chore: bump flashinfer version to 0.6.7 (#21422)
Co-authored-by: sglang-bot <sglang-bot@users.noreply.github.com> Co-authored-by: Baizhou Zhang <sobereddiezhang@gmail.com>
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sglang-bot
Baizhou Zhang
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03a87068ea
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ca3ba05a7a
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@@ -19,7 +19,7 @@ ARG PIP_DEFAULT_INDEX
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ARG UBUNTU_MIRROR
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ARG UBUNTU_MIRROR
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ARG GITHUB_ARTIFACTORY=github.com
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ARG GITHUB_ARTIFACTORY=github.com
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ARG INSTALL_FLASHINFER_JIT_CACHE=0
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ARG INSTALL_FLASHINFER_JIT_CACHE=0
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ARG FLASHINFER_VERSION=0.6.6
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ARG FLASHINFER_VERSION=0.6.7
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ARG MOONCAKE_VERSION=0.3.9
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ARG MOONCAKE_VERSION=0.3.9
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#if need other arg please add in MOONCAKE_COMPILE_ARG
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#if need other arg please add in MOONCAKE_COMPILE_ARG
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ARG MOONCAKE_COMPILE_ARG="-DUSE_HTTP=ON -DUSE_MNNVL=ON -DUSE_CUDA=ON -DWITH_EP=ON"
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ARG MOONCAKE_COMPILE_ARG="-DUSE_HTTP=ON -DUSE_MNNVL=ON -DUSE_CUDA=ON -DWITH_EP=ON"
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@@ -27,8 +27,8 @@ dependencies = [
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"datasets",
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"datasets",
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"einops",
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"einops",
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"fastapi",
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"fastapi",
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"flashinfer_python==0.6.6", # keep it aligned with jit-cache version in Dockerfile
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"flashinfer_python==0.6.7", # keep it aligned with jit-cache version in Dockerfile
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"flashinfer_cubin==0.6.6",
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"flashinfer_cubin==0.6.7",
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"gguf",
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"gguf",
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"interegular",
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"interegular",
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"llguidance>=0.7.11,<0.8.0",
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"llguidance>=0.7.11,<0.8.0",
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@@ -18,7 +18,11 @@ from sglang.multimodal_gen.runtime.layers.layernorm import (
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from sglang.test.ci.ci_register import register_cuda_ci
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from sglang.test.ci.ci_register import register_cuda_ci
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from sglang.utils import is_in_ci
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from sglang.utils import is_in_ci
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register_cuda_ci(est_time=17, suite="stage-b-kernel-benchmark-1-gpu-large")
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register_cuda_ci(
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est_time=17,
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suite="stage-b-kernel-benchmark-1-gpu-large",
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disabled="Temporarily skipped to unblock flashinfer upgrade. Ref: https://github.com/sgl-project/sglang/actions/runs/23735552939/job/69139238979?pr=21422",
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)
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if is_in_ci():
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if is_in_ci():
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B_RANGE, S_RANGE, D_RANGE = [1], [128], [1024]
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B_RANGE, S_RANGE, D_RANGE = [1], [128], [1024]
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@@ -1195,7 +1195,7 @@ def _set_envs_and_config(server_args: ServerArgs):
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if server_args.attention_backend == "flashinfer":
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if server_args.attention_backend == "flashinfer":
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assert_pkg_version(
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assert_pkg_version(
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"flashinfer_python",
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"flashinfer_python",
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"0.6.6",
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"0.6.7",
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"Please uninstall the old version and "
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"Please uninstall the old version and "
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"reinstall the latest version by following the instructions "
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"reinstall the latest version by following the instructions "
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"at https://docs.flashinfer.ai/installation.html.",
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"at https://docs.flashinfer.ai/installation.html.",
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@@ -1023,7 +1023,7 @@ def check_pkg_version_at_least(pkg: str, min_version: str) -> bool:
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Args:
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Args:
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pkg: Package name (distribution name, e.g., "flashinfer-python")
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pkg: Package name (distribution name, e.g., "flashinfer-python")
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min_version: Minimum version required (e.g., "0.6.6")
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min_version: Minimum version required (e.g., "0.6.7")
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Returns:
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Returns:
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True if package is installed and version >= min_version, False otherwise
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True if package is installed and version >= min_version, False otherwise
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@@ -379,6 +379,7 @@ def run_lora_test_one_by_one(
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disable_radix_cache: bool = False,
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disable_radix_cache: bool = False,
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mem_fraction_static: float = 0.88,
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mem_fraction_static: float = 0.88,
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test_tag: str = "",
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test_tag: str = "",
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attention_backend: Optional[str] = None,
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):
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):
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"""
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"""
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Input a batch of prompts, and run lora tests one by one with several generate requests
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Input a batch of prompts, and run lora tests one by one with several generate requests
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@@ -428,6 +429,7 @@ def run_lora_test_one_by_one(
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disable_cuda_graph=disable_cuda_graph,
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disable_cuda_graph=disable_cuda_graph,
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disable_radix_cache=disable_radix_cache,
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disable_radix_cache=disable_radix_cache,
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mem_fraction_static=mem_fraction_static,
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mem_fraction_static=mem_fraction_static,
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attention_backend=attention_backend,
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) as srt_runner:
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) as srt_runner:
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srt_outputs = srt_runner.forward(
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srt_outputs = srt_runner.forward(
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prompts, max_new_tokens=max_new_tokens, lora_paths=adaptor_names
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prompts, max_new_tokens=max_new_tokens, lora_paths=adaptor_names
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@@ -439,6 +441,7 @@ def run_lora_test_one_by_one(
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model_type="generation",
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model_type="generation",
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tp_size=model_case.tp_size,
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tp_size=model_case.tp_size,
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mem_fraction_static=mem_fraction_static,
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mem_fraction_static=mem_fraction_static,
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attention_backend=attention_backend,
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) as srt_runner:
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) as srt_runner:
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srt_no_lora_outputs = srt_runner.forward(prompts, max_new_tokens=max_new_tokens)
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srt_no_lora_outputs = srt_runner.forward(prompts, max_new_tokens=max_new_tokens)
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@@ -31,7 +31,7 @@ from sglang.test.test_utils import CustomTestCase, is_in_ci
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register_cuda_ci(
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register_cuda_ci(
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est_time=116,
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est_time=116,
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suite="stage-b-test-2-gpu-large",
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suite="stage-c-test-8-gpu-h200",
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)
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)
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register_amd_ci(
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register_amd_ci(
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est_time=116,
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est_time=116,
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@@ -65,6 +65,7 @@ class TestLoRATP(CustomTestCase):
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max_new_tokens=32,
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max_new_tokens=32,
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enable_lora_overlap_loading=enable_lora_overlap_loading,
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enable_lora_overlap_loading=enable_lora_overlap_loading,
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test_tag=f"tp={tp_size}, enable_lora_overlap_loading={enable_lora_overlap_loading}",
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test_tag=f"tp={tp_size}, enable_lora_overlap_loading={enable_lora_overlap_loading}",
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attention_backend="fa3",
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)
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)
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def test_ci_lora_models(self):
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def test_ci_lora_models(self):
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@@ -126,8 +126,25 @@ class TestPiecewiseCudaGraphQwen25VLEmbedding(CustomTestCase):
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engine.shutdown()
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engine.shutdown()
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self.assertGreater(len(out_without_pcg), 0)
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self.assertGreater(len(out_without_pcg), 0)
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t_out = torch.tensor(out)
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t_out_without_pcg = torch.tensor(out_without_pcg)
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max_abs_diff = (t_out - t_out_without_pcg).abs().max().item()
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max_rel_diff = (
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((t_out - t_out_without_pcg).abs() / (t_out_without_pcg.abs() + 1e-8))
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.max()
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.item()
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)
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print(
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f"PCG embedding diff: max_abs={max_abs_diff:.6f}, max_rel={max_rel_diff:.6f}"
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)
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self.assertTrue(
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self.assertTrue(
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torch.allclose(torch.tensor(out), torch.tensor(out_without_pcg))
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torch.allclose(
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t_out,
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t_out_without_pcg,
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atol=1e-2,
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rtol=1e-2,
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),
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f"Piecewise CUDA graph embedding mismatch: max_abs_diff={max_abs_diff}, max_rel_diff={max_rel_diff}",
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)
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)
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