EngineX-Ascend/enginex-ascend-910-vllm
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init v0.11.0rc0

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This commit is contained in:
luopingyi
2025-10-14 10:38:28 +08:00
parent 67afd0ea78
commit 66dc16f966
278 changed files with 28130 additions and 11708 deletions
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56
tests/ut/models/test_qwen2_5_vl.py
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@@ -286,6 +286,22 @@ class TestAscendQwen2_5_VisionTransformer(PytestBase):
"vllm_ascend.models.qwen2_5_vl.parallel_state.get_tensor_model_parallel_world_size",
return_value=2,
)
mocker.patch(
"vllm_ascend.ops.linear.divide",
return_value=2,
)
mock_group = mocker.MagicMock()
mock_group.rank_in_group = 0
mock_group.world_size = 2
mocker.patch(
"vllm_ascend.ops.linear_op.get_tp_group",
return_value=mock_group,
)
mocker.patch(
"vllm.distributed.parallel_state.get_tp_group",
return_value=mock_group,
)
vision_transformer = AscendQwen2_5_VisionTransformer(
vision_config,
@@ -341,6 +357,46 @@ class TestAscendQwen2_5_VisionTransformer(PytestBase):
cos_new, _ = vision_transformer.cal_cos_sin(self.input_data)
assert cos_new.shape == (1, 32, 1, 2)
def test_pad_qkv_bias(self, mocker: MockerFixture):
attention = self.init_vision_transformer(mocker)
mocker.patch("torch.nn.Module.__setattr__")
mocker.patch("torch.nn.Module.__getattr__")
mocker.patch("torch.nn.Module.__delattr__")
res = attention.pad_qkv_bias(torch.rand((300)))
assert res.shape[0] == 384
def test_pad_qkv_weight(self, mocker: MockerFixture):
attention = self.init_vision_transformer(mocker)
mocker.patch("torch.nn.Module.__setattr__")
mocker.patch("torch.nn.Module.__getattr__")
mocker.patch("torch.nn.Module.__delattr__")
res = attention.pad_qkv_weight(torch.rand((300, 300)))
assert res.shape == (384, 300)
def test_pad_proj_weight(self, mocker: MockerFixture):
attention = self.init_vision_transformer(mocker)
mocker.patch("torch.nn.Module.__setattr__")
mocker.patch("torch.nn.Module.__getattr__")
mocker.patch("torch.nn.Module.__delattr__")
res = attention.pad_proj_weight(torch.rand((300, 300)))
assert res.shape == (300, 384)
def test_pad_qkv_weight_scale_offset(self, mocker: MockerFixture):
attention = self.init_vision_transformer(mocker)
mocker.patch("torch.nn.Module.__setattr__")
mocker.patch("torch.nn.Module.__getattr__")
mocker.patch("torch.nn.Module.__delattr__")
res = attention.pad_qkv_weight_scale_offset(torch.rand((300, 1)))
assert res.shape == (384, 1)
def test_pad_qkv_deq_scale_quant_bias(self, mocker: MockerFixture):
attention = self.init_vision_transformer(mocker)
mocker.patch("torch.nn.Module.__setattr__")
mocker.patch("torch.nn.Module.__getattr__")
mocker.patch("torch.nn.Module.__delattr__")
res = attention.pad_qkv_deq_scale_quant_bias(torch.rand((300)))
assert res.shape[0] == 384
def test_forward(self, mocker: MockerFixture):
vision_transformer = self.init_vision_transformer(mocker)
mocker.patch("torch.nn.Module.__setattr__")