2024-05-27 15:18:17 -07:00
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import pytest
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2024-03-15 04:56:57 +08:00
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from vllm.config import ModelConfig
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2024-10-19 02:31:58 +08:00
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@pytest.mark.parametrize(("model_id", "expected_task"), [
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("facebook/opt-125m", "generate"),
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("intfloat/e5-mistral-7b-instruct", "embedding"),
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])
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def test_auto_task(model_id, expected_task):
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config = ModelConfig(
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model_id,
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task="auto",
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tokenizer=model_id,
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tokenizer_mode="auto",
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trust_remote_code=False,
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seed=0,
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dtype="float16",
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)
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assert config.task == expected_task
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@pytest.mark.parametrize(("model_id", "bad_task"), [
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("facebook/opt-125m", "embedding"),
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("intfloat/e5-mistral-7b-instruct", "generate"),
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])
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def test_incorrect_task(model_id, bad_task):
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with pytest.raises(ValueError, match=r"does not support the .* task"):
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ModelConfig(
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model_id,
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task=bad_task,
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tokenizer=model_id,
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tokenizer_mode="auto",
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trust_remote_code=False,
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seed=0,
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dtype="float16",
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)
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2024-05-27 15:18:17 -07:00
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MODEL_IDS_EXPECTED = [
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("Qwen/Qwen1.5-7B", 32768),
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("mistralai/Mistral-7B-v0.1", 4096),
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("mistralai/Mistral-7B-Instruct-v0.2", 32768),
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]
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@pytest.mark.parametrize("model_id_expected", MODEL_IDS_EXPECTED)
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def test_disable_sliding_window(model_id_expected):
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model_id, expected = model_id_expected
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model_config = ModelConfig(
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model_id,
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2024-10-19 02:31:58 +08:00
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task="auto",
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tokenizer=model_id,
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2024-05-27 15:18:17 -07:00
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tokenizer_mode="auto",
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trust_remote_code=False,
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seed=0,
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dtype="float16",
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revision=None,
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disable_sliding_window=True,
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)
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assert model_config.max_model_len == expected
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2024-03-15 04:56:57 +08:00
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def test_get_sliding_window():
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TEST_SLIDING_WINDOW = 4096
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# Test that the sliding window is correctly computed.
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# For Qwen1.5/Qwen2, get_sliding_window() should be None
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# when use_sliding_window is False.
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qwen2_model_config = ModelConfig(
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"Qwen/Qwen1.5-7B",
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2024-10-19 02:31:58 +08:00
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task="auto",
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tokenizer="Qwen/Qwen1.5-7B",
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2024-03-15 04:56:57 +08:00
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tokenizer_mode="auto",
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trust_remote_code=False,
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seed=0,
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dtype="float16",
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revision=None,
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)
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qwen2_model_config.hf_config.use_sliding_window = False
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qwen2_model_config.hf_config.sliding_window = TEST_SLIDING_WINDOW
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assert qwen2_model_config.get_sliding_window() is None
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qwen2_model_config.hf_config.use_sliding_window = True
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assert qwen2_model_config.get_sliding_window() == TEST_SLIDING_WINDOW
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mistral_model_config = ModelConfig(
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"mistralai/Mistral-7B-v0.1",
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2024-10-19 02:31:58 +08:00
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task="auto",
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tokenizer="mistralai/Mistral-7B-v0.1",
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2024-03-15 04:56:57 +08:00
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tokenizer_mode="auto",
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trust_remote_code=False,
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seed=0,
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dtype="float16",
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revision=None,
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)
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mistral_model_config.hf_config.sliding_window = None
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assert mistral_model_config.get_sliding_window() is None
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mistral_model_config.hf_config.sliding_window = TEST_SLIDING_WINDOW
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2024-05-22 05:32:35 +00:00
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assert mistral_model_config.get_sliding_window() == TEST_SLIDING_WINDOW
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2024-06-11 17:42:26 +00:00
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def test_rope_customization():
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2024-10-16 13:56:17 +08:00
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TEST_ROPE_SCALING = {"rope_type": "dynamic", "factor": 2.0}
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2024-06-11 17:42:26 +00:00
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TEST_ROPE_THETA = 16_000_000.0
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2024-10-16 13:56:17 +08:00
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LONGCHAT_ROPE_SCALING = {"rope_type": "linear", "factor": 8.0}
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2024-05-22 05:32:35 +00:00
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llama_model_config = ModelConfig(
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"meta-llama/Meta-Llama-3-8B-Instruct",
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2024-10-19 02:31:58 +08:00
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task="auto",
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tokenizer="meta-llama/Meta-Llama-3-8B-Instruct",
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2024-05-22 05:32:35 +00:00
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tokenizer_mode="auto",
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trust_remote_code=False,
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dtype="float16",
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seed=0,
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)
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assert getattr(llama_model_config.hf_config, "rope_scaling", None) is None
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2024-06-11 17:42:26 +00:00
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assert getattr(llama_model_config.hf_config, "rope_theta", None) == 500_000
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2024-05-22 05:32:35 +00:00
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assert llama_model_config.max_model_len == 8192
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llama_model_config = ModelConfig(
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"meta-llama/Meta-Llama-3-8B-Instruct",
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2024-10-19 02:31:58 +08:00
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task="auto",
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tokenizer="meta-llama/Meta-Llama-3-8B-Instruct",
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2024-05-22 05:32:35 +00:00
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tokenizer_mode="auto",
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trust_remote_code=False,
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dtype="float16",
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seed=0,
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rope_scaling=TEST_ROPE_SCALING,
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2024-06-11 17:42:26 +00:00
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rope_theta=TEST_ROPE_THETA,
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2024-05-22 05:32:35 +00:00
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)
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assert getattr(llama_model_config.hf_config, "rope_scaling",
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None) == TEST_ROPE_SCALING
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2024-06-11 17:42:26 +00:00
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assert getattr(llama_model_config.hf_config, "rope_theta",
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None) == TEST_ROPE_THETA
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2024-05-22 05:32:35 +00:00
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assert llama_model_config.max_model_len == 16384
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2024-07-24 16:22:16 -04:00
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longchat_model_config = ModelConfig(
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"lmsys/longchat-13b-16k",
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2024-10-19 02:31:58 +08:00
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task="auto",
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tokenizer="lmsys/longchat-13b-16k",
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2024-07-24 16:22:16 -04:00
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tokenizer_mode="auto",
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trust_remote_code=False,
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dtype="float16",
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seed=0,
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)
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# Check if LONGCHAT_ROPE_SCALING entries are in longchat_model_config
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assert all(
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longchat_model_config.hf_config.rope_scaling.get(key) == value
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for key, value in LONGCHAT_ROPE_SCALING.items())
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assert longchat_model_config.max_model_len == 16384
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longchat_model_config = ModelConfig(
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"lmsys/longchat-13b-16k",
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2024-10-19 02:31:58 +08:00
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task="auto",
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tokenizer="lmsys/longchat-13b-16k",
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2024-07-24 16:22:16 -04:00
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tokenizer_mode="auto",
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trust_remote_code=False,
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dtype="float16",
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seed=0,
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rope_scaling=TEST_ROPE_SCALING,
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)
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assert getattr(longchat_model_config.hf_config, "rope_scaling",
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None) == TEST_ROPE_SCALING
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assert longchat_model_config.max_model_len == 4096
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2024-11-07 14:00:21 +08:00
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@pytest.mark.parametrize(("model_id", "is_encoder_decoder"), [
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("facebook/opt-125m", False),
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("facebook/bart-base", True),
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("meta-llama/Llama-3.2-1B", False),
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("meta-llama/Llama-3.2-11B-Vision", True),
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])
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def test_is_encoder_decoder(model_id, is_encoder_decoder):
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config = ModelConfig(
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model_id,
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task="auto",
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tokenizer=model_id,
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tokenizer_mode="auto",
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trust_remote_code=False,
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dtype="float16",
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seed=0,
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)
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assert config.is_encoder_decoder == is_encoder_decoder
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@pytest.mark.parametrize(("model_id", "uses_mrope"), [
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("facebook/opt-125m", False),
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("Qwen/Qwen2-VL-2B-Instruct", True),
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])
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def test_uses_mrope(model_id, uses_mrope):
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config = ModelConfig(
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model_id,
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task="auto",
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tokenizer=model_id,
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tokenizer_mode="auto",
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trust_remote_code=False,
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dtype="float16",
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seed=0,
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)
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assert config.uses_mrope == uses_mrope
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