delete_code (#4635)

PaddleNLP/dialogue_system/auto_dialogue_evaluation/ade/utils/save_load_io.py

-# Copyright (c) 2019 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.
-"""save or load model api"""
-
-import os
-import sys
-
-import paddle
-import paddle.fluid as fluid
-
-
-def init_from_pretrain_model(args, exe, program):
-
-    assert isinstance(args.init_from_pretrain_model, str)
-
-    if not os.path.exists(args.init_from_pretrain_model):
-        raise Warning("The pretrained params do not exist.")
-        return False
-
-    def existed_params(var):
-        if not isinstance(var, fluid.framework.Parameter):
-            return False
-        return os.path.exists(
-            os.path.join(args.init_from_pretrain_model, var.name))
-
-    fluid.io.load_vars(
-        exe,
-        args.init_from_pretrain_model,
-        main_program=program,
-        predicate=existed_params)
-
-    print("finish initing model from pretrained params from %s" %
-          (args.init_from_pretrain_model))
-
-    return True
-
-
-def init_from_checkpoint(args, exe, program):
-
-    assert isinstance(args.init_from_checkpoint, str)
-
-    if not os.path.exists(args.init_from_checkpoint):
-        raise Warning("the checkpoint path does not exist.")
-        return False
-
-    fluid.io.load_persistables(
-        executor=exe,
-        dirname=args.init_from_checkpoint,
-        main_program=program,
-        filename="checkpoint.pdckpt")
-
-    print("finish initing model from checkpoint from %s" %
-          (args.init_from_checkpoint))
-
-    return True
-
-
-def init_from_params(args, exe, program):
-
-    assert isinstance(args.init_from_params, str)
-
-    if not os.path.exists(args.init_from_params):
-        raise Warning("the params path does not exist.")
-        return False
-
-    fluid.io.load_params(
-        executor=exe,
-        dirname=args.init_from_params,
-        main_program=program,
-        filename="params.pdparams")
-
-    print("finish init model from params from %s" % (args.init_from_params))
-
-    return True
-
-
-def save_checkpoint(args, exe, program, dirname):
-
-    assert isinstance(args.save_model_path, str)
-
-    checkpoint_dir = os.path.join(args.save_model_path, args.save_checkpoint)
-
-    if not os.path.exists(checkpoint_dir):
-        os.mkdir(checkpoint_dir)
-
-    fluid.io.save_persistables(
-        exe,
-        os.path.join(checkpoint_dir, dirname),
-        main_program=program,
-        filename="checkpoint.pdckpt")
-
-    print("save checkpoint at %s" % (os.path.join(checkpoint_dir, dirname)))
-
-    return True
-
-
-def save_param(args, exe, program, dirname):
-
-    assert isinstance(args.save_model_path, str)
-
-    param_dir = os.path.join(args.save_model_path, args.save_param)
-
-    if not os.path.exists(param_dir):
-        os.makedirs(param_dir)
-
-    fluid.io.save_params(
-        exe,
-        os.path.join(param_dir, dirname),
-        main_program=program,
-        filename="params.pdparams")
-    print("save parameters at %s" % (os.path.join(param_dir, dirname)))
-
-    return True

PaddleNLP/dialogue_system/dialogue_general_understanding/dgu/utils/save_load_io.py

-# Copyright (c) 2019 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.
-"""save or load model api"""
-
-import os
-import sys
-
-import paddle
-import paddle.fluid as fluid
-
-
-def init_from_pretrain_model(args, exe, program):
-
-    assert isinstance(args.init_from_pretrain_model, str)
-
-    if not os.path.exists(args.init_from_pretrain_model):
-        raise Warning("The pretrained params do not exist.")
-        return False
-
-    def existed_params(var):
-        if not isinstance(var, fluid.framework.Parameter):
-            return False
-        return os.path.exists(
-            os.path.join(args.init_from_pretrain_model, var.name))
-
-    fluid.io.load_vars(
-        exe,
-        args.init_from_pretrain_model,
-        main_program=program,
-        predicate=existed_params)
-
-    print("finish initing model from pretrained params from %s" %
-          (args.init_from_pretrain_model))
-
-    return True
-
-
-def init_from_checkpoint(args, exe, program):
-
-    assert isinstance(args.init_from_checkpoint, str)
-
-    if not os.path.exists(args.init_from_checkpoint):
-        raise Warning("the checkpoint path does not exist.")
-        return False
-
-    fluid.io.load_persistables(
-        executor=exe,
-        dirname=args.init_from_checkpoint,
-        main_program=program,
-        filename="checkpoint.pdckpt")
-
-    print("finish initing model from checkpoint from %s" %
-          (args.init_from_checkpoint))
-
-    return True
-
-
-def init_from_params(args, exe, program):
-
-    assert isinstance(args.init_from_params, str)
-
-    if not os.path.exists(args.init_from_params):
-        raise Warning("the params path does not exist.")
-        return False
-
-    fluid.io.load_params(
-        executor=exe,
-        dirname=args.init_from_params,
-        main_program=program,
-        filename="params.pdparams")
-
-    print("finish init model from params from %s" % (args.init_from_params))
-
-    return True
-
-
-def save_checkpoint(args, exe, program, dirname):
-
-    assert isinstance(args.save_model_path, str)
-
-    checkpoint_dir = os.path.join(args.save_model_path, args.save_checkpoint)
-
-    if not os.path.exists(checkpoint_dir):
-        os.mkdir(checkpoint_dir)
-
-    fluid.io.save_persistables(
-        exe,
-        os.path.join(checkpoint_dir, dirname),
-        main_program=program,
-        filename="checkpoint.pdckpt")
-
-    print("save checkpoint at %s" % (os.path.join(checkpoint_dir, dirname)))
-
-    return True
-
-
-def save_param(args, exe, program, dirname):
-
-    assert isinstance(args.save_model_path, str)
-
-    param_dir = os.path.join(args.save_model_path, args.save_param)
-
-    if not os.path.exists(param_dir):
-        os.makedirs(param_dir)
-
-    fluid.io.save_params(
-        exe,
-        os.path.join(param_dir, dirname),
-        main_program=program,
-        filename="params.pdparams")
-    print("save parameters at %s" % (os.path.join(param_dir, dirname)))
-
-    return True