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# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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#     http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import errno
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import uuid
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import paddle.v2.master
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__all__ = ["save_model", "load_model"]
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trainer_id = str(uuid.uuid4())
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def mkdir_p(path):
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    try:
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        os.makedirs(path)
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    except OSError as exc:
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        if exc.errno == errno.EEXIST and os.path.isdir(path):
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            pass
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        else:
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            raise
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def save_model(parameters, path):
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    need_request = "KUBERNETES_SERVICE_HOST" in os.environ.keys()
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    if need_request:
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        # TODO(helin): figure out how MPI trains, since MPI only save
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        # model when trainer_id == "0", we can consolidate the logic
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        # here.
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        # TODO(helin): change this environment variable name from
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        # MASTER_IP to ETCD_IP
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        etcd_name = "MASTER_IP"
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        if etcd_name not in os.environ.keys():
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            raise Exception('not find ' + etcd_name +
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                            ' in environment variable.')
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        etcd_ip = os.environ.get(etcd_name)
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        client = master.client("http://" + etcd_ip + ":2379", 5, 0)
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        r = client.request_save_model(trainer_id, 5000)
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        if r == 0:
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            # do not need to save
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            return
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        elif r < 0:
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            # error
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            return
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        else:
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            # save model
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            path = os.path.join(path, trainer_id)
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            path = os.path.join(path, "model.tar")
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    mkdir_p(path)
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    with open(path, 'wb') as f:
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        parameters.to_tar(f)
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def load_model(parameters, path):
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    with open(path, 'rb') as f:
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        parameters.from_tar(f)
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