def compress(cls, operators):
sets = OrderedDict()
incs = OrderedDict()
rval = []
for op in operators:
if isinstance(op, cls):
if op.as_update:
rval.append(op)
else:
assert op.sets or op.incs
if op.sets:
sets.setdefault(op.sets[0], []).append(op)
if op.incs:
incs.setdefault(op.incs[0], []).append(op)
else:
rval.append(op)
done = set()
for view, set_ops in sets.items():
set_op, = set_ops
done.add(set_op)
for inc_op in incs.get(view, []):
set_op.As.extend(inc_op.As)
set_op.Xs.extend(inc_op.Xs)
done.add(inc_op)
rval.append(set_op)
for view, inc_ops in incs.items():
for inc_op in inc_ops:
if inc_op not in done:
rval.append(inc_op)
return rval
class Effect(object):
"""Parses an Action effect given a set of module outputs.
Parameters
----------
sources : list of string
The names of valid sources of information (SPA module outputs)
sinks : list of string
The names of valid places to send information (SPA module inputs)
effect: string
The action to implement. This is a set of assignment statements
which can be parsed into a VectorList.
The following are valid effects:
"motor=A"
"motor=A*B, memory=vision+DOG"
"motor=0.5*(memory*A + vision*B)"
"""
def __init__(self, sources, sinks, effect):
self.effect = OrderedDict()
# Splits by ',' and separates into lvalue=rvalue. We cannot simply use
# split, because the rvalue may contain commas in the case of dot(*,*).
# However, *? is lazy, and * is greedy, making this regex work.
for lvalue, rvalue in re.findall("(.*?)=([^=]*)(?:,|$)", effect):
sink = lvalue.strip()
if sink not in sinks:
raise NameError("Left-hand module '%s' from effect '%s=%s' "
"is not defined." %
(lvalue, lvalue, rvalue))
if sink in self.effect:
raise ValueError("Left-hand module '%s' from effect '%s=%s' "
"is assigned to multiple times in '%s'." %
(lvalue, lvalue, rvalue, effect))
self.effect[sink] = Expression(sources, rvalue)
def __str__(self):
return ", ".join("%s=%s" % x for x in self.effect.items())
class Effect(object):
"""Parses an Action effect given a set of module outputs.
Parameters
----------
sources : list of string
The names of valid sources of information (SPA module outputs)
sinks : list of string
The names of valid places to send information (SPA module inputs)
effect: string
The action to implement. This is a set of assignment statements
which can be parsed into a VectorList.
The following are valid effects:
"motor=A"
"motor=A*B, memory=vision+DOG"
"motor=0.5*(memory*A + vision*B)"
"""
def __init__(self, sources, sinks, effect):
self.effect = OrderedDict()
# Splits by ',' and separates into lvalue=rvalue. We cannot simply use
# split, because the rvalue may contain commas in the case of dot(*,*).
# However, *? is lazy, and * is greedy, making this regex work.
for lvalue, rvalue in re.findall("(.*?)=([^=]*)(?:,|$)", effect):
sink = lvalue.strip()
if sink not in sinks:
raise NameError("Left-hand module '%s' from effect '%s=%s' "
"is not defined." % (lvalue, lvalue, rvalue))
if sink in self.effect:
raise ValueError("Left-hand module '%s' from effect '%s=%s' "
"is assigned to multiple times in '%s'." %
(lvalue, lvalue, rvalue, effect))
self.effect[sink] = Expression(sources, rvalue)
def __str__(self):
return ", ".join("%s=%s" % x for x in self.effect.items())
def plan_SimPyFunc(self, ops):
# TODO: test with a hybrid program (Python and OCL)
# group nonlinearities
unique_ops = OrderedDict()
for op in ops:
# assert op.n_args in (1, 2), op.n_args
op_key = (op.fn, op.t_in, op.x is not None)
if op_key not in unique_ops:
unique_ops[op_key] = {'in': [], 'out': []}
unique_ops[op_key]['in'].append(op.x)
unique_ops[op_key]['out'].append(op.output)
# make plans
plans = []
for (fn, t_in, x_in), signals in unique_ops.items():
fn_name = (fn.__name__ if inspect.isfunction(fn) else
fn.__class__.__name__)
if fn_name == "<lambda>":
fn_name += "%d" % len(plans)
# check signal input and output shape (implicitly checks
# for indexing errors)
vector_dims = lambda shape, dim: len(
shape) == 1 and shape[0] == dim
unit_stride = lambda es: len(es) == 1 and es[0] == 1
if x_in:
in_dim = signals['in'][0].size
for sig_in in signals['in']:
assert sig_in.size == in_dim
assert vector_dims(sig_in.shape, in_dim)
assert unit_stride(sig_in.elemstrides)
else:
in_dim = None
# if any functions have no output, must do them in Python
if any(s is None for s in signals['out']):
assert all(s is None for s in signals['out'])
warnings.warn(
"Function '%s' could not be converted to OCL since it has "
"no outputs." % (fn_name), RuntimeWarning)
plans.append(self._plan_pythonfn(
fn, t_in, signals, fn_name=fn_name))
continue
out_dim = signals['out'][0].size
for sig_out in signals['out']:
assert sig_out.size == out_dim
assert vector_dims(sig_out.shape, out_dim)
assert unit_stride(sig_out.elemstrides)
# try to get OCL code
try:
in_dims = [1] if t_in else []
in_dims += [in_dim] if x_in else []
ocl_fn = OCL_Function(fn, in_dims=in_dims, out_dim=out_dim)
input_names = ocl_fn.translator.arg_names
inputs = []
if t_in: # append time
inputs.append(self.all_data[
[self.sidx[self._time] for i in signals['out']]])
if x_in: # append x
inputs.append(self.all_data[
[self.sidx[i] for i in signals['in']]])
output = self.all_data[[self.sidx[i] for i in signals['out']]]
plan = plan_direct(self.queue, ocl_fn.code, ocl_fn.init,
input_names, inputs, output, tag=fn_name)
plans.append(plan)
except Exception as e:
if self.ocl_only:
raise
warnings.warn(
"Function '%s' could not be converted to OCL due to %s%s"
% (fn_name, e.__class__.__name__, e.args), RuntimeWarning)
# not successfully translated to OCL, so do it in Python
plans.append(self._plan_pythonfn(
fn, t_in, signals, fn_name=fn_name))
return plans
def plan_SimPyFunc(self, ops):
# TODO: test with a hybrid program (Python and OCL)
# group nonlinearities
unique_ops = OrderedDict()
for op in ops:
# assert op.n_args in (1, 2), op.n_args
op_key = (op.fn, op.t_in, op.x is not None)
if op_key not in unique_ops:
unique_ops[op_key] = {'in': [], 'out': []}
unique_ops[op_key]['in'].append(op.x)
unique_ops[op_key]['out'].append(op.output)
# make plans
plans = []
for (fn, t_in, x_in), signals in unique_ops.items():
fn_name = (fn.__name__
if inspect.isfunction(fn) else fn.__class__.__name__)
if fn_name == "<lambda>":
fn_name += "%d" % len(plans)
# check signal input and output shape (implicitly checks
# for indexing errors)
vector_dims = lambda shape, dim: len(shape) == 1 and shape[0
] == dim
unit_stride = lambda es: len(es) == 1 and es[0] == 1
if x_in:
in_dim = signals['in'][0].size
for sig_in in signals['in']:
assert sig_in.size == in_dim
assert vector_dims(sig_in.shape, in_dim)
assert unit_stride(sig_in.elemstrides)
else:
in_dim = None
# if any functions have no output, must do them in Python
if any(s is None for s in signals['out']):
assert all(s is None for s in signals['out'])
warnings.warn(
"Function '%s' could not be converted to OCL since it has "
"no outputs." % (fn_name), RuntimeWarning)
plans.append(
self._plan_pythonfn(fn, t_in, signals, fn_name=fn_name))
continue
out_dim = signals['out'][0].size
for sig_out in signals['out']:
assert sig_out.size == out_dim
assert vector_dims(sig_out.shape, out_dim)
assert unit_stride(sig_out.elemstrides)
# try to get OCL code
try:
in_dims = [1] if t_in else []
in_dims += [in_dim] if x_in else []
ocl_fn = OCL_Function(fn, in_dims=in_dims, out_dim=out_dim)
input_names = ocl_fn.translator.arg_names
inputs = []
if t_in: # append time
inputs.append(self.all_data[[
self.sidx[self._time] for i in signals['out']
]])
if x_in: # append x
inputs.append(
self.all_data[[self.sidx[i] for i in signals['in']]])
output = self.all_data[[self.sidx[i] for i in signals['out']]]
plan = plan_direct(self.queue,
ocl_fn.code,
ocl_fn.init,
input_names,
inputs,
output,
tag=fn_name)
plans.append(plan)
except Exception as e:
if self.ocl_only:
raise
warnings.warn(
"Function '%s' could not be converted to OCL due to %s%s" %
(fn_name, e.__class__.__name__, e.args), RuntimeWarning)
# not successfully translated to OCL, so do it in Python
plans.append(
self._plan_pythonfn(fn, t_in, signals, fn_name=fn_name))
return plans
