SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Fix missing initializations for models created in 2024 (#38987)

Browse Source 
* fix GroundingDino

* fix SuperGlue

* fix GroundingDino

* fix MambaModel

* fix OmDetTurbo

* fix SegGpt

* fix Qwen2Audio

* fix Mamba2

* fix DabDetr

* fix Dac

* fix FalconMamba

* skip timm initialization

* fix Encodec and MusicgenMelody

* fix Musicgen

* skip timm initialization test

* fix OmDetTurbo

* clean the code

Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>

* add reviewed changes

* add back timm

* style

* better check for parametrizations

---------

Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
This commit is contained in:
BUI Van Tuan
2025-07-02 15:03:57 +02:00
committed by GitHub
parent 1125513a8d
commit e355c0a11c
21 changed files with 229 additions and 98 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
tests/models/mamba/test_modeling_mamba.py
View File

@@ -24,7 +24,7 @@ from transformers.testing_utils import require_torch, require_torch_multi_gpu, s
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_modeling_common import ModelTesterMixin, _config_zero_init, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin
@@ -326,9 +326,11 @@ class MambaModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixi
def test_initialization(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
config.rescale_prenorm_residual = True
configs_no_init = _config_zero_init(config)
for model_class in self.all_model_classes:
model = model_class(config=config)
model = model_class(config=configs_no_init)
for name, param in model.named_parameters():
if "dt_proj.bias" in name:
dt = torch.exp(
@@ -347,6 +349,19 @@ class MambaModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixi
if param.requires_grad:
# check if it's a ones like
torch.testing.assert_close(param.data, torch.ones_like(param.data), rtol=1e-5, atol=1e-5)
else:
if param.requires_grad:
if (
"mixer.conv1d.weight" in name
or "mixer.dt_proj.weight" in name
or "mixer.out_proj.weight" in name
):
continue
self.assertIn(
((param.data.mean() * 1e9).round() / 1e9).item(),
[0.0, 1.0],
msg=f"Parameter {name} of model {model_class} seems not properly initialized",
)
@slow
def test_model_from_pretrained(self):