Spaces:
Paused
Paused
File size: 1,735 Bytes
2f5127c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
# Copyright 2020-2025 The HuggingFace Team. 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 unittest
import torch
from trl.core import masked_mean, masked_var, masked_whiten
class CoreTester(unittest.TestCase):
"""
A wrapper class for testing core utils functions
"""
def setUp(self):
self.test_input = torch.Tensor([1, 2, 3, 4])
self.test_mask = torch.Tensor([0, 1, 1, 0])
self.test_input_unmasked = self.test_input[1:3]
def test_masked_mean(self):
self.assertEqual(torch.mean(self.test_input_unmasked), masked_mean(self.test_input, self.test_mask))
def test_masked_var(self):
self.assertEqual(torch.var(self.test_input_unmasked), masked_var(self.test_input, self.test_mask))
def test_masked_whiten(self):
def whiten(values: torch.Tensor) -> torch.Tensor:
mean, var = torch.mean(values), torch.var(values)
return (values - mean) * torch.rsqrt(var + 1e-8)
whiten_unmasked = whiten(self.test_input_unmasked)
whiten_masked = masked_whiten(self.test_input, self.test_mask)[1:3]
diffs = (whiten_unmasked - whiten_masked).sum()
self.assertLess(abs(diffs.item()), 0.00001)
|