lambda u, v, s: unify_MetaSymbol(u, metatize(v), s),
)
_unify.add(
(tf_class_abstractions, TFlowMetaSymbol, Mapping),
lambda u, v, s: unify_MetaSymbol(metatize(u), v, s),
)
_unify.add(
(tf_class_abstractions, tf_class_abstractions, Mapping),
lambda u, v, s: unify_MetaSymbol(metatize(u), metatize(v), s),
)
def _reify_TFlowClasses(o, s):
meta_obj = metatize(o)
return reify(meta_obj, s)
_reify.add((tf_class_abstractions, Mapping), _reify_TFlowClasses)
_car.add((tf.Tensor,), lambda x: operator(metatize(x)))
operator.add((tf.Tensor,), lambda x: operator(metatize(x)))
_cdr.add((tf.Tensor,), lambda x: arguments(metatize(x)))
arguments.add((tf.Tensor,), lambda x: arguments(metatize(x)))
etuplize.add(tf_class_abstractions, lambda x, shallow=False: etuplize(metatize(x), shallow))
__all__ = []
)
_unify.add(
(tt_class_abstractions, TheanoMetaSymbol, Mapping),
lambda u, v, s: unify_MetaSymbol(metatize(u), v, s),
)
_unify.add(
(tt_class_abstractions, tt_class_abstractions, Mapping),
lambda u, v, s: unify_MetaSymbol(metatize(u), metatize(v), s),
)
def _reify_TheanoClasses(o, s):
meta_obj = metatize(o)
return reify(meta_obj, s)
_reify.add((tt_class_abstractions, Mapping), _reify_TheanoClasses)
operator.add((tt.Variable, ), lambda x: operator(metatize(x)))
_car.add((tt.Variable, ), lambda x: operator(metatize(x)))
arguments.add((tt.Variable, ), lambda x: arguments(metatize(x)))
_cdr.add((tt.Variable, ), lambda x: arguments(metatize(x)))
term.add((tt.Op, ExpressionTuple), lambda op, args: term(metatize(op), args))
etuplize.add(tt_class_abstractions,
lambda x, shallow=False: etuplize(metatize(x), shallow))
__all__ = []
This applies a special consideration for Theano `Variable`s: if it has a
non-`None` `owner` with non-`None` `op` and `inputs`, then the `Variable`
is more aptly given as the output of `op(inputs)`.
Otherwise, considering the `Variable` in isolation, it can be constructed
directly using its `type` constructor.
"""
# Get an apply node, if any
x_owner = getattr(x, 'owner', None)
if x_owner and hasattr(x_owner, 'op'):
return x_owner.inputs
return arguments_MetaSymbol(x)
arguments.add((MetaSymbol, ), arguments_MetaSymbol)
arguments.add((MetaVariable, ), arguments_MetaVariable)
arguments.add((tt.Variable, ), lambda x: arguments(MetaVariable.from_obj(x)))
# Enable [re]construction of terms
term.add((tt.Op, (list, tuple)),
lambda op, args: term(MetaOp.from_obj(op), args))
term.add((MetaOp, (list, tuple)), lambda op, args: op(*args))
# Function application for tuples/lists starting with a function or partial
term.add(((types.FunctionType, partial), (tuple, list)),
lambda op, args: op(*args))
class ExpressionTuple(tuple):
"""A tuple object that represents an expression.
x_e = etuple(type(x), *x.rands, eval_obj=x)
return x_e[1:]
def arguments_MetaVariable(x):
"""Return the arguments/tail/CDR of a variable object.
See `arguments_MetaSymbol`
"""
x_op = x.base_operator
if x_op is not None:
x_e = etuple(x_op, *x.base_arguments, eval_obj=x)
return x_e[1:]
arguments.add((MetaSymbol, ), arguments_MetaSymbol)
arguments.add((MetaVariable, ), arguments_MetaVariable)
arguments.add((ExpressionTuple, ), itemgetter(slice(1, None)))
def _term_ExpressionTuple(rand, rators):
res = (rand, ) + rators
return res.eval_obj
term.add((object, ExpressionTuple), _term_ExpressionTuple)
@_reify.register(ExpressionTuple, dict)
def _reify_ExpressionTuple(t, s):
"""When `kanren` reifies `etuple`s, we don't want them to turn into regular `tuple`s.
# original object is later reconstructed and evaluated (e.g. using
# `term`).
#
# """
# try:
# x_e = etuple(_car(x), *x.rands, eval_obj=x)
# except NotImplementedError:
# raise ConsError("Not a cons pair.")
#
# return x_e[1:]
def cdr_MetaVariable(x):
"""Return the arguments/tail/CDR of a variable object.
See `cdr_MetaSymbol`
"""
try:
x_e = etuple(_car(x), *x.base_arguments, eval_obj=x)
except NotImplementedError:
raise ConsError("Not a cons pair.")
return x_e[1:]
# _cdr.add((MetaSymbol,), cdr_MetaSymbol)
_cdr.add((MetaVariable, ), cdr_MetaVariable)
# arguments.add((MetaSymbol,), cdr_MetaSymbol)
arguments.add((MetaVariable, ), cdr_MetaVariable)