def _call_func(self, args, kwargs):
try:
vars_at_start = self._template_store.variables()
trainable_at_start = self._template_store.trainable_variables()
if self._variables_created:
result = self._func(*args, **kwargs)
else:
# The first time we run, restore variables if necessary (via
# Trackable).
with trackable_util.capture_dependencies(template=self):
result = self._func(*args, **kwargs)
if self._variables_created:
# Variables were previously created, implying this is not the first
# time the template has been called. Check to make sure that no new
# trainable variables were created this time around.
trainable_variables = self._template_store.trainable_variables(
)
# If a variable that we intend to train is created as a side effect
# of creating a template, then that is almost certainly an error.
if len(trainable_at_start) != len(trainable_variables):
raise ValueError(
"Trainable variable created when calling a template "
"after the first time, perhaps you used tf.Variable "
"when you meant tf.get_variable: %s" % list(
object_identity.ObjectIdentitySet(
trainable_variables) - object_identity.
ObjectIdentitySet(trainable_at_start)))
# Non-trainable tracking variables are a legitimate reason why a new
# variable would be created, but it is a relatively advanced use-case,
# so log it.
variables = self._template_store.variables()
if len(vars_at_start) != len(variables):
logging.info(
"New variables created when calling a template after "
"the first time, perhaps you used tf.Variable when you "
"meant tf.get_variable: %s",
list(
object_identity.ObjectIdentitySet(variables) -
object_identity.ObjectIdentitySet(vars_at_start)))
else:
self._variables_created = True
return result
except Exception as exc:
# Reraise the exception, but append the original definition to the
# trace.
args = exc.args
if not args:
arg0 = ""
else:
arg0 = args[0]
trace = "".join(
_skip_common_stack_elements(self._stacktrace,
traceback.format_stack()))
arg0 = "%s\n\noriginally defined at:\n%s" % (arg0, trace)
new_args = [arg0]
new_args.extend(args[1:])
exc.args = tuple(new_args)
raise
def _call_func(self, args, kwargs):
try:
vars_at_start = self._template_store.variables()
trainable_at_start = self._template_store.trainable_variables()
if self._variables_created:
result = self._func(*args, **kwargs)
else:
# The first time we run, restore variables if necessary (via
# Trackable).
with trackable_util.capture_dependencies(template=self):
result = self._func(*args, **kwargs)
if self._variables_created:
# Variables were previously created, implying this is not the first
# time the template has been called. Check to make sure that no new
# trainable variables were created this time around.
trainable_variables = self._template_store.trainable_variables()
# If a variable that we intend to train is created as a side effect
# of creating a template, then that is almost certainly an error.
if len(trainable_at_start) != len(trainable_variables):
raise ValueError(
"Trainable variable created when calling a template "
"after the first time, perhaps you used tf.Variable "
"when you meant tf.get_variable: %s" %
list(set(trainable_variables) - set(trainable_at_start)))
# Non-trainable tracking variables are a legitimate reason why a new
# variable would be created, but it is a relatively advanced use-case,
# so log it.
variables = self._template_store.variables()
if len(vars_at_start) != len(variables):
logging.info(
"New variables created when calling a template after "
"the first time, perhaps you used tf.Variable when you "
"meant tf.get_variable: %s",
list(set(variables) - set(vars_at_start)))
else:
self._variables_created = True
return result
except Exception as exc:
# Reraise the exception, but append the original definition to the
# trace.
args = exc.args
if not args:
arg0 = ""
else:
arg0 = args[0]
trace = "".join(
_skip_common_stack_elements(self._stacktrace,
traceback.format_stack()))
arg0 = "%s\n\noriginally defined at:\n%s" % (arg0, trace)
new_args = [arg0]
new_args.extend(args[1:])
exc.args = tuple(new_args)
raise
def __call__(self):
with variable_scope.variable_scope("ManualScope") as vs:
self.variable_scope = vs
with trackable_utils.capture_dependencies(template=self):
return self._build()
def __call__(self):
with tf.compat.v1.variable_scope("ManualScope") as vs:
self.variable_scope = vs
with trackable_utils.capture_dependencies(template=self):
return self._build()
