def __hrepr__(self, H, hrepr):
"""Return HTML representation (uses buche-cytoscape)."""
if hrepr.config.depth > 1 and not hrepr.config.graph_expand_all:
label = short_labeler.label(self, True)
return H.span['node', f'node-Graph'](label)
dc = hrepr.config.duplicate_constants
dfv = hrepr.config.duplicate_free_variables
fin = hrepr.config.function_in_node
fr = hrepr.config.follow_references
tgen = hrepr.config.node_tooltip
cgen = hrepr.config.node_class
xsty = hrepr.config.graph_style
beau = hrepr.config.graph_beautify
gpr = MyiaGraphPrinter(
{self},
duplicate_constants=True if dc is None else dc,
duplicate_free_variables=True if dfv is None else dfv,
function_in_node=True if fin is None else fin,
follow_references=True if fr is None else fr,
tooltip_gen=tgen,
class_gen=cgen,
extra_style=xsty,
beautify=True if beau is None else beau)
gpr.process()
return gpr.__hrepr__(H, hrepr)
def run_test(args):
pip = pipeline.make()
argspec = tuple({'value': arg} for arg in args)
pip.resources.inferrer.fill_in(argspec)
print(argspec)
for arg in argspec:
del arg['value']
result_py = fn(*args)
try:
res = pip(input=fn, argspec=argspec)
except InferenceError as ierr:
print_inference_error(ierr)
raise ierr
except ValidationError as verr:
print('Collected the following errors:')
for err in verr.errors:
n = err.node
nlbl = lbl.label(n)
print(f' {nlbl} ({type(n).__name__}) :: {n.type}')
print(f' {err.args[0]}')
raise verr
result_final = res['output'](*args)
if isinstance(result_py, numpy.ndarray):
assert (result_py == result_final).all()
else:
assert result_py == result_final
def _opt_fancy_array_map(optimizer, node, equiv):
xs = equiv[Xs]
v = equiv[V]
if v.is_constant_graph():
return node
name = short_labeler.label(v)
ct = Constant(GraphCosmeticPrimitive(f'[{name}]'))
with About(node.debug, 'cosmetic'):
return Apply([ct, *xs], node.graph)
def mkdict(info):
d = {k: v for k, v in info.__dict__.items()
if not k.startswith('_') and k not in exclude}
tr = d.get('trace', None)
if tr:
fr = tr[-3]
d['trace'] = parser.Location(
fr.filename, fr.lineno, 0, fr.lineno, 0, None
)
d['name'] = short_labeler.label(info)
return d
def run_test(args):
if isinstance(args, Exception):
exc = type(args)
args = args.args
else:
exc = None
pdef = pipeline
if not validate:
pdef = pdef.configure(validate=False)
pip = pdef.make()
if abstract is None:
argspec = tuple(
from_value(arg, broaden=True) for arg in args)
else:
argspec = tuple(to_abstract_test(a) for a in abstract)
if exc is not None:
try:
mfn = pip(input=fn, argspec=argspec)
mfn['output'](*args)
except exc:
pass
return
result_py = fn(*args)
try:
res = pip(input=fn, argspec=argspec)
except InferenceError as ierr:
print_inference_error(ierr)
raise ierr
except ValidationError as verr:
print('Collected the following errors:')
for err in verr.errors:
n = err.node
nlbl = lbl.label(n)
tname = type(n).__name__
print(f' {nlbl} ({tname}) :: {n.abstract}')
print(f' {err.args[0]}')
raise verr
result_final = res['output'](*args)
assert _eq(result_py, result_final)
def run_test(args):
pip = pipeline.make()
argspec = tuple(from_value(arg, broaden=True) for arg in args)
result_py = fn(*args)
try:
res = pip(input=fn, argspec=argspec)
except InferenceError as ierr:
print_inference_error(ierr)
raise ierr
except ValidationError as verr:
print('Collected the following errors:')
for err in verr.errors:
n = err.node
nlbl = lbl.label(n)
print(f' {nlbl} ({type(n).__name__}) :: {n.type}')
print(f' {err.args[0]}')
raise verr
result_final = res['output'](*args)
assert _eq(result_py, result_final)
def lbl(x):
if isinstance(x, ParentProxy):
return f"{short_labeler.label(x.graph)}'"
else:
return short_labeler.label(x)
def __hrepr__(self, H, hrepr):
class_name = 'constant'
label = 'Prox:' + short_labeler.label(self.graph, True)
return H.span['node', f'node-{class_name}'](label)
def __hrepr__(self, H, hrepr):
class_name = self.__class__.__name__.lower()
label = short_labeler.label(self, True)
return H.span['node', f'node-{class_name}'](label)
def __hrepr__(self, H, hrepr):
class_name = "constant"
label = "Prox:" + short_labeler.label(self.graph, True)
return H.span["node", f"node-{class_name}"](label)
def name(node):
return short_labeler.label(node, fn_label=False)
