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)]