Signed-off-by: Carl You <4531192+carlyou@users.noreply.github.com> Signed-off-by: Carl Y <4531192+carlyou@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -18,8 +18,11 @@ from .common import (
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from .models import (
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FLASHINFER_ATTN,
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FLASHINFER_MLA_ATTN,
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FLASHMLA_SPARSE_ATTN,
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TRITON_ATTN,
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deepseek_coder_v2_lite_fp8,
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deepseek_v3_fp8,
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deepseek_v32_fp4,
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gpt_oss_20b,
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llama3_8b,
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llama3_8b_fp4,
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@@ -37,7 +40,13 @@ pytestmark = pytest.mark.skipif(not current_platform.is_cuda(), reason="Only tes
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@pytest.mark.parametrize(
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"model_name, matches_fn, model_kwargs, hf_overrides",
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# qwen3 & dsv3 should still fuse AR+rms even though group quant is not yet supported
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[llama3_8b_fp8, llama4_scout_fp8, qwen3_a3b_fp8, deepseek_v3_fp8],
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[
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llama3_8b_fp8,
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llama4_scout_fp8,
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qwen3_a3b_fp8,
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deepseek_coder_v2_lite_fp8,
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deepseek_v3_fp8,
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],
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)
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@pytest.mark.parametrize(
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"attn_backend", [TRITON_ATTN, FLASHINFER_ATTN, FLASHINFER_MLA_ATTN]
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@@ -104,9 +113,12 @@ def test_tp2_ar_rms_fp8_fusions(
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@multi_gpu_test(num_gpus=2)
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@pytest.mark.parametrize(
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"model_name, matches_fn, model_kwargs, hf_overrides",
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[llama3_8b_fp4, llama4_scout_fp4],
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[llama3_8b_fp4, llama4_scout_fp4, deepseek_v32_fp4],
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)
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@pytest.mark.parametrize(
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"attn_backend",
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[FLASHINFER_ATTN, FLASHMLA_SPARSE_ATTN],
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)
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@pytest.mark.parametrize("attn_backend", [FLASHINFER_ATTN])
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@pytest.mark.parametrize("n_layers", [4])
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@pytest.mark.parametrize("custom_ops", custom_ops_combos("rms_norm"))
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@pytest.mark.parametrize("inductor_graph_partition", INDUCTOR_GRAPH_PARTITION)
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