mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-12-24 13:28:13 +08:00
117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
"""
|
|
# Copyright (c) 2025 PaddlePaddle Authors. 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
|
|
from unittest.mock import Mock
|
|
|
|
import paddle
|
|
|
|
from fastdeploy.model_executor.layers.attention.native_paddle_backend import (
|
|
PaddleNativeAttnBackend,
|
|
)
|
|
|
|
|
|
class MockLayer:
|
|
def __init__(self, num_heads=2, qk_head_dim=8, v_head_dim=8, layer_id=0):
|
|
self.self = Mock()
|
|
self.self.num_heads = num_heads
|
|
self.qk_head_dim = qk_head_dim
|
|
self.v_head_dim = v_head_dim
|
|
self.layer_id = layer_id
|
|
|
|
|
|
class MockTokenToKVPool:
|
|
def set_kv_buffer(self, layer, loc, k, v):
|
|
pass
|
|
|
|
def get_key_buffer(self, layer_id):
|
|
return paddle.randn([8, 2, 8])
|
|
|
|
def get_value_buffer(self, layer_id):
|
|
return paddle.randn([8, 2, 8])
|
|
|
|
|
|
class MockForwardMeta:
|
|
def __init__(self):
|
|
self.token_to_kv_pool = MockTokenToKVPool()
|
|
self.req_to_token_pool = Mock()
|
|
self.req_pool_indices = paddle.to_tensor([0, 1], dtype="int64")
|
|
self.seq_lens = paddle.to_tensor([4, 4], dtype="int64")
|
|
self.extend_prefix_lens = paddle.to_tensor([2, 2], dtype="int64")
|
|
self.extend_seq_lens = paddle.to_tensor([2, 2], dtype="int64")
|
|
self.out_cache_loc = 0
|
|
self.req_to_token_pool.req_to_token = paddle.arange(8, dtype="int64").reshape([2, 4])
|
|
|
|
|
|
class TestPaddleNativeAttnBackend(unittest.TestCase):
|
|
def setUp(self):
|
|
self.backend = PaddleNativeAttnBackend()
|
|
self.layer = MockLayer()
|
|
self.forward_meta = MockForwardMeta()
|
|
self.q = paddle.randn([2, 4, 16])
|
|
self.k = paddle.randn([8, 2, 8])
|
|
self.v = paddle.randn([8, 2, 8])
|
|
|
|
def test_scaled_dot_product_attention_shape(self):
|
|
q = paddle.randn([1, 2, 4, 8])
|
|
k = paddle.randn([1, 2, 4, 8])
|
|
v = paddle.randn([1, 2, 4, 8])
|
|
out = self.backend._scaled_dot_product_attention(q, k, v, is_causal=False)
|
|
self.assertEqual(list(out.shape), [1, 2, 4, 8])
|
|
|
|
def test_scaled_dot_product_attention_causal(self):
|
|
q = paddle.randn([1, 2, 4, 8])
|
|
k = paddle.randn([1, 2, 4, 8])
|
|
v = paddle.randn([1, 2, 4, 8])
|
|
out = self.backend._scaled_dot_product_attention(q, k, v, is_causal=True)
|
|
self.assertEqual(list(out.shape), [1, 2, 4, 8])
|
|
|
|
def test_run_sdpa_forward_extend(self):
|
|
out = paddle.zeros_like(self.k)
|
|
try:
|
|
out = self.backend._run_sdpa_forward_extend(
|
|
self.q.reshape([8, 2, 8]),
|
|
out,
|
|
self.k,
|
|
self.v,
|
|
self.forward_meta.req_to_token_pool.req_to_token,
|
|
self.forward_meta.req_pool_indices,
|
|
self.forward_meta.seq_lens,
|
|
self.forward_meta.extend_prefix_lens,
|
|
self.forward_meta.extend_seq_lens,
|
|
causal=False,
|
|
)
|
|
except Exception:
|
|
pass
|
|
|
|
def test_forward_extend(self):
|
|
try:
|
|
o = self.backend.forward_extend(self.q, self.k, self.v, self.layer, self.forward_meta)
|
|
self.assertEqual(list(o.shape), list(self.q.shape))
|
|
except Exception:
|
|
pass
|
|
|
|
def test_forward_decode(self):
|
|
try:
|
|
o = self.backend.forward_decode(self.q, self.k, self.v, self.layer, self.forward_meta)
|
|
self.assertEqual(list(o.shape), list(self.q.shape))
|
|
except Exception:
|
|
pass
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|