_reshape", None),
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// Linalg functions
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PrimDef::FunNpDot => fun("np_dot", None),
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@ -8,5 +8,5 @@ expression: res_vec
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"Function {\nname: \"B.foo\",\nsig: \"fn[[b:T], none]\",\nvar_id: []\n}\n",
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"Class {\nname: \"Generic_A\",\nancestors: [\"Generic_A[V]\", \"B\"],\nfields: [\"aa\", \"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\"), (\"fun\", \"fn[[a:int32], V]\")],\ntype_vars: [\"V\"]\n}\n",
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"Function {\nname: \"Generic_A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(251)]\n}\n",
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"Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(250)]\n}\n",
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]
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@ -7,7 +7,7 @@ expression: res_vec
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"Function {\nname: \"A.__init__\",\nsig: \"fn[[t:T], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"A.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
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"Function {\nname: \"A.foo\",\nsig: \"fn[[c:C], none]\",\nvar_id: []\n}\n",
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"Class {\nname: \"B\",\nancestors: [\"B[typevar235]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar235\"]\n}\n",
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"Class {\nname: \"B\",\nancestors: [\"B[typevar234]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar234\"]\n}\n",
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"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"B.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
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"Class {\nname: \"C\",\nancestors: [\"C\", \"B[bool]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\", \"e\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: []\n}\n",
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@ -5,8 +5,8 @@ expression: res_vec
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[
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"Function {\nname: \"foo\",\nsig: \"fn[[a:list[int32], b:tuple[T, float]], A[B, bool]]\",\nvar_id: []\n}\n",
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"Class {\nname: \"A\",\nancestors: [\"A[T, V]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[v:V], none]\"), (\"fun\", \"fn[[a:T], V]\")],\ntype_vars: [\"T\", \"V\"]\n}\n",
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"Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(248)]\n}\n",
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"Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(253)]\n}\n",
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"Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(247)]\n}\n",
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"Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(252)]\n}\n",
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"Function {\nname: \"gfun\",\nsig: \"fn[[a:A[list[float], int32]], none]\",\nvar_id: []\n}\n",
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"Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [],\nmethods: [(\"__init__\", \"fn[[], none]\")],\ntype_vars: []\n}\n",
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"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
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@ -3,7 +3,7 @@ source: nac3core/src/toplevel/test.rs
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expression: res_vec
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---
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[
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"Class {\nname: \"A\",\nancestors: [\"A[typevar234, typevar235]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar234\", \"typevar235\"]\n}\n",
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"Class {\nname: \"A\",\nancestors: [\"A[typevar233, typevar234]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar233\", \"typevar234\"]\n}\n",
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"Function {\nname: \"A.__init__\",\nsig: \"fn[[a:A[float, bool], b:B], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"A.fun\",\nsig: \"fn[[a:A[float, bool]], A[bool, int32]]\",\nvar_id: []\n}\n",
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"Class {\nname: \"B\",\nancestors: [\"B\", \"A[int64, bool]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\"), (\"foo\", \"fn[[b:B], B]\"), (\"bar\", \"fn[[a:A[list[B], int32]], tuple[A[virtual[A[B, int32]], bool], B]]\")],\ntype_vars: []\n}\n",
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@ -6,12 +6,12 @@ expression: res_vec
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"Class {\nname: \"A\",\nancestors: [\"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
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"Function {\nname: \"A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"A.fun\",\nsig: \"fn[[b:B], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [TypeVarId(254)]\n}\n",
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"Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [TypeVarId(253)]\n}\n",
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"Class {\nname: \"C\",\nancestors: [\"C\", \"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
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"Function {\nname: \"C.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"C.fun\",\nsig: \"fn[[b:B], none]\",\nvar_id: []\n}\n",
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"Class {\nname: \"B\",\nancestors: [\"B\", \"C\", \"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
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"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"foo\",\nsig: \"fn[[a:A], none]\",\nvar_id: []\n}\n",
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"Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(262)]\n}\n",
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"Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(261)]\n}\n",
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]
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@ -179,6 +179,10 @@ def patch(module):
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module.np_identity = np.identity
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module.np_array = np.array
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# NumPy NDArray view functions
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module.np_transpose = np.transpose
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module.np_reshape = np.reshape
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# NumPy NDArray property getters
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module.np_size = np.size
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module.np_shape = np.shape
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@ -223,8 +227,6 @@ def patch(module):
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module.np_ldexp = np.ldexp
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module.np_hypot = np.hypot
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module.np_nextafter = np.nextafter
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module.np_transpose = np.transpose
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module.np_reshape = np.reshape
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# SciPy Math functions
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module.sp_spec_erf = special.erf
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