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50 lines
1.8 KiB
Python
50 lines
1.8 KiB
Python
# Copyright (c) 2020, 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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# Copyright 2018-2020 William Falcon
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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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from collections import namedtuple
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import torch
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from .pl_utils import BATCH_SIZE, NUM_BATCHES, NUM_CLASSES
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Input = namedtuple('Input', ["probs", "logits"])
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ONLY_PROBS = Input(probs=torch.rand(NUM_BATCHES, BATCH_SIZE, NUM_CLASSES), logits=None)
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ONLY_LOGITS1 = Input(probs=None, logits=torch.rand(NUM_BATCHES, BATCH_SIZE, NUM_CLASSES))
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ONLY_LOGITS100 = Input(probs=None, logits=torch.rand(NUM_BATCHES, BATCH_SIZE, NUM_CLASSES) * 200 - 100)
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PROBS_AND_LOGITS = Input(
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probs=torch.rand(NUM_BATCHES, BATCH_SIZE, NUM_CLASSES),
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logits=torch.rand(NUM_BATCHES, BATCH_SIZE, NUM_CLASSES) * 200 - 100,
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)
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NO_PROBS_NO_LOGITS = Input(probs=None, logits=None)
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