wehub-resource-sync
77 lines
2.5 KiB
Python
77 lines
2.5 KiB
Python
# 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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import unittest
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import paddle
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class TestEmbeddingGrad(unittest.TestCase):
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"""Test case for comparing embedding gradient implementations"""
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def setUp(self):
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"""Initialize test data before each test"""
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self.vocab_size = 129280
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self.hidden_size = 7168
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self.seq_length = 4096
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# Set random seed for reproducibility
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paddle.seed(42)
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# Initialize test tensors
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self.embedding = paddle.uniform(
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[self.vocab_size, self.hidden_size], dtype=paddle.bfloat16
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)
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self.main_grad = paddle.uniform(
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[self.vocab_size, self.hidden_size], dtype=paddle.float32
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)
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self.dw = paddle.uniform(
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[self.seq_length, self.hidden_size], dtype=paddle.bfloat16
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)
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self.x = paddle.uniform(
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[self.seq_length], min=0, max=self.vocab_size, dtype=paddle.float32
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).cast(paddle.int32)
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def test_embedding_grad_equivalence(self):
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"""Test if reference and fused implementations produce same results"""
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# Reference implementation
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ref_out = self.main_grad.detach().clone()
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d_embedding = paddle._C_ops.embedding_grad(
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self.x, self.embedding, self.dw, -1, False
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)
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ref_out.add_(d_embedding)
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# Fused implementation
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fused_out = self.main_grad.detach().clone()
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paddle.incubate.nn.functional.embedding_grad_add_to_(
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self.x, fused_out, self.dw
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)
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# Compare results
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# Bypassed because result is non-deterministic, and current implementation
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# is using higher precision (float32)
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'''
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np.testing.assert_allclose(
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ref_out.numpy(),
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fused_out.numpy(),
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rtol=1e-5,
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atol=1e-8,
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err_msg="Reference and fused implementations differ"
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)
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'''
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if __name__ == '__main__':
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unittest.main()
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