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58 lines
2.1 KiB
58 lines
2.1 KiB
# Copyright (c) 2018 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 core
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import framework
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import executor
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import io
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from trainer import check_and_get_place
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__all__ = ['Inferencer', ]
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class Inferencer(object):
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def __init__(self, param_path, place=None):
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"""
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:param param_path: the path where the inference model is saved by fluid.io.save_inference_model
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:param place: place to do the inference
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"""
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self.param_path = param_path
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self.scope = core.Scope()
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self.exe = executor.Executor(check_and_get_place(place))
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with executor.scope_guard(self.scope):
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# load params from param_path into scope
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[self.inference_program, _,
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self.fetch_targets] = io.load_inference_model(
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executor=self.exe, dirname=param_path)
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def infer(self, inputs, return_numpy=True):
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"""
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:param inputs: a map of {"input_name": input_var} that will be feed into the inference program
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to get the predict value
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:param return_numpy: if return numpy value for row tensor
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:return: the predict value of the inference model
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"""
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if not isinstance(inputs, dict):
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raise ValueError(
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"inputs should be a map of {'input_name': input_var}")
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with executor.scope_guard(self.scope):
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results = self.exe.run(self.inference_program,
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feed=inputs,
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fetch_list=self.fetch_targets,
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return_numpy=return_numpy)
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return results
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