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[Bug] MLA models can't use enable-torch-compile. Can be fix by suppressing errors. #1423

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Achazwl opened this issue Sep 14, 2024 · 1 comment
Closed
5 tasks done

[Bug] MLA models can't use enable-torch-compile. Can be fix by suppressing errors. #1423

Achazwl opened this issue Sep 14, 2024 · 1 comment

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@Achazwl
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Achazwl commented Sep 14, 2024

Checklist

  • 1. I have searched related issues but cannot get the expected help.
  • 2. The bug has not been fixed in the latest version.
  • 3. Please note that if the bug-related issue you submitted lacks corresponding environment info and a minimal reproducible demo, it will be challenging for us to reproduce and resolve the issue, reducing the likelihood of receiving feedback.
  • 4. If the issue you raised is not a bug but a question, please raise a discussion at https://github.com/sgl-project/sglang/discussions/new/choose Otherwise, it will be closed.
  • 5. Please use English, otherwise it will be closed.

Describe the bug

MLA models like DeepSeek-V2 and MiniCPM3 cannot use --enable-torch-compile.

However, simply adding 2 lines of code into sglang can resolve it and improve single batch speed.

import torch._dynamo
torch._dynamo.config.suppress_errors = True

I request to add this error suppression before torch becomes stable.

For example, fixing this bug can make MiniCPM3 single batch decoding throughput rise from 66 token/s to 103 token/s, without affecting the output quality.

Reproduction

to reproduce:

python3 -m sglang.bench_latency --model openbmb/MiniCPM3-4B--trust-remote-code --input-len 1024 --output-len 1024 --batch 1 --enable-torch-compile

[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1] Error in codegen for ComputedBuffer(name='buf13', layout=FixedLayout('cuda', torch.bfloat16, size=[s0, 40, 128], stride=[5120, 128, 1]), data=Pointwise(
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]   'cuda',
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]   torch.bfloat16,
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]   def inner_fn(index):
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       i0, i1, i2 = index
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp0 = ops.index_expr(i2, torch.int64)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp1 = ops.index_expr(96, torch.int64)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp2 = tmp0 < tmp1
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp3 = ops.index_expr(i2, torch.int64)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp4 = ops.index_expr(64, torch.int64)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp5 = tmp3 >= tmp4
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp6 = ops.load(buf12, -64 + i2 + 32 * i0)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp7 = ops.masked(tmp5, tmp6, 0.0)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp8 = ops.index_expr(i2, torch.int64)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp9 = ops.index_expr(64, torch.int64)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp10 = tmp8 < tmp9
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp11 = ops.load(buf7, i2 + 128 * i1 + 5120 * i0)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp12 = ops.masked(tmp10, tmp11, 0.0)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp13 = ops.load(buf11, i2 + 96 * i1 + 3840 * i0)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp14 = ops.where(tmp10, tmp12, tmp13)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp15 = ops.where(tmp5, tmp7, tmp14)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       tmp16 = ops.masked(tmp2, tmp15, 0.0)
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]       return tmp16
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]   ,
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]   ranges=[s0, 40, 128],
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]   origin_node=constant_pad_nd_1,
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1]   origins={slice_scatter_default_2, copy_2, slice_scatter_defau...
[rank0]:C0914 16:10:28.525000 47272548425472 torch/_inductor/scheduler.py:836] [5/62_1] ))
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009] WON'T CONVERT forward /mypath/sglang/python/sglang/srt/models/minicpm3.py line 188 
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009] due to: 
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009] Traceback (most recent call last):
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 948, in __call__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     result = self._inner_convert(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 472, in __call__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return _compile(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_utils_internal.py", line 84, in wrapper_function
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return StrobelightCompileTimeProfiler.profile_compile_time(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_strobelight/compile_time_profiler.py", line 129, in profile_compile_time
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 817, in _compile
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     guarded_code = compile_inner(code, one_graph, hooks, transform)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 231, in time_wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     r = func(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 636, in compile_inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     out_code = transform_code_object(code, transform)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/bytecode_transformation.py", line 1185, in transform_code_object
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     transformations(instructions, code_options)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 178, in _fn
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return fn(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 582, in transform
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     tracer.run()
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 2451, in run
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     super().run()
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 893, in run
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     while self.step():
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 805, in step
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.dispatch_table[inst.opcode](self, inst)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 497, in wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return handle_graph_break(self, inst, speculation.reason)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 566, in handle_graph_break
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.output.compile_subgraph(self, reason=reason)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 1123, in compile_subgraph
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 1318, in compile_and_call_fx_graph
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_fn = self.call_user_compiler(gm)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 231, in time_wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     r = func(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 1409, in call_user_compiler
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     raise BackendCompilerFailed(self.compiler_fn, e).with_traceback(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 1390, in call_user_compiler
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_fn = compiler_fn(gm, self.example_inputs())
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/repro/after_dynamo.py", line 129, in __call__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_gm = compiler_fn(gm, example_inputs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/__init__.py", line 1951, in __call__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return compile_fx(model_, inputs_, config_patches=self.config)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 1261, in compile_fx
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return compile_fx(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 1505, in compile_fx
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return aot_autograd(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/backends/common.py", line 69, in __call__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     cg = aot_module_simplified(gm, example_inputs, **self.kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_functorch/aot_autograd.py", line 954, in aot_module_simplified
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_fn, _ = create_aot_dispatcher_function(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 231, in time_wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     r = func(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_functorch/aot_autograd.py", line 687, in create_aot_dispatcher_function
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_fn, fw_metadata = compiler_fn(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/jit_compile_runtime_wrappers.py", line 168, in aot_dispatch_base
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_fw = compiler(fw_module, updated_flat_args)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 231, in time_wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     r = func(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 1410, in fw_compiler_base
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return inner_compile(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/repro/after_aot.py", line 84, in debug_wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     inner_compiled_fn = compiler_fn(gm, example_inputs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/debug.py", line 304, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return fn(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 231, in time_wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     r = func(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 517, in compile_fx_inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_graph = FxGraphCache.load(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codecache.py", line 1044, in load
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_graph = compile_fx_fn(gm, example_inputs, **fx_kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 831, in fx_codegen_and_compile
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     compiled_fn = graph.compile_to_fn()
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/graph.py", line 1749, in compile_to_fn
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return self.compile_to_module().call
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 231, in time_wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     r = func(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/graph.py", line 1678, in compile_to_module
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.codegen_with_cpp_wrapper() if self.cpp_wrapper else self.codegen()
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/graph.py", line 1634, in codegen
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.scheduler = Scheduler(self.buffers)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 231, in time_wrapper
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     r = func(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 1409, in __init__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.fuse_nodes()
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 1825, in fuse_nodes
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.fuse_nodes_once()
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 2067, in fuse_nodes_once
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     if not self.speedup_by_fusion(node1, node2):
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 1996, in speedup_by_fusion
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     ms_fused, _ = self.benchmark_fused_nodes(node_list_fused)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 1848, in benchmark_fused_nodes
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return backend.benchmark_fused_nodes(nodes)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codegen/cuda_combined_scheduling.py", line 81, in benchmark_fused_nodes
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return self._triton_scheduling.benchmark_fused_nodes(nodes)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/contextlib.py", line 79, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return func(*args, **kwds)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codegen/triton.py", line 2515, in benchmark_fused_nodes
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     src_code = self.generate_kernel_code_from_nodes(nodes, benchmark_kernel=True)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codegen/simd.py", line 1686, in generate_kernel_code_from_nodes
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     src_code = self.codegen_template(
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codegen/simd.py", line 1420, in codegen_template
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     node.codegen(kernel.split_and_set_ranges(node.get_ranges()))
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 834, in codegen
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self._body(*index_vars)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 8038, in __call__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     result = self.root_block()
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 8200, in __call__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return InterpreterShim(graph, submodules).run(V.get_ops_handler())
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 7941, in run
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return super().run(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/fx/interpreter.py", line 146, in run
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.env[node] = self.run_node(node)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 7937, in run_node
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return super().run_node(n)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/fx/interpreter.py", line 203, in run_node
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return getattr(self, n.op)(n.target, args, kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/fx/interpreter.py", line 320, in call_module
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return submod(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 8116, in shim
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return V.ops.masked(mask, subblock, other)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codegen/common.py", line 1676, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     value = getattr(parent_handler, name)(*args, **kwargs)  # type: ignore[has-type]
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codegen/triton.py", line 923, in masked
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     result = body()
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 8200, in __call__
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return InterpreterShim(graph, submodules).run(V.get_ops_handler())
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 7941, in run
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return super().run(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/fx/interpreter.py", line 146, in run
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     self.env[node] = self.run_node(node)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 7937, in run_node
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return super().run_node(n)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/fx/interpreter.py", line 203, in run_node
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return getattr(self, n.op)(n.target, args, kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/fx/interpreter.py", line 320, in call_module
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return submod(*args, **kwargs)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/ir.py", line 8116, in shim
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     return V.ops.masked(mask, subblock, other)
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codegen/common.py", line 1676, in inner
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     value = getattr(parent_handler, name)(*args, **kwargs)  # type: ignore[has-type]
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]   File "/my_conda_env/lib/python3.10/site-packages/torch/_inductor/codegen/triton.py", line 926, in masked
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009]     if result.bounds.is_bool:
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009] torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009] AttributeError: 'str' object has no attribute 'bounds'
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009] 
[rank0]:W0914 16:10:28.557000 47272548425472 torch/_dynamo/convert_frame.py:1009] Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information

Environment

Python: 3.10.14 | packaged by conda-forge | (main, Mar 20 2024, 12:45:18) [GCC 12.3.0]
CUDA available: True
GPU 0,1,2,3,4,5,6,7: NVIDIA A800-SXM4-80GB
GPU 0,1,2,3,4,5,6,7 Compute Capability: 8.0
CUDA_HOME: /home/test/test01/cuda-12.1
NVCC: Cuda compilation tools, release 12.1, V12.1.66
CUDA Driver Version: 535.183.06
PyTorch: 2.4.0+cu121
sglang: 0.3.0
flashinfer: 0.1.6
triton: 3.0.0
transformers: 4.43.3
requests: 2.32.3
tqdm: 4.66.4
numpy: 1.26.3
aiohttp: 3.10.0
fastapi: 0.111.1
hf_transfer: 0.1.8
huggingface_hub: 0.24.3
interegular: 0.3.3
packaging: 24.1
PIL: 10.2.0
psutil: 6.0.0
pydantic: 2.8.2
uvicorn: 0.30.3
uvloop: 0.19.0
zmq: 26.0.3
vllm: 0.5.5
multipart: 0.0.9
openai: 1.44.0
anthropic: 0.34.2
NVIDIA Topology: 
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5   GPU6     GPU7    NIC0    NIC1    NIC2    NIC3    NIC4   NIC5     NIC6    NIC7    NIC8    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV8     NV8     NV8     NV8     NV8    NV8      NV8     PXB     NODE    NODE    NODE    SYS    SYS      SYS     SYS     SYS     0-51    0              N/A
GPU1    NV8      X      NV8     NV8     NV8     NV8    NV8      NV8     NODE    PXB     NODE    NODE    SYS    SYS      SYS     SYS     SYS     0-51    0              N/A
GPU2    NV8     NV8      X      NV8     NV8     NV8    NV8      NV8     NODE    NODE    PXB     NODE    SYS    SYS      SYS     SYS     SYS     0-51    0              N/A
GPU3    NV8     NV8     NV8      X      NV8     NV8    NV8      NV8     NODE    NODE    NODE    PXB     SYS    SYS      SYS     SYS     SYS     0-51    0              N/A
GPU4    NV8     NV8     NV8     NV8      X      NV8    NV8      NV8     SYS     SYS     SYS     SYS     PXB    NODE     NODE    NODE    NODE    52-103  1              N/A
GPU5    NV8     NV8     NV8     NV8     NV8      X     NV8      NV8     SYS     SYS     SYS     SYS     NODE   NODE     PXB     NODE    NODE    52-103  1              N/A
GPU6    NV8     NV8     NV8     NV8     NV8     NV8     X       NV8     SYS     SYS     SYS     SYS     NODE   NODE     NODE    PXB     NODE    52-103  1              N/A
GPU7    NV8     NV8     NV8     NV8     NV8     NV8    NV8       X      SYS     SYS     SYS     SYS     NODE   NODE     NODE    NODE    PXB     52-103  1              N/A
NIC0    PXB     NODE    NODE    NODE    SYS     SYS    SYS      SYS      X      NODE    NODE    NODE    SYS    SYS      SYS     SYS     SYS
NIC1    NODE    PXB     NODE    NODE    SYS     SYS    SYS      SYS     NODE     X      NODE    NODE    SYS    SYS      SYS     SYS     SYS
NIC2    NODE    NODE    PXB     NODE    SYS     SYS    SYS      SYS     NODE    NODE     X      NODE    SYS    SYS      SYS     SYS     SYS
NIC3    NODE    NODE    NODE    PXB     SYS     SYS    SYS      SYS     NODE    NODE    NODE     X      SYS    SYS      SYS     SYS     SYS
NIC4    SYS     SYS     SYS     SYS     PXB     NODE   NODE     NODE    SYS     SYS     SYS     SYS      X     NODE     NODE    NODE    NODE
NIC5    SYS     SYS     SYS     SYS     NODE    NODE   NODE     NODE    SYS     SYS     SYS     SYS     NODE    X       NODE    NODE    NODE
NIC6    SYS     SYS     SYS     SYS     NODE    PXB    NODE     NODE    SYS     SYS     SYS     SYS     NODE   NODE      X      NODE    NODE
NIC7    SYS     SYS     SYS     SYS     NODE    NODE   PXB      NODE    SYS     SYS     SYS     SYS     NODE   NODE     NODE     X      NODE
NIC8    SYS     SYS     SYS     SYS     NODE    NODE   NODE     PXB     SYS     SYS     SYS     SYS     NODE   NODE     NODE    NODE     X 

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

NIC Legend:

  NIC0: mlx5_0
  NIC1: mlx5_1
  NIC2: mlx5_2
  NIC3: mlx5_3
  NIC4: mlx5_4
  NIC5: mlx5_5
  NIC6: mlx5_6
  NIC7: mlx5_7
  NIC8: mlx5_8


ulimit soft: 1000000
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zhyncs commented Sep 14, 2024

It will fixed by #1422

@zhyncs zhyncs closed this as completed Sep 14, 2024
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