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Paddle/python/paddle/incubate/hapi/dygraph_layer_patch.py

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3.9 KiB

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import warnings
import paddle.fluid as fluid
from paddle.fluid.framework import in_dygraph_mode
from .device import _get_device
def monkey_patch_layer():
def load_dict(self,
stat_dict,
include_sublayers=True,
use_structured_name=True):
'''
Set parameters from stat_dict. All the parameters will be reset by the
tensor in the stat_dict
This api will be Deprecated. Please use set_dict
Parameters:
state_dict(dict) : Dict contains all the parameters
include_sublayers(bool, optional) : If true, also include the
parameters from sublayers. Default: True
use_structured_name(bool, optional) : If true, use structured name
as key, otherwise, use parameter name as key. Default: True
Returns:
None
Examples:
.. code-block:: python
import paddle.fluid as fluid
with fluid.dygraph.guard():
emb = fluid.dygraph.Embedding([10, 10])
state_dict = emb.state_dict()
fluid.save_dygraph( state_dict, "paddle_dy")
para_state_dict, _ = fluid.load_dygraph( "paddle_dy")
emb.load_dict( para_state_dict )
'''
def _check_match(key, param):
state = stat_dict.get(key, None)
if state is None:
raise ValueError(
"{} is not found in the providing file.".format(key))
if list(state.shape) != list(param.shape):
raise ValueError(
"{} receives a shape {}, but the expected shape is {}.".
format(key, list(state.shape), list(param.shape)))
return param, state
matched_param_state = []
for key, param in self.state_dict().items():
key_name = key if use_structured_name else param.name
try:
match_res = _check_match(key_name, param)
matched_param_state.append(match_res)
except ValueError as err:
warnings.warn(("Skip loading for {}. ".format(key) + str(err)))
if in_dygraph_mode():
for param, state in matched_param_state:
param.set_value(state)
else:
def _set_var(var, ndarray):
t = fluid.global_scope().find_var(var.name).get_tensor()
p = t._place()
if p.is_cpu_place():
place = fluid.CPUPlace()
elif p.is_cuda_pinned_place():
place = fluid.CUDAPinnedPlace()
else:
p = fluid.core.Place()
p.set_place(t._place())
place = fluid.CUDAPlace(p.gpu_device_id())
t.set(ndarray, place)
executor = fluid.Executor(_get_device())._default_executor
# restore parameter states
fluid.core._create_loaded_parameter(
[param for param, state in matched_param_state],
fluid.global_scope(), executor)
for param, state in matched_param_state:
_set_var(param, state)
setattr(fluid.dygraph.Layer, 'load_dict', load_dict)