29 lines
1 KiB
Python
29 lines
1 KiB
Python
# Copyright (c) 2021, NVIDIA CORPORATION. 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 torch
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import torch.nn as nn
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import torch.nn.functional as F
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class QuantileLoss(nn.Module):
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def __init__(self, config):
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super().__init__()
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self.register_buffer('q', torch.tensor(config.quantiles))
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def forward(self, predictions, targets):
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diff = predictions - targets
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ql = (1-self.q)*F.relu(diff) + self.q*F.relu(-diff)
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losses = ql.view(-1, ql.shape[-1]).mean(0)
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return losses
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