[Frontend] Remove frontend pooling multi task support. (#37861)

Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io>
Signed-off-by: wang.yuqi <noooop@126.com>
Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com>
Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>

tests/entrypoints/pooling/classify/test_offline.py

@@ -1,13 +1,12 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-import logging
 import weakref
 
 import pytest
 import torch
 
 from tests.models.utils import softmax
-from vllm import LLM, ClassificationRequestOutput, PoolingParams, PoolingRequestOutput
+from vllm import LLM, ClassificationRequestOutput, PoolingParams
 from vllm.distributed import cleanup_dist_env_and_memory
 from vllm.tasks import PoolingTask
 
@@ -66,18 +65,6 @@ def test_list_prompts(llm: LLM):
         assert len(outputs[i].outputs.probs) == num_labels
 
 
-@pytest.mark.skip_global_cleanup
-def test_token_classify(llm: LLM, caplog_vllm):
-    with caplog_vllm.at_level(level=logging.WARNING, logger="vllm"):
-        outputs = llm.encode(prompt, pooling_task="token_classify", use_tqdm=False)
-        assert "deprecated" in caplog_vllm.text
-
-    assert len(outputs) == 1
-    assert isinstance(outputs[0], PoolingRequestOutput)
-    assert outputs[0].prompt_token_ids == prompt_token_ids
-    assert outputs[0].outputs.data.shape == (len(prompt_token_ids), num_labels)
-
-
 @pytest.mark.skip_global_cleanup
 def test_pooling_params(llm: LLM):
     def get_outputs(use_activation):
@@ -110,10 +97,12 @@ def test_score_api(llm: LLM):
         llm.score("ping", "pong", use_tqdm=False)
 
 
-@pytest.mark.parametrize("task", ["embed", "token_embed", "plugin"])
+@pytest.mark.parametrize("task", ["embed", "token_embed", "token_classify", "plugin"])
 def test_unsupported_tasks(llm: LLM, task: PoolingTask):
     if task == "plugin":
         err_msg = "No IOProcessor plugin installed."
+    elif task == "token_classify":
+        err_msg = "Try switching the model's pooling_task via.+"
     else:
         err_msg = "Embedding API is not supported by this model.+"
     with pytest.raises(ValueError, match=err_msg):

tests/entrypoints/pooling/classify/test_online.py

@@ -436,26 +436,7 @@ async def test_pooling_classify(server: RemoteOpenAIServer, model_name: str):
 
 @pytest.mark.asyncio
 @pytest.mark.parametrize("model_name", [MODEL_NAME])
-async def test_pooling_token_classify(server: RemoteOpenAIServer, model_name: str):
-    task = "token_classify"
-    response = requests.post(
-        server.url_for("pooling"),
-        json={
-            "model": model_name,
-            "input": input_text,
-            "encoding_format": "float",
-            "task": task,
-        },
-    )
-    poolings = PoolingResponse.model_validate(response.json())
-    assert len(poolings.data) == 1
-    assert len(poolings.data[0].data) == 8
-    assert len(poolings.data[0].data[0]) == 2
-
-
-@pytest.mark.asyncio
-@pytest.mark.parametrize("model_name", [MODEL_NAME])
-@pytest.mark.parametrize("task", ["embed", "token_embed", "plugin"])
+@pytest.mark.parametrize("task", ["embed", "token_embed", "token_classify", "plugin"])
 async def test_pooling_not_supported(
     server: RemoteOpenAIServer, model_name: str, task: str
 ):
@@ -469,8 +450,11 @@ async def test_pooling_not_supported(
         },
     )
     assert response.json()["error"]["type"] == "BadRequestError"
+
     if task == "plugin":
         err_msg = "No IOProcessor plugin installed."
+    elif task == "token_classify":
+        err_msg = "Try switching the model's pooling_task via"
     else:
         err_msg = f"Unsupported task: {task!r}"
     assert response.json()["error"]["message"].startswith(err_msg)

tests/entrypoints/pooling/embed/test_offline.py

@@ -1,6 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-import logging
 import weakref
 
 import pytest
@@ -38,11 +37,11 @@ def llm():
         seed=0,
         attention_config=attention_config,
     )
+    assert embedding_size == llm.model_config.embedding_size
 
     yield weakref.proxy(llm)
 
     del llm
-
     cleanup_dist_env_and_memory()
 
 
@@ -74,16 +73,6 @@ def test_list_prompts(llm: LLM):
         assert len(outputs[i].outputs.embedding) == embedding_size
 
 
-@pytest.mark.skip_global_cleanup
-def test_token_embed(llm: LLM, caplog_vllm):
-    with caplog_vllm.at_level(level=logging.WARNING, logger="vllm"):
-        outputs = llm.encode(prompt, pooling_task="token_embed", use_tqdm=False)
-        assert "deprecated" in caplog_vllm.text
-
-    multi_vector = outputs[0].outputs.data
-    assert multi_vector.shape == (11, 384)
-
-
 @pytest.mark.skip_global_cleanup
 def test_pooling_params(llm: LLM):
     def get_outputs(normalize):
@@ -107,10 +96,14 @@ def test_pooling_params(llm: LLM):
     )
 
 
-@pytest.mark.parametrize("task", ["token_classify", "classify", "plugin"])
+@pytest.mark.parametrize(
+    "task", ["token_classify", "classify", "token_embed", "plugin"]
+)
 def test_unsupported_tasks(llm: LLM, task: PoolingTask):
     if task == "plugin":
         err_msg = "No IOProcessor plugin installed."
+    elif task == "token_embed":
+        err_msg = "Try switching the model's pooling_task via.+"
     else:
         err_msg = "Classification API is not supported by this model.+"
     with pytest.raises(ValueError, match=err_msg):

tests/entrypoints/pooling/embed/test_online.py

@@ -732,28 +732,9 @@ async def test_pooling_embed(server: RemoteOpenAIServer, model_name: str):
 
 @pytest.mark.asyncio
 @pytest.mark.parametrize("model_name", [MODEL_NAME])
-async def test_pooling_token_embed(server: RemoteOpenAIServer, model_name: str):
-    task = "token_embed"
-    response = requests.post(
-        server.url_for("pooling"),
-        json={
-            "model": model_name,
-            "input": input_text,
-            "encoding_format": "float",
-            "task": task,
-        },
-    )
-
-    poolings = PoolingResponse.model_validate(response.json())
-
-    assert len(poolings.data) == 1
-    assert len(poolings.data[0].data) == len(input_tokens)
-    assert len(poolings.data[0].data[0]) == 384
-
-
-@pytest.mark.asyncio
-@pytest.mark.parametrize("model_name", [MODEL_NAME])
-@pytest.mark.parametrize("task", ["classify", "token_classify", "plugin"])
+@pytest.mark.parametrize(
+    "task", ["classify", "token_classify", "token_embed", "plugin"]
+)
 async def test_pooling_not_supported(
     server: RemoteOpenAIServer, model_name: str, task: str
 ):
@@ -769,6 +750,8 @@ async def test_pooling_not_supported(
     assert response.json()["error"]["type"] == "BadRequestError"
     if task == "plugin":
         err_msg = "No IOProcessor plugin installed."
+    elif task == "token_embed":
+        err_msg = "Try switching the model's pooling_task via"
     else:
         err_msg = f"Unsupported task: {task!r}"
     assert response.json()["error"]["message"].startswith(err_msg)

tests/entrypoints/pooling/scoring/test_cross_encoder_online.py

@@ -452,25 +452,6 @@ async def test_pooling_classify(server: RemoteOpenAIServer):
     assert len(poolings.data[0].data) == 1
 
 
-@pytest.mark.asyncio
-async def test_pooling_token_classify(server: RemoteOpenAIServer):
-    response = requests.post(
-        server.url_for("pooling"),
-        json={
-            "model": MODEL_NAME,
-            "task": "token_classify",
-            "input": input_text,
-            "encoding_format": "float",
-        },
-    )
-
-    poolings = PoolingResponse.model_validate(response.json())
-
-    assert len(poolings.data) == 1
-    assert len(poolings.data[0].data) == len(input_tokens)
-    assert len(poolings.data[0].data[0]) == 1
-
-
 @pytest.mark.asyncio
 async def test_rerank_max_tokens_per_doc(
     server: RemoteOpenAIServer,
@@ -544,7 +525,7 @@ async def test_rerank_max_tokens_per_doc_validation(
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize("task", ["embed", "token_embed", "plugin"])
+@pytest.mark.parametrize("task", ["embed", "token_embed", "token_classify", "plugin"])
 async def test_pooling_not_supported(server: RemoteOpenAIServer, task: str):
     response = requests.post(
         server.url_for("pooling"),
@@ -558,6 +539,8 @@ async def test_pooling_not_supported(server: RemoteOpenAIServer, task: str):
     assert response.json()["error"]["type"] == "BadRequestError"
     if task == "plugin":
         err_msg = "No IOProcessor plugin installed."
+    elif task == "token_classify":
+        err_msg = "Try switching the model's pooling_task via"
     else:
         err_msg = f"Unsupported task: {task!r}"
     assert response.json()["error"]["message"].startswith(err_msg)

tests/entrypoints/pooling/token_classify/test_offline.py

@@ -1,6 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-import logging
 import weakref
 
 import pytest
@@ -60,22 +59,19 @@ def test_token_ids_prompts(llm: LLM):
 
 @pytest.mark.skip_global_cleanup
 def test_score_api(llm: LLM):
-    err_msg = "Scoring API is only enabled for num_labels == 1."
+    err_msg = "This model does not support the Scoring API."
     with pytest.raises(ValueError, match=err_msg):
         llm.score("ping", "pong", use_tqdm=False)
 
 
 @pytest.mark.parametrize("task", ["classify", "embed", "token_embed", "plugin"])
 def test_unsupported_tasks(llm: LLM, task: PoolingTask, caplog_vllm):
-    if task == "classify":
-        with caplog_vllm.at_level(level=logging.WARNING, logger="vllm"):
-            llm.encode(prompt, pooling_task=task, use_tqdm=False)
-        assert "deprecated" in caplog_vllm.text
+    if task == "plugin":
+        err_msg = "No IOProcessor plugin installed."
+    elif task == "classify":
+        err_msg = "Try switching the model's pooling_task via.+"
     else:
-        if task == "plugin":
-            err_msg = "No IOProcessor plugin installed."
-        else:
-            err_msg = "Embedding API is not supported by this model.+"
+        err_msg = "Embedding API is not supported by this model.+"
 
-        with pytest.raises(ValueError, match=err_msg):
-            llm.encode(prompt, pooling_task=task, use_tqdm=False)
+    with pytest.raises(ValueError, match=err_msg):
+        llm.encode(prompt, pooling_task=task, use_tqdm=False)

tests/entrypoints/pooling/token_classify/test_online.py

@@ -50,7 +50,7 @@ async def test_pooling_token_classify(server: RemoteOpenAIServer, model_name: st
 
 @pytest.mark.asyncio
 @pytest.mark.parametrize("model_name", [MODEL_NAME])
-@pytest.mark.parametrize("task", ["embed", "token_embed", "plugin"])
+@pytest.mark.parametrize("task", ["classify", "embed", "token_embed", "plugin"])
 async def test_pooling_not_supported(
     server: RemoteOpenAIServer, model_name: str, task: str
 ):
@@ -63,9 +63,12 @@ async def test_pooling_not_supported(
             "task": task,
         },
     )
+    assert response.json()["error"]["type"] == "BadRequestError"
 
     if task == "plugin":
         err_msg = "No IOProcessor plugin installed."
+    elif task == "classify":
+        err_msg = "Try switching the model's pooling_task via"
     else:
         err_msg = f"Unsupported task: {task!r}"
     assert response.json()["error"]["message"].startswith(err_msg)

tests/entrypoints/pooling/token_embed/test_offline.py

@@ -1,6 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-import logging
 import weakref
 
 import pytest
@@ -64,15 +63,12 @@ def test_token_ids_prompts(llm: LLM):
 
 @pytest.mark.parametrize("task", ["embed", "classify", "token_classify", "plugin"])
 def test_unsupported_tasks(llm: LLM, task: PoolingTask, caplog_vllm):
-    if task == "embed":
-        with caplog_vllm.at_level(level=logging.WARNING, logger="vllm"):
-            llm.encode(prompt, pooling_task=task, use_tqdm=False)
-        assert "deprecated" in caplog_vllm.text
+    if task == "plugin":
+        err_msg = "No IOProcessor plugin installed."
+    elif task == "embed":
+        err_msg = "Try switching the model's pooling_task via.+"
     else:
-        if task == "plugin":
-            err_msg = "No IOProcessor plugin installed."
-        else:
-            err_msg = "Classification API is not supported by this model.+"
+        err_msg = "Classification API is not supported by this model.+"
 
-        with pytest.raises(ValueError, match=err_msg):
-            llm.encode(prompt, pooling_task=task, use_tqdm=False)
+    with pytest.raises(ValueError, match=err_msg):
+        llm.encode(prompt, pooling_task=task, use_tqdm=False)

tests/entrypoints/pooling/token_embed/test_online.py

@@ -73,7 +73,7 @@ async def test_pooling_token_embed(server: RemoteOpenAIServer, model_name: str):
 
 @pytest.mark.asyncio
 @pytest.mark.parametrize("model_name", [MODEL_NAME])
-@pytest.mark.parametrize("task", ["classify", "token_classify", "plugin"])
+@pytest.mark.parametrize("task", ["embed", "classify", "token_classify", "plugin"])
 async def test_pooling_not_supported(
     server: RemoteOpenAIServer, model_name: str, task: str
 ):
@@ -86,9 +86,12 @@ async def test_pooling_not_supported(
             "task": task,
         },
     )
+    assert response.json()["error"]["type"] == "BadRequestError"
 
     if task == "plugin":
         err_msg = "No IOProcessor plugin installed."
+    elif task == "embed":
+        err_msg = "Try switching the model's pooling_task via"
     else:
         err_msg = f"Unsupported task: {task!r}"
     assert response.json()["error"]["message"].startswith(err_msg)