mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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77 lines
3.2 KiB
Python
77 lines
3.2 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. 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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"""
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import unittest
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from fastdeploy.engine.kv_cache_interface import AttentionSpec, KVCacheSpec
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class TestKVCacheSpec(unittest.TestCase):
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def test_merge_valid(self):
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# Create two valid KVCacheSpec objects with the same block_size and block_memory_used
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spec1 = KVCacheSpec(block_size=256, block_memory_used=1024)
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spec2 = KVCacheSpec(block_size=256, block_memory_used=1024)
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merged_spec = KVCacheSpec.merge([spec1, spec2])
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self.assertEqual(merged_spec.block_size, spec1.block_size)
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self.assertEqual(merged_spec.block_memory_used, spec1.block_memory_used)
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def test_merge_invalid(self):
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spec1 = KVCacheSpec(block_size=256, block_memory_used=1024)
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spec2 = KVCacheSpec(block_size=512, block_memory_used=1024)
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with self.assertRaises(AssertionError):
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KVCacheSpec.merge([spec1, spec2])
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def test_attention_spec_inheritance(self):
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# Create an AttentionSpec object
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attention_spec = AttentionSpec(
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block_size=256, block_memory_used=1024, num_kv_heads=12, head_size=64, dtype="float32"
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)
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self.assertEqual(attention_spec.block_size, 256)
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self.assertEqual(attention_spec.block_memory_used, 1024)
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self.assertEqual(attention_spec.num_kv_heads, 12)
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self.assertEqual(attention_spec.head_size, 64)
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self.assertEqual(attention_spec.dtype, "float32")
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def test_attention_spec_merge(self):
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# Create two AttentionSpec objects with the same attributes
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spec1 = AttentionSpec(block_size=256, block_memory_used=1024, num_kv_heads=12, head_size=64, dtype="float32")
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spec2 = AttentionSpec(block_size=256, block_memory_used=1024, num_kv_heads=12, head_size=64, dtype="float32")
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merged_spec = AttentionSpec.merge([spec1, spec2])
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self.assertEqual(merged_spec.block_size, spec1.block_size)
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self.assertEqual(merged_spec.block_memory_used, spec1.block_memory_used)
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self.assertEqual(merged_spec.num_kv_heads, spec1.num_kv_heads)
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self.assertEqual(merged_spec.head_size, spec1.head_size)
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self.assertEqual(merged_spec.dtype, spec1.dtype)
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def test_attention_spec_merge_invalid(self):
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# Create two AttentionSpec objects with different attributes
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spec1 = AttentionSpec(block_size=256, block_memory_used=1024, num_kv_heads=12, head_size=64, dtype="float32")
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spec2 = AttentionSpec(block_size=512, block_memory_used=1024, num_kv_heads=12, head_size=64, dtype="float32")
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with self.assertRaises(AssertionError):
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AttentionSpec.merge([spec1, spec2])
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if __name__ == "__main__":
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unittest.main()
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