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- """
- Copyright 2020 Tianshu AI Platform. 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 numpy as np
- import torch
- from kamal.core.metrics.stream_metrics import Metric
- from typing import Callable
-
- __all__=['AverageMetric']
-
- class AverageMetric(Metric):
- def __init__(self, fn:Callable, attach_to=None):
- super(AverageMetric, self).__init__(attach_to=attach_to)
- self._fn = fn
- self.reset()
-
- @torch.no_grad()
- def update(self, outputs, targets):
-
- outputs, targets = self._attach(outputs, targets)
- m = self._fn( outputs, targets )
-
- if m.ndim > 1:
- self._cnt += m.shape[0]
- self._accum += m.sum(0)
- else:
- self._cnt += 1
- self._accum += m
-
- def get_results(self):
- return (self._accum / self._cnt).detach().cpu()
-
- def reset(self):
- self._accum = 0.
- self._cnt = 0.
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