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* COPYRIGHT (c) 2010 The Diderot Project (http://diderot.cs.uchicago.edu) |
* COPYRIGHT (c) 2010 The Diderot Project (http://diderot.cs.uchicago.edu) |
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* All rights reserved. |
* All rights reserved. |
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* |
* |
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* Internal representation of Diderot types |
* Internal representation of Diderot types. These are the types produced |
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* by the type checker. |
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*) |
*) |
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structure Types = |
structure Types = |
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(* kinds for type variables *) |
(* kinds for type variables *) |
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datatype kind |
datatype kind |
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= TK_NAT (* ranges over natural numbers (0, 1, 2, ...) *) |
= TK_NAT (* ranges over natural numbers (0, 1, 2, ...) *) |
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| TK_INT (* ranges over integer types *) |
| TK_SHAPE (* ranges over tensor shapes *) |
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| TK_FLT (* ranges over floating-point types *) |
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| TK_RAW (* ranges over raw (scalar) types *) |
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| TK_TYPE (* ranges over types *) |
| TK_TYPE (* ranges over types *) |
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(* Question: do we want kinds for tensors of different orders (e.g., TK_TENSOR of word?); |
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* Then TK_RAW would be TK_TENSOR of 0w0. |
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*) |
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(* raw numeric types as supported by NRRD *) |
(* raw numeric types as supported by NRRD *) |
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datatype raw_ty |
datatype raw_ty |
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= T_Var of var |
= T_Var of var |
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| T_Bool |
| T_Bool |
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| T_Int |
| T_Int |
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(* scalars, vectors, matrices, etc. *) |
| T_String |
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| T_Tensor of nat list (* tensor shape *) |
(* convolution kernel; argument is number of levels of differentiation *) |
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| T_Kernel of nat |
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(* scalars, vectors, matrices, etc.; argument is tensor shape *) |
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| T_Tensor of shape |
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(* data sets from NRRD *) |
(* data sets from NRRD *) |
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| T_Image of { |
| T_Image of { |
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dim : nat, (* 2D or 3D data set *) |
dim : nat, (* 2D or 3D data set *) |
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shape : nat list (* tensor shape; order is length of list *) |
shape : shape (* tensor shape; order is length of list *) |
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} |
} |
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(* continuous field reconstructed from a data set *) |
(* continuous field reconstructed from a data set *) |
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| T_Field of { |
| T_Field of { |
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diff : nat, (* number of levels of differentiation supported *) |
diff : nat, (* number of levels of differentiation supported *) |
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dim : nat, (* dimension of domain (2D or 3D field) *) |
dim : nat, (* dimension of domain (2D or 3D field) *) |
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shape : nat list (* shape of tensors in range; order is length of list *) |
shape : shape (* shape of tensors in range; order is length of list *) |
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} |
} |
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| T_Fun of ty list * ty list |
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and shape |
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= Shape of nat list |
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| ShapeVar of var |
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| ShapeExt of shape * nat (* extension of shape (i.e., for D operator) *) |
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|
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and nat |
and nat |
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= NatConst of int (* i *) |
= NatConst of int (* i *) |
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stamp : Stamp.stamp |
stamp : Stamp.stamp |
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} |
} |
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type scheme = var list * ty |
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(* useful types *) |
(* useful types *) |
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val realTy = T_Tensor[] |
val realTy = T_Tensor(Shape[]) |
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fun vec2Ty = T_Tensor[NatConst 2] |
val vec2Ty = T_Tensor(Shape[NatConst 2]) |
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fun vec3Ty = T_Tensor[NatConst 3] |
val vec3Ty = T_Tensor(Shape[NatConst 3]) |
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fun vec4Ty = T_Tensor[NatConst 4] |
val vec4Ty = T_Tensor(Shape[NatConst 4]) |
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end |
end |
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