diff --git a/src/pystencils/backend/kernelcreation/context.py b/src/pystencils/backend/kernelcreation/context.py
index 9ebc913d5a60e956c9f4af2a64cb3c5cd78f7aa6..ffa400a16dcadb4e91de55fbfb54b627a0dfd57e 100644
--- a/src/pystencils/backend/kernelcreation/context.py
+++ b/src/pystencils/backend/kernelcreation/context.py
@@ -6,12 +6,11 @@ from types import EllipsisType
from ...defaults import DEFAULTS
from ...field import Field, FieldType
-from ...sympyextensions.typed_sympy import TypedSymbol, BasicType, StructType
+from ...sympyextensions.typed_sympy import TypedSymbol
from ..symbols import PsSymbol
from ..arrays import PsLinearizedArray
-from ...types import PsAbstractType, PsIntegerType, PsNumericType
-from ...types.quick import make_type
+from ...types import PsAbstractType, PsIntegerType, PsNumericType, PsScalarType, PsStructType
from ..constraints import PsKernelParamsConstraint
from ..exceptions import PsInternalCompilerError, KernelConstraintsError
@@ -216,8 +215,8 @@ class KernelCreationContext:
# Add array
assert arr_strides is not None
- assert isinstance(field.dtype, (BasicType, StructType))
- element_type = make_type(field.dtype.numpy_dtype)
+ assert isinstance(field.dtype, (PsScalarType, PsStructType))
+ element_type = field.dtype
arr = PsLinearizedArray(
field.name, element_type, arr_shape, arr_strides, self.index_dtype
diff --git a/src/pystencils/backend/kernelcreation/freeze.py b/src/pystencils/backend/kernelcreation/freeze.py
index d0bca50a0bd44ebe1f9d914d33efc8a280080fa6..2d10b0c0ce6ab7bc0b154d370ba04d14cd9f0149 100644
--- a/src/pystencils/backend/kernelcreation/freeze.py
+++ b/src/pystencils/backend/kernelcreation/freeze.py
@@ -5,7 +5,7 @@ from operator import add, mul
import sympy as sp
from ...sympyextensions import Assignment, AssignmentCollection
-from ...sympyextensions.typed_sympy import BasicType
+from ...sympyextensions.typed_sympy import TypedSymbol
from ...field import Field, FieldType
from .context import KernelCreationContext
@@ -27,7 +27,7 @@ from ..ast.expressions import (
)
from ..constants import PsConstant
-from ...types import constify, make_type, PsAbstractType, PsStructType
+from ...types import PsStructType
from ..exceptions import PsInputError
from ..functions import PsMathFunction, MathFunctions
@@ -118,16 +118,8 @@ class FreezeExpressions:
denom = PsConstantExpr(PsConstant(expr.denominator))
return num / denom
- def map_type(self, expr: BasicType) -> PsAbstractType:
- # TODO: This should not be necessary; the frontend should use the new type system.
- dtype = make_type(expr.numpy_dtype.type)
- if expr.const:
- return constify(dtype)
- else:
- return dtype
-
- def map_TypedSymbol(self, expr):
- dtype = self.map_type(expr.dtype)
+ def map_TypedSymbol(self, expr: TypedSymbol):
+ dtype = expr.dtype
symb = self._ctx.get_symbol(expr.name, dtype)
return PsSymbolExpr(symb)
diff --git a/src/pystencils/backend/kernelcreation/typification.py b/src/pystencils/backend/kernelcreation/typification.py
index 5c041fb2a74dde777002c8f3fea18db85bd4d704..2f6b5b33b3fdc6fcdc1f2f253bae1818d0dd3b06 100644
--- a/src/pystencils/backend/kernelcreation/typification.py
+++ b/src/pystencils/backend/kernelcreation/typification.py
@@ -197,7 +197,7 @@ class Typifier:
"Aggregate type of lookup was not a struct type."
)
- member = aggr_type.get_member(member_name)
+ member = aggr_type.find_member(member_name)
if member is None:
raise TypificationError(
f"Aggregate of type {aggr_type} does not have a member {member}."
diff --git a/src/pystencils/backend/transformations/erase_anonymous_structs.py b/src/pystencils/backend/transformations/erase_anonymous_structs.py
index ecca07aea426f0b4455f258c36616861385bf7a2..c946ae7bb1e30b8ad80cf41b9e4425c1ba4eb2ad 100644
--- a/src/pystencils/backend/transformations/erase_anonymous_structs.py
+++ b/src/pystencils/backend/transformations/erase_anonymous_structs.py
@@ -85,7 +85,7 @@ class EraseAnonymousStructTypes:
)
member_name = lookup.member_name
- member = struct_type.get_member(member_name)
+ member = struct_type.find_member(member_name)
assert member is not None
np_struct = struct_type.numpy_dtype
diff --git a/src/pystencils/field.py b/src/pystencils/field.py
index 389413f2530a791ba923e5eac5cff5f0b4352982..253c94fc0f4a209fcf59d434f9cb78881e8370ab 100644
--- a/src/pystencils/field.py
+++ b/src/pystencils/field.py
@@ -14,8 +14,8 @@ from sympy.core.cache import cacheit
from pystencils.alignedarray import aligned_empty
from pystencils.spatial_coordinates import x_staggered_vector, x_vector
from pystencils.stencil import direction_string_to_offset, inverse_direction, offset_to_direction_string
-from pystencils.sympyextensions.typed_sympy import (FieldShapeSymbol, FieldStrideSymbol, StructType,
- TypedSymbol, BasicType, create_type)
+from pystencils.types import PsAbstractType, PsStructType, create_type
+from pystencils.sympyextensions.typed_sympy import (FieldShapeSymbol, FieldStrideSymbol, TypedSymbol)
from pystencils.sympyextensions.math import is_integer_sequence
@@ -315,12 +315,12 @@ class Field:
return self.strides[self.spatial_dimensions:]
@property
- def dtype(self):
+ def dtype(self) -> PsAbstractType:
return self._dtype
@property
def itemsize(self):
- return self.dtype.numpy_dtype.itemsize
+ return self.dtype.itemsize
def __repr__(self):
if any(isinstance(s, sp.Symbol) for s in self.spatial_shape):
@@ -592,7 +592,7 @@ class Field:
else:
idx_str = ",".join([str(e) for e in idx])
superscript = idx_str
- if field.has_fixed_index_shape and not isinstance(field.dtype, StructType):
+ if field.has_fixed_index_shape and not isinstance(field.dtype, PsStructType):
for i, bound in zip(idx, field.index_shape):
if i >= bound:
raise ValueError("Field index out of bounds")
@@ -604,7 +604,7 @@ class Field:
if superscript is not None:
symbol_name += "^" + superscript
- if dtype:
+ if dtype is not None:
obj = super(Field.Access, self).__xnew__(self, symbol_name, dtype)
else:
obj = super(Field.Access, self).__xnew__(self, symbol_name, field.dtype)
@@ -652,7 +652,9 @@ class Field:
if len(idx) != self.field.index_dimensions:
raise ValueError(f"Wrong number of indices: Got {len(idx)}, expected {self.field.index_dimensions}")
if len(idx) == 1 and isinstance(idx[0], str):
- dtype = BasicType(self.field.dtype.numpy_dtype[idx[0]])
+ struct_type = self.field.dtype
+ assert isinstance(struct_type, PsStructType)
+ dtype = struct_type.get_member(idx[0]).dtype
return Field.Access(self.field, self._offsets, idx,
is_absolute_access=self.is_absolute_access, dtype=dtype)
else:
diff --git a/src/pystencils/functions.py b/src/pystencils/functions.py
index 550a2724f1f3366d8fe3bb583f177d62a2616d22..df8d0ef6f611285d80a94ed08de8b72d41f2322f 100644
--- a/src/pystencils/functions.py
+++ b/src/pystencils/functions.py
@@ -1,5 +1,5 @@
import sympy as sp
-from .sympyextensions.typed_sympy import PointerType
+from .types import PsPointerType
class DivFunc(sp.Function):
@@ -52,6 +52,6 @@ class AddressOf(sp.Function):
@property
def dtype(self):
if hasattr(self.args[0], 'dtype'):
- return PointerType(self.args[0].dtype, restrict=True)
+ return PsPointerType(self.args[0].dtype, const=True, restrict=True)
else:
raise ValueError(f'pystencils supports only non void pointers. Current address_of type: {self.args[0]}')
diff --git a/src/pystencils/runhelper/db.py b/src/pystencils/runhelper/db.py
index 1c8d3aa66c0e47681b942dd06f0a1805e244e930..53d65b2ea16fb90a72ae1f418802404b45842767 100644
--- a/src/pystencils/runhelper/db.py
+++ b/src/pystencils/runhelper/db.py
@@ -14,7 +14,7 @@ from pystencils import CreateKernelConfig, Target, Backend, Field
import json
import sympy as sp
-from pystencils.typing import BasicType
+from pystencils.types import PsAbstractType
class PystencilsJsonEncoder(JsonEncoder):
@@ -26,7 +26,7 @@ class PystencilsJsonEncoder(JsonEncoder):
return float(obj)
if isinstance(obj, sp.Integer):
return int(obj)
- if isinstance(obj, (BasicType, MappingProxyType)):
+ if isinstance(obj, (PsAbstractType, MappingProxyType)):
return str(obj)
if isinstance(obj, (Target, Backend, sp.Symbol)):
return obj.name
diff --git a/src/pystencils/spatial_coordinates.py b/src/pystencils/spatial_coordinates.py
index cc244b11c2f633fe920abfa7ce654028a3fcc8e9..794bb713f7d7c4f79251a38b480a09b841408c89 100644
--- a/src/pystencils/spatial_coordinates.py
+++ b/src/pystencils/spatial_coordinates.py
@@ -1,14 +1,14 @@
import sympy
-from pystencils.sympyextensions.typed_sympy import get_loop_counter_symbol
+from .defaults import DEFAULTS
-x_, y_, z_ = tuple(get_loop_counter_symbol(i) for i in range(3))
+x_, y_, z_ = DEFAULTS.spatial_counters
x_staggered, y_staggered, z_staggered = x_ + 0.5, y_ + 0.5, z_ + 0.5
def x_vector(ndim):
- return sympy.Matrix(tuple(get_loop_counter_symbol(i) for i in range(ndim)))
+ return sympy.Matrix(DEFAULTS.spatial_counters)
def x_staggered_vector(ndim):
- return sympy.Matrix(tuple(get_loop_counter_symbol(i) + 0.5 for i in range(ndim)))
+ return sympy.Matrix(tuple(DEFAULTS.spatial_counters[i] + 0.5 for i in range(ndim)))
diff --git a/src/pystencils/sympyextensions/math.py b/src/pystencils/sympyextensions/math.py
index 00974809fe11c2de6e4b72d896821d1eacb8b443..3e7eeaabcc070eb28bce99a998051ad7963dad9d 100644
--- a/src/pystencils/sympyextensions/math.py
+++ b/src/pystencils/sympyextensions/math.py
@@ -12,7 +12,8 @@ from sympy.core.numbers import Zero
from .astnodes import Assignment
from pystencils.functions import DivFunc
-from .typed_sympy import CastFunc, PointerType, VectorType, FieldPointerSymbol
+from .typed_sympy import CastFunc, FieldPointerSymbol
+from ..types import PsPointerType, PsVectorType
T = TypeVar('T')
@@ -572,9 +573,9 @@ def count_operations(term: Union[sp.Expr, List[sp.Expr], List[Assignment]],
base_type = get_type_of_expression(e)
except ValueError:
return False
- if isinstance(base_type, VectorType):
+ if isinstance(base_type, PsVectorType):
return False
- if isinstance(base_type, PointerType):
+ if isinstance(base_type, PsPointerType):
return only_type == 'int'
if only_type == 'int' and (base_type.is_int() or base_type.is_uint()):
return True
diff --git a/src/pystencils/sympyextensions/typed_sympy.py b/src/pystencils/sympyextensions/typed_sympy.py
index 1f20624cedd46dde661c61fd7d26745fc58b7e09..c437afd92cec0925bf772495038228cac33932a1 100644
--- a/src/pystencils/sympyextensions/typed_sympy.py
+++ b/src/pystencils/sympyextensions/typed_sympy.py
@@ -1,429 +1,37 @@
-from abc import abstractmethod
-from itertools import groupby
-from typing import Sequence, Union
-
-import numpy as np
import sympy as sp
+from ..types import PsAbstractType, PsNumericType, PsPointerType, PsBoolType
+from ..types.quick import create_type
-class AbstractType(sp.Atom):
- # TODO: Is it necessary to ineherit from sp.Atom?
- def __new__(cls, *args, **kwargs):
- return sp.Basic.__new__(cls)
-
- def _sympystr(self, *args, **kwargs):
- return str(self)
-
- @property
- @abstractmethod
- def base_type(self) -> Union[None, 'BasicType']:
- """
- Returns: Returns BasicType of a Vector or Pointer type, None otherwise
- """
- pass
-
- @property
- @abstractmethod
- def item_size(self) -> int:
- """
- Returns: Number of items.
- E.g. width * item_size(basic_type) in vector's case, or simple numpy itemsize in Struct's case.
- """
- pass
-
-def is_supported_type(dtype: np.dtype):
- scalar = dtype.type
- c = np.issctype(dtype)
- subclass = issubclass(scalar, np.floating) or issubclass(scalar, np.integer) or issubclass(scalar, np.bool_)
- additional_checks = dtype.fields is None and dtype.hasobject is False and dtype.subdtype is None
- return c and subclass and additional_checks
-
-
-def numpy_name_to_c(name: str) -> str:
- """
- Converts a np.dtype.name into a C type
- Args:
- name: np.dtype.name string
- Returns:
- type as a C string
- """
- if name == 'float64':
- return 'double'
- elif name == 'float32':
- return 'float'
- elif name == 'float16' or name == 'half':
- return 'half'
- elif name.startswith('int'):
- width = int(name[len("int"):])
- return f"int{width}_t"
- elif name.startswith('uint'):
- width = int(name[len("uint"):])
- return f"uint{width}_t"
- elif name == 'bool':
- return 'bool'
- else:
- raise NotImplementedError(f"Can't map numpy to C name for {name}")
-
-
-def create_type(specification: Union[type, AbstractType, str]) -> AbstractType:
- # TODO: Deprecated Use the constructor of BasicType or StructType instead
- """Creates a subclass of Type according to a string or an object of subclass Type.
+def assumptions_from_dtype(dtype: PsAbstractType):
+ """Derives SymPy assumptions from :class:`PsAbstractType`
Args:
- specification: Type object, or a string
-
- Returns:
- Type object, or a new Type object parsed from the string
- """
- if isinstance(specification, AbstractType):
- return specification
- else:
- numpy_dtype = np.dtype(specification)
- if numpy_dtype.fields is None:
- return BasicType(numpy_dtype, const=False)
- else:
- return StructType(numpy_dtype, const=False)
-
-
-def get_base_type(data_type):
- """
- Returns the BasicType of a Pointer or a Vector
- """
- while data_type.base_type is not None:
- data_type = data_type.base_type
- return data_type
-
-
-class BasicType(AbstractType):
- """
- BasicType is defined with a const qualifier and a np.dtype.
- """
-
- def __init__(self, dtype: Union[type, 'BasicType', str], const: bool = False):
- if isinstance(dtype, BasicType):
- self.numpy_dtype = dtype.numpy_dtype
- self.const = dtype.const
- else:
- self.numpy_dtype = np.dtype(dtype)
- self.const = const
- assert is_supported_type(self.numpy_dtype), f'Type {self.numpy_dtype} is currently not supported!'
-
- def __getnewargs__(self):
- return self.numpy_dtype, self.const
-
- def __getnewargs_ex__(self):
- return (self.numpy_dtype, self.const), {}
-
- @property
- def base_type(self):
- return None
-
- @property
- def item_size(self): # TODO: Do we want self.numpy_type.itemsize????
- return 1
-
- def is_float(self):
- return issubclass(self.numpy_dtype.type, np.floating)
-
- def is_half(self):
- return issubclass(self.numpy_dtype.type, np.half)
-
- def is_int(self):
- return issubclass(self.numpy_dtype.type, np.integer)
-
- def is_uint(self):
- return issubclass(self.numpy_dtype.type, np.unsignedinteger)
-
- def is_sint(self):
- return issubclass(self.numpy_dtype.type, np.signedinteger)
-
- def is_bool(self):
- return issubclass(self.numpy_dtype.type, np.bool_)
-
- def dtype_eq(self, other):
- if not isinstance(other, BasicType):
- return False
- else:
- return self.numpy_dtype == other.numpy_dtype
-
- @property
- def c_name(self) -> str:
- return numpy_name_to_c(self.numpy_dtype.name)
-
- def __str__(self):
- return f'{self.c_name}{" const" if self.const else ""}'
-
- def __repr__(self):
- return f'BasicType( {str(self)} )'
-
- def _repr_html_(self):
- return f'BasicType( {str(self)} )'
-
- def __eq__(self, other):
- return self.dtype_eq(other) and self.const == other.const
-
- def __hash__(self):
- return hash(str(self))
-
-
-class VectorType(AbstractType):
- """
- VectorType consists of a BasicType and a width.
- """
- instruction_set = None
-
- def __init__(self, base_type: BasicType, width: int):
- self._base_type = base_type
- self.width = width
-
- @property
- def base_type(self):
- return self._base_type
-
- @property
- def item_size(self):
- return self.width * self.base_type.item_size
-
- def __eq__(self, other):
- if not isinstance(other, VectorType):
- return False
- else:
- return (self.base_type, self.width) == (other.base_type, other.width)
-
- def __str__(self):
- if self.instruction_set is None:
- return f"{self.base_type}[{self.width}]"
- else:
- # TODO VectorizationRevamp: this seems super weird. the instruction_set should know how to print a type out!
- # TODO VectorizationRevamp: this is error prone. base_type could be cons=True. Use dtype instead
- if self.base_type == create_type("int64") or self.base_type == create_type("int32"):
- return self.instruction_set['int']
- elif self.base_type == create_type("float64"):
- return self.instruction_set['double']
- elif self.base_type == create_type("float32"):
- return self.instruction_set['float']
- elif self.base_type == create_type("bool"):
- return self.instruction_set['bool']
- else:
- raise NotImplementedError()
-
- def __hash__(self):
- return hash((self.base_type, self.width))
-
- def __getnewargs__(self):
- return self._base_type, self.width
-
- def __getnewargs_ex__(self):
- return (self._base_type, self.width), {}
-
-
-class PointerType(AbstractType):
- def __init__(self, base_type: BasicType, const: bool = False, restrict: bool = True, double_pointer: bool = False):
- self._base_type = base_type
- self.const = const
- self.restrict = restrict
- self.double_pointer = double_pointer
-
- def __getnewargs__(self):
- return self.base_type, self.const, self.restrict, self.double_pointer
-
- def __getnewargs_ex__(self):
- return (self.base_type, self.const, self.restrict, self.double_pointer), {}
-
- @property
- def alias(self):
- return not self.restrict
-
- @property
- def base_type(self):
- return self._base_type
-
- @property
- def item_size(self):
- if self.double_pointer:
- raise NotImplementedError("The item_size for double_pointer is not implemented")
- else:
- return self.base_type.item_size
-
- def __eq__(self, other):
- if not isinstance(other, PointerType):
- return False
- else:
- own = (self.base_type, self.const, self.restrict, self.double_pointer)
- return own == (other.base_type, other.const, other.restrict, other.double_pointer)
-
- def __str__(self):
- restrict_str = "RESTRICT" if self.restrict else ""
- const_str = "const" if self.const else ""
- if self.double_pointer:
- return f'{str(self.base_type)} ** {restrict_str} {const_str}'
- else:
- return f'{str(self.base_type)} * {restrict_str} {const_str}'
-
- def __repr__(self):
- return str(self)
-
- def _repr_html_(self):
- return str(self)
-
- def __hash__(self):
- return hash((self._base_type, self.const, self.restrict, self.double_pointer))
-
-
-class StructType(AbstractType):
- """
- A list of types (with C offsets).
- It is implemented with uint8_t and casts to the correct datatype.
- """
- def __init__(self, numpy_type, const=False):
- self.const = const
- self._dtype = np.dtype(numpy_type)
-
- def __getnewargs__(self):
- return self.numpy_dtype, self.const
-
- def __getnewargs_ex__(self):
- return (self.numpy_dtype, self.const), {}
-
- @property
- def base_type(self):
- return None
-
- @property
- def numpy_dtype(self):
- return self._dtype
-
- @property
- def item_size(self):
- return self.numpy_dtype.itemsize
-
- def get_element_offset(self, element_name):
- return self.numpy_dtype.fields[element_name][1]
-
- def get_element_type(self, element_name):
- np_element_type = self.numpy_dtype.fields[element_name][0]
- return BasicType(np_element_type, self.const)
-
- def has_element(self, element_name):
- return element_name in self.numpy_dtype.fields
-
- def __eq__(self, other):
- if not isinstance(other, StructType):
- return False
- else:
- return (self.numpy_dtype, self.const) == (other.numpy_dtype, other.const)
-
- def __str__(self):
- # structs are handled byte-wise
- result = "uint8_t"
- if self.const:
- result += " const"
- return result
-
- def __repr__(self):
- return str(self)
-
- def _repr_html_(self):
- return str(self)
-
- def __hash__(self):
- return hash((self.numpy_dtype, self.const))
-
-
-def result_type(*args: np.dtype):
- """Returns the type of the result if the np.dtype arguments would be collated.
- We can't use numpy functionality, because numpy casts don't behave exactly like C casts"""
- s = sorted(args, key=lambda x: x.itemsize)
-
- def kind_to_value(kind: str) -> int:
- if kind == 'f':
- return 3
- elif kind == 'i':
- return 2
- elif kind == 'u':
- return 1
- elif kind == 'b':
- return 0
- else:
- raise NotImplementedError(f'{kind=} is not a supported kind of a type. See "numpy.dtype.kind" for options')
- s = sorted(s, key=lambda x: kind_to_value(x.kind))
- return s[-1]
-
-
-def all_equal(iterable):
- """
- Returns ``True`` if all the elements are equal to each other.
- Copied from: more-itertools 8.12.0
- """
- g = groupby(iterable)
- return next(g, True) and not next(g, False)
-
-
-def collate_types(types: Sequence[Union[BasicType, VectorType]]):
- """
- Takes a sequence of types and returns their "common type" e.g. (float, double, float) -> double
- Uses the collation rules from numpy.
- """
- # Pointer arithmetic case i.e. pointer + [int, uint] is allowed
- if any(isinstance(t, PointerType) for t in types):
- pointer_type = None
- for t in types:
- if isinstance(t, PointerType):
- if pointer_type is not None:
- raise ValueError(f'Cannot collate the combination of two pointer types "{pointer_type}" and "{t}"')
- pointer_type = t
- elif isinstance(t, BasicType):
- if not (t.is_int() or t.is_uint()):
- raise ValueError("Invalid pointer arithmetic")
- else:
- raise ValueError("Invalid pointer arithmetic")
- return pointer_type
-
- # # peel of vector types, if at least one vector type occurred the result will also be the vector type
- vector_type = [t for t in types if isinstance(t, VectorType)]
- if not all_equal(t.width for t in vector_type):
- raise ValueError("Collation failed because of vector types with different width")
-
- types = [t.base_type if isinstance(t, VectorType) else t for t in types]
-
- # now we should have a list of basic types - struct types are not yet supported
- assert all(type(t) is BasicType for t in types)
-
- result_numpy_type = result_type(*(t.numpy_dtype for t in types))
- result = BasicType(result_numpy_type)
- if vector_type:
- result = VectorType(result, vector_type[0].width)
- return result
-
-
-def assumptions_from_dtype(dtype: Union[BasicType, np.dtype]):
- """Derives SymPy assumptions from :class:`BasicType` or a Numpy dtype
-
- Args:
- dtype (BasicType, np.dtype): a Numpy data type
+ dtype (PsAbstractType): a pystencils data type
Returns:
A dict of SymPy assumptions
"""
- if hasattr(dtype, 'numpy_dtype'):
- dtype = dtype.numpy_dtype
-
assumptions = dict()
- try:
- if np.issubdtype(dtype, np.integer):
- assumptions.update({'integer': True})
+ if isinstance(dtype, PsNumericType):
+ if dtype.is_int:
+ assumptions.update({"integer": True})
+ if dtype.is_uint:
+ assumptions.update({"negative": False})
+ if dtype.is_int or dtype.is_float:
+ assumptions.update({"real": True})
- if np.issubdtype(dtype, np.unsignedinteger):
- assumptions.update({'negative': False})
+ return assumptions
- if np.issubdtype(dtype, np.integer) or \
- np.issubdtype(dtype, np.floating):
- assumptions.update({'real': True})
- except Exception: # TODO this is dirty
- pass
- return assumptions
+def is_loop_counter_symbol(symbol):
+ from ..defaults import DEFAULTS
+
+ try:
+ return DEFAULTS.spatial_counters.index(symbol)
+ except ValueError:
+ return None
class TypedSymbol(sp.Symbol):
@@ -431,27 +39,30 @@ class TypedSymbol(sp.Symbol):
obj = TypedSymbol.__xnew_cached_(cls, *args, **kwds)
return obj
- def __new_stage2__(cls, name, dtype, **kwargs): # TODO does not match signature of sp.Symbol???
+ def __new_stage2__(
+ cls, name, dtype, **kwargs
+ ): # TODO does not match signature of sp.Symbol???
# TODO: also Symbol should be allowed ---> see sympy Variable
+ dtype = create_type(dtype)
assumptions = assumptions_from_dtype(dtype)
assumptions.update(kwargs)
+
obj = super(TypedSymbol, cls).__xnew__(cls, name, **assumptions)
- try:
- obj.numpy_dtype = create_type(dtype)
- except (TypeError, ValueError):
- # on error keep the string
- obj.numpy_dtype = dtype
+ obj._dtype = create_type(dtype)
+
return obj
__xnew__ = staticmethod(__new_stage2__)
__xnew_cached_ = staticmethod(sp.core.cacheit(__new_stage2__))
@property
- def dtype(self):
- return self.numpy_dtype
+ def dtype(self) -> PsAbstractType:
+ # mypy: ignore
+ return self._dtype
def _hashable_content(self):
- return super()._hashable_content(), hash(self.numpy_dtype)
+ # mypy: ignore
+ return super()._hashable_content(), hash(self._dtype)
def __getnewargs__(self):
return self.name, self.dtype
@@ -468,38 +79,24 @@ class TypedSymbol(sp.Symbol):
return self
@property
- def headers(self):
- headers = []
- try:
- if np.issubdtype(self.dtype.numpy_dtype, np.complexfloating):
- headers.append('"cuda_complex.hpp"')
- except Exception:
- pass
- try:
- if np.issubdtype(self.dtype.base_type.numpy_dtype, np.complexfloating):
- headers.append('"cuda_complex.hpp"')
- except Exception:
- pass
-
- return headers
-
-
-SHAPE_DTYPE = BasicType('int64', const=True)
-STRIDE_DTYPE = BasicType('int64', const=True)
-LOOP_COUNTER_DTYPE = BasicType('int64', const=True)
-LOOP_COUNTER_NAME_PREFIX = "ctr"
-BLOCK_LOOP_COUNTER_NAME_PREFIX = "_blockctr"
+ def headers(self) -> set[str]:
+ return self.dtype.required_headers
class FieldStrideSymbol(TypedSymbol):
"""Sympy symbol representing the stride value of a field in a specific coordinate."""
+
def __new__(cls, *args, **kwds):
obj = FieldStrideSymbol.__xnew_cached_(cls, *args, **kwds)
return obj
def __new_stage2__(cls, field_name, coordinate):
+ from ..defaults import DEFAULTS
+
name = f"_stride_{field_name}_{coordinate}"
- obj = super(FieldStrideSymbol, cls).__xnew__(cls, name, STRIDE_DTYPE, positive=True)
+ obj = super(FieldStrideSymbol, cls).__xnew__(
+ cls, name, DEFAULTS.index_dtype, positive=True
+ )
obj.field_name = field_name
obj.coordinate = coordinate
return obj
@@ -519,15 +116,21 @@ class FieldStrideSymbol(TypedSymbol):
class FieldShapeSymbol(TypedSymbol):
"""Sympy symbol representing the shape value of a sequence of fields. In a kernel iterating over multiple fields
- there is only one set of `FieldShapeSymbol`s since all the fields have to be of equal size."""
+ there is only one set of `FieldShapeSymbol`s since all the fields have to be of equal size.
+ """
+
def __new__(cls, *args, **kwds):
obj = FieldShapeSymbol.__xnew_cached_(cls, *args, **kwds)
return obj
def __new_stage2__(cls, field_names, coordinate):
+ from ..defaults import DEFAULTS
+
names = "_".join([field_name for field_name in field_names])
name = f"_size_{names}_{coordinate}"
- obj = super(FieldShapeSymbol, cls).__xnew__(cls, name, SHAPE_DTYPE, positive=True)
+ obj = super(FieldShapeSymbol, cls).__xnew__(
+ cls, name, DEFAULTS.index_dtype, positive=True
+ )
obj.field_names = tuple(field_names)
obj.coordinate = coordinate
return obj
@@ -547,13 +150,14 @@ class FieldShapeSymbol(TypedSymbol):
class FieldPointerSymbol(TypedSymbol):
"""Sympy symbol representing the pointer to the beginning of the field data."""
+
def __new__(cls, *args, **kwds):
obj = FieldPointerSymbol.__xnew_cached_(cls, *args, **kwds)
return obj
- def __new_stage2__(cls, field_name, field_dtype, const):
+ def __new_stage2__(cls, field_name, field_dtype: PsAbstractType, const: bool):
name = f"_data_{field_name}"
- dtype = PointerType(get_base_type(field_dtype), const=const, restrict=True)
+ dtype = PsPointerType(field_dtype, const=const, restrict=True)
obj = super(FieldPointerSymbol, cls).__xnew__(cls, name, dtype)
obj.field_name = field_name
return obj
@@ -571,30 +175,12 @@ class FieldPointerSymbol(TypedSymbol):
__xnew_cached_ = staticmethod(sp.core.cacheit(__new_stage2__))
-def get_loop_counter_symbol(coordinate_to_loop_over):
- return TypedSymbol(f"{LOOP_COUNTER_NAME_PREFIX}_{coordinate_to_loop_over}",
- LOOP_COUNTER_DTYPE, nonnegative=True)
-
-
-def get_block_loop_counter_symbol(coordinate_to_loop_over):
- return TypedSymbol(f"{BLOCK_LOOP_COUNTER_NAME_PREFIX}_{coordinate_to_loop_over}",
- LOOP_COUNTER_DTYPE, nonnegative=True)
-
-
-def is_loop_counter_symbol(symbol):
- if not symbol.name.startswith(LOOP_COUNTER_NAME_PREFIX):
- return None
- if symbol.dtype != LOOP_COUNTER_DTYPE:
- return None
- coordinate = int(symbol.name[len(LOOP_COUNTER_NAME_PREFIX) + 1:])
- return coordinate
-
-
class CastFunc(sp.Function):
"""
CastFunc is used in order to introduce static casts. They are especially useful as a way to signal what type
a certain node should have, if it is impossible to add a type to a node, e.g. a sp.Number.
"""
+
is_Atom = True
def __new__(cls, *args, **kwargs):
@@ -606,8 +192,7 @@ class CastFunc(sp.Function):
# This optimisation is only available for simple casts. Thus the == is intended here!
if expr.__class__ == CastFunc:
expr = expr.args[0]
- if not isinstance(dtype, AbstractType):
- dtype = BasicType(dtype)
+ dtype = create_type(dtype)
# to work in conditions of sp.Piecewise cast_func has to be of type Boolean as well
# however, a cast_function should only be a boolean if its argument is a boolean, otherwise this leads
# to problems when for example comparing cast_func's for equality
@@ -616,15 +201,16 @@ class CastFunc(sp.Function):
# rhs = cast_func(0, 'int')
# print( sp.Ne(lhs, rhs) ) # would give true if all cast_funcs are booleans
# -> thus a separate class boolean_cast_func is introduced
- if (isinstance(expr, sp.logic.boolalg.Boolean) and
- (not isinstance(expr, TypedSymbol) or expr.dtype == BasicType('bool'))):
+ if isinstance(expr, sp.logic.boolalg.Boolean) and (
+ not isinstance(expr, TypedSymbol) or isinstance(expr.dtype, PsBoolType)
+ ):
cls = BooleanCastFunc
return sp.Function.__new__(cls, expr, dtype, *other_args, **kwargs)
@property
def canonical(self):
- if hasattr(self.args[0], 'canonical'):
+ if hasattr(self.args[0], "canonical"):
return self.args[0].canonical
else:
raise NotImplementedError()
@@ -643,13 +229,8 @@ class CastFunc(sp.Function):
@property
def is_integer(self):
- """
- Uses Numpy type hierarchy to determine :func:`sympy.Expr.is_integer` predicate
-
- For reference: Numpy type hierarchy https://docs.scipy.org/doc/numpy-1.13.0/reference/arrays.scalars.html
- """
- if hasattr(self.dtype, 'numpy_dtype'):
- return np.issubdtype(self.dtype.numpy_dtype, np.integer) or super().is_integer
+ if isinstance(self.dtype, PsNumericType):
+ return self.dtype.is_int() or super().is_integer
else:
return super().is_integer
@@ -658,8 +239,8 @@ class CastFunc(sp.Function):
"""
See :func:`.TypedSymbol.is_integer`
"""
- if hasattr(self.dtype, 'numpy_dtype'):
- if np.issubdtype(self.dtype.numpy_dtype, np.unsignedinteger):
+ if isinstance(self.dtype, PsNumericType):
+ if self.dtype.is_uint():
return False
return super().is_negative
@@ -679,9 +260,8 @@ class CastFunc(sp.Function):
"""
See :func:`.TypedSymbol.is_integer`
"""
- if hasattr(self.dtype, 'numpy_dtype'):
- return np.issubdtype(self.dtype.numpy_dtype, np.integer) or np.issubdtype(self.dtype.numpy_dtype,
- np.floating) or super().is_real
+ if isinstance(self.dtype, PsNumericType):
+ return self.dtype.is_int() or self.dtype.is_float() or super().is_real
else:
return super().is_real
@@ -696,6 +276,7 @@ class VectorMemoryAccess(CastFunc):
Special memory access for vectorized kernel.
Arguments: read/write expression, type, aligned, non-temporal, mask (or none), stride
"""
+
nargs = (6,)
@@ -703,6 +284,7 @@ class ReinterpretCastFunc(CastFunc):
"""
Reinterpret cast is necessary for the StructType
"""
+
pass
@@ -710,10 +292,7 @@ class PointerArithmeticFunc(sp.Function, sp.logic.boolalg.Boolean):
# TODO: documentation, or deprecate!
@property
def canonical(self):
- if hasattr(self.args[0], 'canonical'):
+ if hasattr(self.args[0], "canonical"):
return self.args[0].canonical
else:
raise NotImplementedError()
-
-
-
diff --git a/src/pystencils/types/__init__.py b/src/pystencils/types/__init__.py
index 4aee28086fe043f6e6dd5c8ee80caf86958d3811..f33d8a1f7eb51b1e230c20f55d3d61c36da3de42 100644
--- a/src/pystencils/types/__init__.py
+++ b/src/pystencils/types/__init__.py
@@ -6,6 +6,7 @@ from .basic_types import (
PsScalarType,
PsVectorType,
PsPointerType,
+ PsBoolType,
PsIntegerType,
PsUnsignedIntegerType,
PsSignedIntegerType,
@@ -14,7 +15,7 @@ from .basic_types import (
deconstify,
)
-from .quick import make_type, make_numeric_type
+from .quick import create_type, create_numeric_type
from .exception import PsTypeError
@@ -27,12 +28,13 @@ __all__ = [
"PsScalarType",
"PsVectorType",
"PsIntegerType",
+ "PsBoolType",
"PsUnsignedIntegerType",
"PsSignedIntegerType",
"PsIeeeFloatType",
"constify",
"deconstify",
- "make_type",
- "make_numeric_type",
+ "create_type",
+ "create_numeric_type",
"PsTypeError",
]
diff --git a/src/pystencils/types/basic_types.py b/src/pystencils/types/basic_types.py
index 947895e2cccaad34592984e189f32efb13346a51..749a4d34ccc30ad66049ae2d52d7ff896ab5f626 100644
--- a/src/pystencils/types/basic_types.py
+++ b/src/pystencils/types/basic_types.py
@@ -187,12 +187,18 @@ class PsStructType(PsAbstractType):
def members(self) -> tuple[PsStructType.Member, ...]:
return self._members
- def get_member(self, member_name: str) -> PsStructType.Member | None:
+ def find_member(self, member_name: str) -> PsStructType.Member | None:
"""Find a member by name"""
for m in self._members:
if m.name == member_name:
return m
return None
+
+ def get_member(self, member_name: str) -> PsStructType.Member:
+ m = self.find_member(member_name)
+ if m is None:
+ raise KeyError(f"No struct member with name {member_name}")
+ return m
@property
def name(self) -> str:
@@ -289,6 +295,10 @@ class PsNumericType(PsAbstractType, ABC):
def is_float(self) -> bool:
pass
+ @abstractmethod
+ def is_bool(self) -> bool:
+ pass
+
class PsScalarType(PsNumericType, ABC):
"""Class to model scalar numeric types."""
@@ -317,6 +327,9 @@ class PsScalarType(PsNumericType, ABC):
def is_float(self) -> bool:
return isinstance(self, PsIeeeFloatType)
+
+ def is_bool(self) -> bool:
+ return isinstance(self, PsBoolType)
class PsVectorType(PsNumericType):
@@ -357,6 +370,9 @@ class PsVectorType(PsNumericType):
def is_float(self) -> bool:
return self._scalar_type.is_float()
+
+ def is_bool(self) -> bool:
+ return self._scalar_type.is_bool()
@property
def itemsize(self) -> int | None:
@@ -412,6 +428,43 @@ class PsVectorType(PsNumericType):
)
+class PsBoolType(PsScalarType):
+ """Class to model the boolean type."""
+
+ NUMPY_TYPE = np.bool_
+
+ def __init__(self, const: bool = False):
+ super().__init__(const)
+
+ @property
+ def width(self) -> int:
+ return 8
+
+ @property
+ def itemsize(self) -> int:
+ return self.width // 8
+
+ @property
+ def numpy_dtype(self) -> np.dtype | None:
+ return np.dtype(PsBoolType.NUMPY_TYPE)
+
+ def create_literal(self, value: Any) -> str:
+ if value in (1, True, np.True_):
+ return "true"
+ elif value in (0, False, np.False_):
+ return "false"
+ else:
+ raise PsTypeError(f"Cannot create boolean literal from {value}")
+
+ def create_constant(self, value: Any) -> Any:
+ if value in (1, True, np.True_):
+ return np.True_
+ elif value in (0, False, np.False_):
+ return np.False_
+ else:
+ raise PsTypeError(f"Cannot create boolean constant from value {value}")
+
+
class PsIntegerType(PsScalarType, ABC):
"""Class to model signed and unsigned integer types.
diff --git a/src/pystencils/types/quick.py b/src/pystencils/types/quick.py
index 65683c80abe25185282b8cc1f7949a110a469047..0268e9a791f50581ead5b0c2a3b3e64619d4165c 100644
--- a/src/pystencils/types/quick.py
+++ b/src/pystencils/types/quick.py
@@ -13,6 +13,7 @@ from .basic_types import (
PsCustomType,
PsNumericType,
PsScalarType,
+ PsBoolType,
PsPointerType,
PsIntegerType,
PsUnsignedIntegerType,
@@ -23,7 +24,7 @@ from .basic_types import (
UserTypeSpec = str | type | np.dtype | PsAbstractType
-def make_type(type_spec: UserTypeSpec) -> PsAbstractType:
+def create_type(type_spec: UserTypeSpec) -> PsAbstractType:
"""Create a pystencils type object from a variety of specifications.
Possible arguments are:
@@ -53,9 +54,9 @@ def make_type(type_spec: UserTypeSpec) -> PsAbstractType:
raise ValueError(f"{type_spec} is not a valid type specification.")
-def make_numeric_type(type_spec: UserTypeSpec) -> PsNumericType:
+def create_numeric_type(type_spec: UserTypeSpec) -> PsNumericType:
"""Like `make_type`, but only for numeric types."""
- dtype = make_type(type_spec)
+ dtype = create_type(type_spec)
if not isinstance(dtype, PsNumericType):
raise ValueError(
f"Given type {type_spec} does not translate to a numeric type."
@@ -72,6 +73,9 @@ Scalar = PsScalarType
Ptr = PsPointerType
"""`Ptr(t)` matches `PsPointerType(base_type=t)`"""
+Bool = PsBoolType
+"""Bool() matches PsBoolType()"""
+
AnyInt = PsIntegerType
"""`AnyInt(width)` matches both `PsUnsignedIntegerType(width)` and `PsSignedIntegerType(width)`"""
diff --git a/tests/nbackend/kernelcreation/test_typification.py b/tests/nbackend/kernelcreation/test_typification.py
index 9f49b2ed08dcc87b0071e9539caf1ead5c4725b4..7625e22e3ce25b2467110d91dd951c775e9dbdb2 100644
--- a/tests/nbackend/kernelcreation/test_typification.py
+++ b/tests/nbackend/kernelcreation/test_typification.py
@@ -7,7 +7,7 @@ from pystencils import Assignment, TypedSymbol, Field, FieldType
from pystencils.backend.ast.structural import PsDeclaration
from pystencils.backend.ast.expressions import PsConstantExpr, PsSymbolExpr, PsBinOp
from pystencils.types import constify
-from pystencils.types.quick import Fp, make_numeric_type
+from pystencils.types.quick import Fp, create_numeric_type
from pystencils.backend.kernelcreation.context import KernelCreationContext
from pystencils.backend.kernelcreation.freeze import FreezeExpressions
from pystencils.backend.kernelcreation.typification import Typifier, TypificationError
@@ -92,7 +92,7 @@ def test_contextual_typing():
def test_erronous_typing():
- ctx = KernelCreationContext(default_dtype=make_numeric_type(np.float64))
+ ctx = KernelCreationContext(default_dtype=create_numeric_type(np.float64))
freeze = FreezeExpressions(ctx)
typify = Typifier(ctx)
diff --git a/tests/nbackend/types/test_types.py b/tests/nbackend/types/test_types.py
index 5f11cd0815f8865172036b381b3b1e87d16275eb..487f777835ee347507504b4b6ed765f912fdd639 100644
--- a/tests/nbackend/types/test_types.py
+++ b/tests/nbackend/types/test_types.py
@@ -19,12 +19,12 @@ def test_widths(Type):
def test_parsing_positive():
- assert make_type("const uint32_t * restrict") == Ptr(
+ assert create_type("const uint32_t * restrict") == Ptr(
UInt(32, const=True), restrict=True
)
- assert make_type("float * * const") == Ptr(Ptr(Fp(32)), const=True)
- assert make_type("uint16 * const") == Ptr(UInt(16), const=True)
- assert make_type("uint64 const * const") == Ptr(UInt(64, const=True), const=True)
+ assert create_type("float * * const") == Ptr(Ptr(Fp(32)), const=True)
+ assert create_type("uint16 * const") == Ptr(UInt(16), const=True)
+ assert create_type("uint64 const * const") == Ptr(UInt(64, const=True), const=True)
def test_parsing_negative():
@@ -40,20 +40,20 @@ def test_parsing_negative():
for spec in bad_specs:
with pytest.raises(ValueError):
- make_type(spec)
+ create_type(spec)
def test_numpy():
import numpy as np
- assert make_type(np.single) == make_type(np.float32) == PsIeeeFloatType(32)
+ assert create_type(np.single) == create_type(np.float32) == PsIeeeFloatType(32)
assert (
- make_type(float)
- == make_type(np.double)
- == make_type(np.float64)
+ create_type(float)
+ == create_type(np.double)
+ == create_type(np.float64)
== PsIeeeFloatType(64)
)
- assert make_type(int) == make_type(np.int64) == PsSignedIntegerType(64)
+ assert create_type(int) == create_type(np.int64) == PsSignedIntegerType(64)
@pytest.mark.parametrize(
@@ -74,7 +74,7 @@ def test_numpy():
)
def test_numpy_translation(numpy_type):
dtype_obj = np.dtype(numpy_type)
- ps_type = make_type(numpy_type)
+ ps_type = create_type(numpy_type)
assert isinstance(ps_type, PsNumericType)
assert ps_type.numpy_dtype == dtype_obj