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[CI/Build] Fix and re-enable v1 PP test on CI (#25496)

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Signed-off-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Signed-off-by: yewentao256 <zhyanwentao@126.com>
This commit is contained in:
Isotr0py 2025-09-24 05:58:25 +08:00 committed by yewentao256
parent c0f11557e1
commit 930e691c65
4 changed files with 0 additions and 24 deletions
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3
tests/distributed/test_pipeline_parallel.py
View File

@ -382,7 +382,6 @@ def test_tp_language_generation(
test_options: PPTestOptions,
num_gpus_available,
):
pytest.skip("Skipping the test until V1 passes it.")
_compare_tp(model_id,
parallel_setup,
distributed_backend,
@ -410,7 +409,6 @@ def test_tp_language_embedding(
test_options: PPTestOptions,
num_gpus_available,
):
pytest.skip("Skipping the test until V1 passes it.")
_compare_tp(model_id,
parallel_setup,
distributed_backend,
@ -438,7 +436,6 @@ def test_tp_multimodal_generation(
test_options: PPTestOptions,
num_gpus_available,
):
pytest.skip("Skipping the test until V1 passes it.")
_compare_tp(model_id,
parallel_setup,
distributed_backend,

7
vllm/model_executor/models/granite.py
View File

@ -308,13 +308,11 @@ class GraniteModel(nn.Module):
hidden_states = inputs_embeds
else:
hidden_states = self.get_input_embeddings(input_ids)
residual = None
hidden_states *= self.config.embedding_multiplier
else:
assert intermediate_tensors is not None
hidden_states = intermediate_tensors["hidden_states"]
residual = intermediate_tensors["residual"]
for layer in islice(self.layers, self.start_layer, self.end_layer):
hidden_states = layer(positions, hidden_states)
@ -322,7 +320,6 @@ class GraniteModel(nn.Module):
if not get_pp_group().is_last_rank:
return IntermediateTensors({
"hidden_states": hidden_states,
"residual": residual
})
hidden_states = self.norm(hidden_states)
@ -475,10 +472,6 @@ class GraniteForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
torch.zeros((batch_size, self.config.hidden_size),
dtype=dtype,
device=device),
"residual":
torch.zeros((batch_size, self.config.hidden_size),
dtype=dtype,
device=device),
})
def load_weights(self, weights: Iterable[tuple[str,

7
vllm/model_executor/models/granitemoe.py
View File

@ -298,17 +298,14 @@ class GraniteMoeModel(nn.Module):
else:
hidden_states = self.get_input_embeddings(input_ids)
hidden_states *= self.embedding_multiplier
residual = None
else:
assert intermediate_tensors is not None
hidden_states = intermediate_tensors["hidden_states"]
residual = intermediate_tensors["residual"]
for layer in islice(self.layers, self.start_layer, self.end_layer):
hidden_states = layer(positions, hidden_states)
if not get_pp_group().is_last_rank:
return IntermediateTensors({
"hidden_states": hidden_states,
"residual": residual
})
hidden_states = self.norm(hidden_states)
return hidden_states
@ -523,10 +520,6 @@ class GraniteMoeForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
torch.zeros((batch_size, self.config.hidden_size),
dtype=dtype,
device=device),
"residual":
torch.zeros((batch_size, self.config.hidden_size),
dtype=dtype,
device=device),
})
def load_weights(self, weights: Iterable[tuple[str,

7
vllm/model_executor/models/granitemoeshared.py
View File

@ -195,17 +195,14 @@ class GraniteMoeSharedModel(nn.Module):
else:
hidden_states = self.get_input_embeddings(input_ids)
hidden_states *= self.embedding_multiplier
residual = None
else:
assert intermediate_tensors is not None
hidden_states = intermediate_tensors["hidden_states"]
residual = intermediate_tensors["residual"]
for layer in islice(self.layers, self.start_layer, self.end_layer):
hidden_states = layer(positions, hidden_states)
if not get_pp_group().is_last_rank:
return IntermediateTensors({
"hidden_states": hidden_states,
"residual": residual
})
hidden_states = self.norm(hidden_states)
return hidden_states
@ -323,10 +320,6 @@ class GraniteMoeSharedForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
torch.zeros((batch_size, self.config.hidden_size),
dtype=dtype,
device=device),
"residual":
torch.zeros((batch_size, self.config.hidden_size),
dtype=dtype,
device=device),
})
def load_weights(self, weights: Iterable[tuple[str,