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Merge branch 'upgrade-transformers' of github.com:flybird11111/ColossalAI into upgrade-transformers

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flybird11111 2025-04-10 12:57:46 +08:00
commit 5c56a7fd7b
1 changed files with 3 additions and 1 deletions
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4
tests/test_infer/test_kernels/cuda/test_flash_decoding_attention.py
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@ -11,6 +11,7 @@ from tests.test_infer.test_kernels.triton.test_context_attn_unpad import generat
inference_ops = InferenceOpsLoader().load() inference_ops = InferenceOpsLoader().load()
from colossalai.testing import clear_cache_before_run
from tests.test_infer.test_kernels.triton.kernel_utils import ( from tests.test_infer.test_kernels.triton.kernel_utils import (
convert_kv_unpad_to_padded, convert_kv_unpad_to_padded,
create_attention_mask, create_attention_mask,
@ -18,7 +19,6 @@ from tests.test_infer.test_kernels.triton.kernel_utils import (
generate_caches_and_block_tables_vllm, generate_caches_and_block_tables_vllm,
torch_attn_ref, torch_attn_ref,
) )
from colossalai.testing import clear_cache_before_run
q_len = 1 q_len = 1
PARTITION_SIZE = 512 PARTITION_SIZE = 512
@ -56,6 +56,7 @@ def numpy_allclose(x, y, rtol, atol):
np.testing.assert_allclose(x_numpy, y_numpy, rtol=rtol, atol=atol) np.testing.assert_allclose(x_numpy, y_numpy, rtol=rtol, atol=atol)
@clear_cache_before_run() @clear_cache_before_run()
@pytest.mark.parametrize("BATCH_SIZE", [1, 4, 7, 32]) @pytest.mark.parametrize("BATCH_SIZE", [1, 4, 7, 32])
@pytest.mark.parametrize("BLOCK_SIZE", [8, 16, 32]) @pytest.mark.parametrize("BLOCK_SIZE", [8, 16, 32])
@ -197,6 +198,7 @@ except ImportError:
HAS_VLLM = False HAS_VLLM = False
print("The subsequent test requires vllm. Please refer to https://github.com/vllm-project/vllm") print("The subsequent test requires vllm. Please refer to https://github.com/vllm-project/vllm")
@clear_cache_before_run() @clear_cache_before_run()
@pytest.mark.skipif(not HAS_VLLM, reason="requires vllm") @pytest.mark.skipif(not HAS_VLLM, reason="requires vllm")
@pytest.mark.parametrize("BATCH_SIZE", [1, 7, 32]) @pytest.mark.parametrize("BATCH_SIZE", [1, 7, 32])