Add loader test for mtp (#3724)

* add test for mtp

* fix unittest

* fix
This commit is contained in:
YuanRisheng
2025-09-01 10:55:49 +08:00
committed by GitHub
parent 085fe070f2
commit 6566e29807
2 changed files with 142 additions and 0 deletions

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"""
# 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 sys
import unittest
from unittest.mock import Mock
import numpy as np
import paddle
import paddle.distributed.fleet as fleet
from fastdeploy.model_executor.layers.embeddings import VocabParallelEmbedding
from fastdeploy.model_executor.models.ernie4_5_mtp import Ernie4_5_MTPForCausalLM
sys.path.append("../")
from utils import get_default_test_fd_config
strategy = fleet.DistributedStrategy()
fleet.init(strategy=strategy)
class TestErnie4_5_MTPLoadWeights(unittest.TestCase):
def setUp(self):
self.fd_config = get_default_test_fd_config()
self.fd_config.speculative_config = Mock()
self.fd_config.speculative_config.sharing_model = Mock()
self.fd_config.speculative_config.sharing_model.ernie = Mock()
self.fd_config.parallel_config.tp_group = None
self.fd_config.speculative_config.sharing_model.ernie.embed_tokens = VocabParallelEmbedding(
fd_config=self.fd_config,
num_embeddings=self.fd_config.model_config.vocab_size,
embedding_dim=self.fd_config.model_config.hidden_size,
params_dtype=paddle.get_default_dtype,
prefix=("embed_tokens"),
)
self.fd_config.speculative_config.sharing_model.ernie.lm_head = Mock()
self.model = Ernie4_5_MTPForCausalLM(self.fd_config)
def test_load_weights_normal_case(self):
weights_iterator = [
("ernie.embed_tokens.weight", np.random.rand(32000, 768).astype("float32")),
("ernie.mtp_block.0.self_attn.qkv_proj.weight", np.random.rand(768, 768 * 3).astype("float32")),
]
for k, v in self.model.named_parameters():
print("{}".format(k))
self.model.load_weights(iter(weights_iterator))
self.assertTrue(np.allclose(self.model.ernie.embed_tokens.embeddings.weight.numpy(), weights_iterator[0][1]))
def test_load_weights_with_unexpected_keys(self):
weights_iterator = [
("unknown_key", np.random.rand(10, 10).astype("float32")),
("ernie.embed_tokens.weight", np.random.rand(32000, 768).astype("float32")),
]
self.model.load_weights(iter(weights_iterator))
self.assertTrue(np.allclose(self.model.ernie.embed_tokens.embeddings.weight.numpy(), weights_iterator[1][1]))
def test_load_weights_empty_iterator(self):
weights_iterator = []
self.model.load_weights(iter(weights_iterator))
if __name__ == "__main__":
unittest.main()

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tests/utils.py Normal file
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"""
# 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.
"""
from unittest.mock import Mock
from fastdeploy.config import (
CacheConfig,
FDConfig,
GraphOptimizationConfig,
ParallelConfig,
)
class FakeModelConfig:
def __init__(self):
self.hidden_size = 768
self.intermediate_size = 768
self.num_hidden_layers = 12
self.num_attention_heads = 12
self.rms_norm_eps = 1e-6
self.tie_word_embeddings = True
self.ori_vocab_size = 32000
self.moe_layer_start_index = 8
self.pretrained_config = Mock()
self.pretrained_config.prefix_name = "test"
self.num_key_value_heads = 1
self.head_dim = 1
self.is_quantized = False
self.hidden_act = "relu"
self.vocab_size = 32000
self.hidden_dropout_prob = 0.1
self.initializer_range = 0.02
self.max_position_embeddings = 512
self.tie_word_embeddings = True
self.model_format = "auto"
def get_default_test_fd_config():
graph_opt_config = GraphOptimizationConfig(args={})
parallel_config = ParallelConfig(args={})
parallel_config.max_num_seqs = 1
parallel_config.data_parallel_rank = 1
cache_config = CacheConfig({})
fd_config = FDConfig(
graph_opt_config=graph_opt_config, parallel_config=parallel_config, cache_config=cache_config, test_mode=True
)
fd_config.model_config = FakeModelConfig()
return fd_config