def fromobject(tuple, type):
head, tail = type.parameters
hd = fromobject(tuple[0], head)
if tuple[1:]:
tl = fromobject(tuple[1:], tail)
else:
tl = EmptyTuple()
return StaticTuple(hd, tl)
def fromobject(tuple, type):
head, tail = type.parameters
hd = fromobject(tuple[0], head)
if tuple[1:]:
tl = fromobject(tuple[1:], tail)
else:
tl = EmptyTuple()
return StaticTuple(hd, tl)
def fromnumpy(ndarray, ty, boundscheck=False):
"""Build an NDArray from a numpy ndarray"""
# Compute steps
itemsize = ndarray.dtype.itemsize
steps = tuple(stride // itemsize for stride in ndarray.strides)
# Check that strides are divisible by itemsize. We need to do this to
# allow computation on Pointer[T] instead of Pointer[char], which we
# need since we cannot access 'T' in __getitem__ to cast the Pointer[char]
# back to Pointer[T]
if any(stride % itemsize for stride in ndarray.strides):
raise ValueError("Cannot handle non-element size strides "
"(e.g. views in record arrays)")
# Build array object
data = fromobject(ndarray.ctypes.data, Pointer[flypy.types.int8])
dims = EmptyDim()
for extent, stride in reversed(zip(ndarray.shape, steps)):
dimcls = Dimension
#dimcls = DimensionContig if stride == 1 else Dimension
dims = dimcls(dims, extent, stride)
if boundscheck:
dims = BoundsCheck(dims)
base_type = ty.parameters[0]
return NDArray(data, dims, base_type)
def fromnumpy(ndarray, ty, keepalive, boundscheck=False):
"""Build an NDArray from a numpy ndarray"""
# Compute steps
itemsize = ndarray.dtype.itemsize
steps = tuple(stride // itemsize for stride in ndarray.strides)
# Check that strides are divisible by itemsize. We need to do this to
# allow computation on Pointer[T] instead of Pointer[char], which we
# need since we cannot access 'T' in __getitem__ to cast the Pointer[char]
# back to Pointer[T]
if any(stride % itemsize for stride in ndarray.strides):
raise ValueError("Cannot handle non-element size strides "
"(e.g. views in record arrays)")
# Build array object
data = fromobject(ndarray.ctypes.data, Pointer[flypy.types.int8], keepalive)
dims = EmptyDim()
for extent, stride in reversed(zip(ndarray.shape, steps)):
dimcls = Dimension
#dimcls = DimensionContig if stride == 1 else Dimension
dims = dimcls(dims, extent, stride)
if boundscheck:
dims = BoundsCheck(dims)
base_type = ty.parameters[0]
return NDArray(data, dims, base_type)
def test_representation(self):
"ctypes"
ty = typeof((1, 2, 3))
obj = fromobject((1, 2, 3), ty)
keepalive = []
rep = toctypes(obj, ty, keepalive)
rep = CTypesStruct(rep)
# print(rep) -> { tl:{ tl:{ tl:{ dummy:0 }, hd:3 }, hd:2 }, hd:1 }
self.assertEqual(rep.hd, 1)
self.assertEqual(rep.tl.hd, 2)
self.assertEqual(rep.tl.tl.hd, 3)
def test_representation(self):
"ctypes"
ty = typeof((1, 2, 3))
obj = fromobject((1, 2, 3), ty)
keepalive = []
rep = toctypes(obj, ty, keepalive)
rep = CTypesStruct(rep)
# print(rep) -> { tl:{ tl:{ tl:{ dummy:0 }, hd:3 }, hd:2 }, hd:1 }
self.assertEqual(rep.hd, 1)
self.assertEqual(rep.tl.hd, 2)
self.assertEqual(rep.tl.tl.hd, 3)
def make_applier(f, *subterms):
"""Create a blaze function application term"""
@jit('Apply[subterms]')
class Apply(object):
"""Function application term"""
layout = [('subterms', 'subterms')] # Tuple of sub-expressions
@jit
def apply(self, args):
args = eval_subterms(self.subterms, args)
return f(*args)
def __repr__(self):
return "Apply(%s, %s)" % (f.py_func.__name__, self.subterms)
# NOTE: flypy doesn't reconstruct flypy objects recursively, it only
# acts on roots!
subterms = fromobject(subterms, typeof(subterms))
return Apply(subterms)
def make_applier(f, *subterms):
"""Create a blaze function application term"""
@jit('Apply[subterms]')
class Apply(object):
"""Function application term"""
layout = [('subterms', 'subterms')] # Tuple of sub-expressions
@jit
def apply(self, args):
args = eval_subterms(self.subterms, args)
return f(*args)
def __repr__(self):
return "Apply(%s, %s)" % (f.py_func.__name__, self.subterms)
# NOTE: flypy doesn't reconstruct flypy objects recursively, it only
# acts on roots!
subterms = fromobject(subterms, typeof(subterms))
return Apply(subterms)
def interpret(nb_func, run_phase, args, debug=False, tracer=None):
"""Interpret and return result"""
# Translate flypy function
argtypes = [typeof(arg) for arg in args]
env = environment.fresh_env(nb_func, argtypes, target="cpu")
f, env = run_phase(nb_func, env)
if debug:
header(f)
if tracer is None:
# Set up tracer to trace interpretation
if debug:
tracer = tracing.Tracer()
else:
tracer = tracing.DummyTracer()
newargs = [conversion.fromobject(arg, typeof(arg)) for arg in args]
# Interpret function
env.setdefault('interp.handlers', handlers(run_phase, env))
return interp.run(f, env, args=newargs, tracer=tracer)
def interpret(nb_func, run_phase, args, debug=False, tracer=None):
"""Interpret and return result"""
# Translate flypy function
argtypes = [typeof(arg) for arg in args]
env = environment.fresh_env(nb_func, argtypes, target="cpu")
f, env = run_phase(nb_func, env)
if debug:
header(f)
if tracer is None:
# Set up tracer to trace interpretation
if debug:
tracer = tracing.Tracer()
else:
tracer = tracing.DummyTracer()
newargs = [conversion.fromobject(arg, typeof(arg)) for arg in args]
# Interpret function
env.setdefault('interp.handlers', handlers(run_phase, env))
return interp.run(f, env, args=newargs, tracer=tracer)
def rewrite_constants(func, env):
"""
Rewrite constants with user-defined types to IR constants. Also rewrite
constants of builtins to instances of flypy classes.
e.g. constant(None) -> constant(NoneValue)
constant("foo") -> constant(Bytes("foo"))
"""
if env['flypy.state.opaque']:
return
context = env['flypy.typing.context']
for op in func.ops:
if op.opcode == 'exc_catch':
continue
constants = collect_constants(op)
new_constants = []
for c in constants:
ty = context[c]
# Python -> flypy (if not already)
flypy_obj = fromobject(c.const, ty)
# flypy -> ctypes
ctype_obj = toctypes(flypy_obj, ty, _keep_alive)
if byref(ty):
ctype_obj = ctypes.pointer(ctype_obj)
# ctypes -> pykit
new_const = from_ctypes_value(ctype_obj)
context[new_const] = ty
new_constants.append(new_const)
_keep_alive.extend([ctype_obj, c.const])
substitute_args(op, constants, new_constants)
def rewrite_constants(func, env):
"""
Rewrite constants with user-defined types to IR constants. Also rewrite
constants of builtins to instances of flypy classes.
e.g. constant(None) -> constant(NoneValue)
constant("foo") -> constant(Bytes("foo"))
"""
if env['flypy.state.opaque']:
return
context = env['flypy.typing.context']
for op in func.ops:
if op.opcode == 'exc_catch':
continue
constants = collect_constants(op)
new_constants = []
for c in constants:
ty = context[c]
# Python -> flypy (if not already)
flypy_obj = fromobject(c.const, ty, _keep_alive)
# flypy -> ctypes
ctype_obj = toctypes(flypy_obj, ty, _keep_alive)
if byref(ty):
ctype_obj = ctypes.pointer(ctype_obj)
# ctypes -> pykit
new_const = from_ctypes_value(ctype_obj)
context[new_const] = ty
new_constants.append(new_const)
_keep_alive.extend([ctype_obj, c.const])
substitute_args(op, constants, new_constants)
def tonb(tup):
return fromobject(tup, typeof(tup))
def tonb(tup):
return fromobject(tup, typeof(tup))
