def _flags_data(self, opdef, model_paths, local_cache):
main_spec = op_util.split_cmd(opdef.main)[0]
flags_dest = opdef.flags_dest
try:
flags_data = local_cache[(main_spec, flags_dest)]
except KeyError:
_log_flags_info("reading flags for main spec %r", main_spec)
flags_data = self._flags_data_(main_spec, model_paths, opdef.flags_dest)
else:
local_cache[(main_spec, flags_dest)] = flags_data
_log_flags_info("using cached flags for main spec %r", main_spec)
return flags_data
def python_script_opdef_loaded(self, opdef):
if opdef.output_scalars is not None:
return
assert opdef.main, opdef
main_mod = op_util.split_cmd(opdef.main)[0]
model_paths = op_util.opdef_model_paths(opdef)
try:
_path, mod_path = python_util.find_module(main_mod, model_paths)
except ImportError:
return
script = python_util.Script(mod_path)
if self.is_keras_script(script):
if opdef.output_scalars is None:
opdef.output_scalars = KERAS_OUTPUT_SCALARS
def _flags_data(self, opdef, local_cache):
main_mod = op_util.split_cmd(opdef.main)[0]
flags_dest = opdef.flags_dest
try:
flags_data = local_cache[(main_mod, flags_dest)]
except KeyError:
flags_import_util.log_flags_info("reading flags for main spec %r",
main_mod)
model_paths = op_util.opdef_model_paths(opdef)
flags_data = self._flags_data_(main_mod, model_paths,
opdef.flags_dest)
else:
flags_import_util.log_flags_info(
"using cached flags for main spec %r", main_mod)
return flags_data
def _split_main_spec(main_spec):
parts = op_util.split_cmd(main_spec)
return parts[0], parts[1:]
def _split_and_resolve_args(cmd, flag_vals):
"""Splits and resolve args for string or list cmd."""
format_part = lambda part: str(util.resolve_refs(part, flag_vals))
return [format_part(part) for part in op_util.split_cmd(cmd)]
