def load_from_file(load_path, load_data=True, custom_objects=None):
"""Load model data from a .zip archive
:param load_path: (str or file-like) Where to load model from
:param load_data: (bool) Whether we should load and return data
(class parameters). Mainly used by `load_parameters` to
only load model parameters (weights).
:param custom_objects: (dict) Dictionary of objects to replace
upon loading. If a variable is present in this dictionary as a
key, it will not be deserialized and the corresponding item
will be used instead. Similar to custom_objects in
`keras.models.load_model`. Useful when you have an object in
file that can not be deserialized.
:return: (dict, OrderedDict) Class parameters and model parameters
"""
# Check if file exists if load_path is
# a string
if isinstance(load_path, str):
if not os.path.exists(load_path):
if os.path.exists(load_path + ".zip"):
load_path += ".zip"
else:
raise ValueError(
"Error: the file {} could not be found".format(load_path))
# Open the zip archive and load data.
try:
with zipfile.ZipFile(load_path, "r") as file_:
namelist = file_.namelist()
# If data or parameters is not in the
# zip archive, assume they were stored
# as None (_save_to_file allows this).
data = None
params = None
if "data" in namelist and load_data:
# Load class parameters and convert to string
# (Required for json library in Python 3.5)
json_data = file_.read("data").decode()
data = json_to_data(json_data, custom_objects=custom_objects)
if "parameters" in namelist:
# Load parameter list and and parameters
parameter_list_json = file_.read("parameter_list").decode()
parameter_list = json.loads(parameter_list_json)
serialized_params = file_.read("parameters")
params = bytes_to_params(serialized_params, parameter_list)
except zipfile.BadZipFile:
# load_path wasn't a zip file. Possibly a cloudpickle
# file. Show a warning and fall back to loading cloudpickle.
warnings.warn(
"It appears you are loading from a file with old format. " +
"Older cloudpickle format has been replaced with zip-archived " +
"models. Consider saving the model with new format.",
DeprecationWarning)
# Attempt loading with the cloudpickle format.
# If load_path is file-like, seek back to beginning of file
if not isinstance(load_path, str):
load_path.seek(0)
data, params = BaseRLModel._load_from_file_cloudpickle(load_path)
return data, params
def __init__(self, load_path):
self.load_path = load_path
if load_path.endswith(".pkl"):
with open(load_path, "rb") as file_:
self.data, self.params = cloudpickle.load(file_)
elif load_path.endswith(".zip"):
with zipfile.ZipFile(load_path, "r") as file_:
namelist = file_.namelist()
# If data or parameters is not in the
# zip archive, assume they were stored
# as None (_save_to_file allows this).
data = None
params = None
custom_objects = None
load_data = True
if "data" in namelist and load_data:
# Load class parameters and convert to string
# (Required for json library in Python 3.5)
json_data = file_.read("data").decode()
data = json_to_data(json_data,
custom_objects=custom_objects)
self.data = data
if "parameters" in namelist:
# Load parameter list and and parameters
parameter_list_json = file_.read("parameter_list").decode()
parameter_list = json.loads(parameter_list_json)
serialized_params = file_.read("parameters")
params = bytes_to_params(serialized_params, parameter_list)
self.params = params
else:
raise RuntimeError("bad file path for stable baselines load")
def load(self, path):
# load data
d_path = osp.join(path, 'params')
with open(d_path, 'r') as f:
json_data = f.read()
data = json_to_data(json_data)
# weights
w_path = osp.join(path, 'model')
return data, w_path
def _load_from_file(load_path, load_data=True, custom_objects=None):
"""Load model data from a .zip archive
:param load_path: (str or file-like) Where to load model from
:param load_data: (bool) Whether we should load and return data (class parameters). Mainly used by `load_parameters` to
only load model parameters (weights).
:param custom_objects: (dict) Dictionary of objects to replace
upon loading. If a variable is present in this dictionary as a key, it will not be deserialized and the corresponding item
will be used instead. Similar to custom_objects in `keras.models.load_model`. Useful when you have an object in
file that can not be deserialized.
:return: (dict, OrderedDict) Class parameters and model parameters
"""
# Check if file exists if load_path is a string
if isinstance(load_path, str):
if not os.path.exists(load_path):
if os.path.exists(load_path + ".zip"):
load_path += ".zip"
else:
raise ValueError("Error: the file {} could not be found".format(load_path))
# Open the zip archive and load data.
with zipfile.ZipFile(load_path, "r") as file_:
namelist = file_.namelist()
# If data or parameters is not in the zip archive, assume they were stored as None (_save_to_file allows this).
data = None
params = None
if "data" in namelist and load_data:
# Load class parameters and convert to string
# (Required for json library in Python 3.5)
json_data = file_.read("data").decode()
data = save_util.json_to_data(json_data, custom_objects=custom_objects)
if "parameters" in namelist:
# Load parameter list and and parameters
parameter_list_json = file_.read("parameter_list").decode()
parameter_list = json.loads(parameter_list_json)
serialized_params = file_.read("parameters")
params = save_util.bytes_to_params(serialized_params, parameter_list)
return data, params
