47 lines
1.6 KiB
Python
47 lines
1.6 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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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 Counter
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import numpy as np
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from prefix_data_generator.sampler import EmpiricalSampler
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def test_empirical_sampler_distribution():
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# Create a test array with equal numbers of 1, 2, and 3
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test_data = np.array([1, 2, 3, 1, 2, 3, 1, 2, 3])
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# Create the sampler
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sampler = EmpiricalSampler(test_data)
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# Sample 1000 times
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samples = [sampler.sample() for _ in range(1000)]
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# Count occurrences of each value
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counts = Counter(samples)
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# Verify each number (1, 2, 3) appears between 300 and 400 times
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for value in [1, 2, 3]:
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assert (
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300 <= counts[value] <= 400
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), f"Value {value} appeared {counts[value]} times, expected 300-400 times"
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# Verify no other values appear in the samples
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assert set(counts.keys()) == {
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1,
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2,
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3,
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}, f"Unexpected values in samples: {set(counts.keys()) - {1, 2, 3}}"
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