def visit_Call(self, node):
full_name = str(anno.getanno(node.func, anno.Basic.QN, default=''))
function_context_name = self.state[_Function].context_name
node = self.generic_visit(node)
# TODO(mdan): Refactor converted_call as a 'Call' operator.
# Calls to the internal 'ag__' module are never converted (though their
# arguments might be).
if full_name.startswith('ag__.'):
return node
# Calls to the function context manager (inserted by function_scopes) are
# also safe.
if full_name.startswith(function_context_name + '.'):
return node
# Calls to pdb.set_trace or ipdb.set_trace are never converted. We don't use
# the normal mechanisms to bypass these literals because they are sensitive
# to the frame they are being called from.
# TODO(mdan): Generalize this to a "static allowlist" config.
if full_name in ('pdb.set_trace', 'ipdb.set_trace', 'breakpoint'):
global set_trace_warned
if not set_trace_warned:
# TODO(mdan): Update and shorten once available on tensorflow.org.
ag_logging.warning(
'Detected `pdb.set_trace()` in user code. The code'
' generated by AutoGraph is not optimized for step-by-step'
' debugging. See https://github.com/tensorflow/tensorflow/'
'blob/master/tensorflow/python/autograph/g3doc/reference/'
'debugging.md.')
set_trace_warned = True
return node
if (full_name == 'print' and not self.ctx.user.options.uses(
converter.Feature.BUILTIN_FUNCTIONS)):
return node
template = """
ag__.converted_call(func, args, kwargs, function_ctx)
"""
new_call = templates.replace_as_expression(
template,
func=node.func,
args=self._args_to_tuple(node),
kwargs=self._kwargs_to_dict(node),
function_ctx=function_context_name)
return new_call
def is_unsupported(o):
"""Checks whether an entity is supported by AutoGraph at all."""
# TODO(b/122265385): Remove this bypass.
if (_is_known_loaded_type(o, 'wrapt', 'FunctionWrapper')
or _is_known_loaded_type(o, 'wrapt', 'BoundFunctionWrapper')):
logging.warning(
'{} appears to be decorated by wrapt, which is not yet supported'
' by AutoGraph. The function will run as-is.'
' You may still apply AutoGraph before the wrapt decorator.'.
format(o))
logging.log(2, 'Permanently allowed: %s: wrapt decorated', o)
return True
if _is_known_loaded_type(o, 'functools', '_lru_cache_wrapper'):
logging.log(2, 'Permanently allowed: %s: lru_cache', o)
return True
# Constructors are permanently allowed.
# TODO(mdan): Toggle as experimental feature instead.
# TODO(b/124016764): Remove this limitation.
if inspect_utils.isconstructor(o):
logging.log(2, 'Permanently allowed: %s: constructor', o)
return True
# Other built-in modules are permanently allowed.
# TODO(mdan): Figure out how to do this consistently for all stdlib modules.
if any(
_is_of_known_loaded_module(o, m)
for m in ('collections', 'pdb', 'copy', 'inspect', 're')):
logging.log(2, 'Permanently allowed: %s: part of builtin module', o)
return True
# Custom ops and kernels are also permanently allowed.
# See tensorflow.framework.load_library.
if (hasattr(o, '__module__')
and hasattr(o.__module__, '_IS_TENSORFLOW_PLUGIN')):
logging.log(2, 'Permanently allowed: %s: TensorFlow plugin', o)
return True
return False
def _verify_inefficient_unroll(self):
"""Checks for possibly-inefficient creation of ops in a Python loop."""
assert self.ops_before_iteration is not None
ops_after_iteration = self._get_ops()
new_ops = tuple(
op for op in ops_after_iteration if op not in self.ops_before_iteration)
if len(new_ops) < INEFFICIENT_UNROLL_MIN_OPS:
return False
ag_logging.warning(
'Large unrolled loop detected. Did you mean to use a TF loop?'
' The following ops were created after iteration %s: %s'
'\nSee'
' https://github.com/tensorflow/tensorflow/blob/master/'
'tensorflow/python/autograph/g3doc/reference/common_errors.md'
'#warning-large-unrolled-loop-detected'
'\n'
'Location:'
'\n%s'
'', self.iterations, new_ops, '\n'.join(traceback.format_stack()))
return True
def _fall_back_unconverted(f, args, kwargs, options, exc):
"""Falls back to calling the function unconverted, in case of error."""
# TODO(mdan): Consider adding an internal metric.
warning_template = (
'AutoGraph could not transform %s and will run it as-is.\n'
'%s'
'Cause: %s\n'
'To silence this warning, decorate the function with'
' @tf.autograph.experimental.do_not_convert')
if isinstance(exc, errors.InaccessibleSourceCodeError):
if ag_ctx.INSPECT_SOURCE_SUPPORTED:
logging.warning(warning_template, f, '', exc)
elif isinstance(exc, errors.UnsupportedLanguageElementError):
if not conversion.is_in_allowlist_cache(f, options):
logging.warning(warning_template, f, '', exc)
else:
file_bug_message = (
'Please report this to the TensorFlow team. When filing the bug, set'
' the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and'
' attach the full output.\n')
logging.warning(warning_template, f, file_bug_message, exc)
return _call_unconverted(f, args, kwargs, options)
def __exit__(self, unused_type, unused_value, unused_traceback):
assert _control_ctx()[-1] is self
_control_ctx().pop()
class NullCtx(object):
"""Helper substitute for contextlib.nullcontext."""
def __enter__(self):
pass
def __exit__(self, unused_type, unused_value, unused_traceback):
pass
def _default_control_status_ctx():
return ControlStatusCtx(status=Status.UNSPECIFIED)
INSPECT_SOURCE_SUPPORTED = True
try:
inspect.getsource(ag_logging.log)
except OSError:
INSPECT_SOURCE_SUPPORTED = False
ag_logging.warning(
'AutoGraph is not available in this environment: functions lack code'
' information. This is typical of some environments like the interactive'
' Python shell. See'
' https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/autograph/g3doc/reference/limitations.md#access-to-source-code'
' for more information.')