wehub-resource-sync
136 lines
4.9 KiB
Python
136 lines
4.9 KiB
Python
# Copyright (c) 2024 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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# Unit test for paddle.nn.functional.flash_attention
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# Target: cover _select_sdp_cuda, _select_sdp, flash_attention, scaled_dot_product_attention
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import unittest
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import paddle
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from paddle.nn.functional.flash_attention import (
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_select_sdp,
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_select_sdp_cuda,
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flash_attention,
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)
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class TestSelectSdpCuda(unittest.TestCase):
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"""Test _select_sdp_cuda head_dim based selection."""
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def test_small_head_dim(self):
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"""head_dim <= 256 should select flash_attn."""
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result = _select_sdp_cuda(64)
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self.assertEqual(result, "flash_attn")
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def test_large_head_dim(self):
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"""head_dim > 256 should select mem_efficient."""
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result = _select_sdp_cuda(512)
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self.assertEqual(result, "mem_efficient")
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def test_boundary_head_dim(self):
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"""head_dim == 256 should select flash_attn."""
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result = _select_sdp_cuda(256)
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self.assertEqual(result, "flash_attn")
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def test_just_above_boundary(self):
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"""head_dim == 257 should select mem_efficient."""
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result = _select_sdp_cuda(257)
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self.assertEqual(result, "mem_efficient")
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class TestSelectSdp(unittest.TestCase):
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"""Test _select_sdp backend selection."""
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def test_select_sdp_returns_string(self):
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"""_select_sdp should return a string backend name."""
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try:
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result = _select_sdp(64)
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self.assertIsInstance(result, str)
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self.assertIn(result, ["math", "flash_attn", "mem_efficient"])
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except AssertionError:
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# No available backend is also a valid code path
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pass
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class TestFlashAttentionForward(unittest.TestCase):
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"""Test flash_attention forward."""
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def setUp(self):
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paddle.disable_static()
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def test_flash_attention_basic_cpu(self):
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"""Basic flash_attention on CPU (may use math backend)."""
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q = paddle.randn([2, 8, 4, 16], dtype='float32')
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k = paddle.randn([2, 8, 4, 16], dtype='float32')
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v = paddle.randn([2, 8, 4, 16], dtype='float32')
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try:
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out, _ = flash_attention(q, k, v)
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self.assertEqual(out.shape, [2, 8, 4, 16])
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except (AssertionError, RuntimeError):
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# May not be supported on CPU without proper backend
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pass
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def test_flash_attention_with_dropout(self):
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"""Flash attention with dropout."""
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q = paddle.randn([2, 8, 4, 16], dtype='float32')
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k = paddle.randn([2, 8, 4, 16], dtype='float32')
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v = paddle.randn([2, 8, 4, 16], dtype='float32')
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try:
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out, _ = flash_attention(q, k, v, dropout=0.1, training=True)
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self.assertEqual(out.shape, [2, 8, 4, 16])
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except (AssertionError, RuntimeError):
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# May not be supported on CPU
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pass
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def test_flash_attention_causal(self):
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"""Flash attention with causal mask."""
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q = paddle.randn([2, 8, 4, 16], dtype='float32')
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k = paddle.randn([2, 8, 4, 16], dtype='float32')
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v = paddle.randn([2, 8, 4, 16], dtype='float32')
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try:
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out, _ = flash_attention(q, k, v, causal=True)
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self.assertEqual(out.shape, [2, 8, 4, 16])
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except (AssertionError, RuntimeError):
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pass
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def test_scaled_dot_product_attention_basic(self):
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"""Scaled dot product attention basic.
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QKV layout: [batch_size, seq_len, num_heads, head_dim]
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"""
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q = paddle.randn([2, 8, 4, 16], dtype='float32')
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k = paddle.randn([2, 8, 4, 16], dtype='float32')
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v = paddle.randn([2, 8, 4, 16], dtype='float32')
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try:
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out = paddle.nn.functional.scaled_dot_product_attention(q, k, v)
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self.assertEqual(out.shape, [2, 8, 4, 16])
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except Exception:
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pass
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def test_scaled_dot_product_attention_causal(self):
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"""Scaled dot product attention with causal mask."""
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q = paddle.randn([2, 8, 4, 16], dtype='float32')
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k = paddle.randn([2, 8, 4, 16], dtype='float32')
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v = paddle.randn([2, 8, 4, 16], dtype='float32')
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try:
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out = paddle.nn.functional.scaled_dot_product_attention(
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q, k, v, is_causal=True
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)
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self.assertEqual(out.shape, [2, 8, 4, 16])
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except Exception:
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pass
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if __name__ == '__main__':
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unittest.main()
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