pytorch - 💡(How to fix) Fix [TMA] NameError in `sum` when TMA enabled
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/opt/pytorch/pytorch/torch/jit/_script.py:365: DeprecationWarning: torch.jit.script_method is deprecated. Please switch to torch.compile or torch.export.
warnings.warn(
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] Triton compilation failed: triton_per_fused_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] def triton_per_fused_0(in_ptr0, in_ptr1, out_ptr0, out_ptr1, XBLOCK : tl.constexpr):
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid = tl.program_id(0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] if pid % 2 == 0:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid_offset = pid // 2
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xnumel = 1024
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_numel = 128
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] R0_BLOCK_0: tl.constexpr = 128
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rnumel = r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_0)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_1 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x0 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp1 = tl.broadcast_to(tmp0, [XBLOCK, R0_BLOCK_0])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp3 = tl.where(r0_mask & xmask, tmp1, 0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp4 = tl.sum(tmp3, 1)[:, None].to(tl.float32)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tl.make_tensor_descriptor(out_ptr0, shape=[1024], strides=[1], block_shape=[XBLOCK]).store([xoffset], tl.reshape(tl.broadcast_to(tmp4, [XBLOCK, 1]), [XBLOCK]).to(tl.float32))
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] elif pid % 2 == 1:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid_offset = pid // 2
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xnumel = 1024
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_numel = 256
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] R0_BLOCK_1: tl.constexpr = 256
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rnumel = r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_1
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_1)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_3 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x2 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp5 = tl.make_tensor_descriptor(in_ptr1, shape=[1024, 256], strides=[256, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp6 = tl.broadcast_to(tmp5, [XBLOCK, R0_BLOCK_1])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp8 = tl.where(r0_mask & xmask, tmp6, 0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp9 = tl.sum(tmp8, 1)[:, None].to(tl.float32)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tl.make_tensor_descriptor(out_ptr1, shape=[1024], strides=[1], block_shape=[XBLOCK]).store([xoffset], tl.reshape(tl.broadcast_to(tmp9, [XBLOCK, 1]), [XBLOCK]).to(tl.float32))
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] else:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pass
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] metadata: {'signature': {'in_ptr0': '*fp32', 'in_ptr1': '*fp32', 'out_ptr0': '*fp32', 'out_ptr1': '*fp32', 'XBLOCK': 'constexpr'}, 'device': 0, 'constants': {'XBLOCK': 4}, 'enable_fp_fusion': True, 'launch_pdl': False, 'disable_ftz': False, 'configs': [{(0,): [['tt.divisibility', 16]], (1,): [['tt.divisibility', 16]], (2,): [['tt.divisibility', 16]], (3,): [['tt.divisibility', 16]]}], 'device_type': 'cuda', 'num_warps': 1, 'num_stages': 1, 'debug': True, 'cc': 90}
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] Traceback (most recent call last):
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 1090, in _precompile_config
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] binary = triton.compile(*compile_args, **compile_kwargs)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 307, in compile
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] module = src.make_ir(target, options, codegen_fns, module_map, context)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 80, in make_ir
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] return ast_to_ttir(self.fn, self, context=context, options=options, codegen_fns=codegen_fns,
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] triton.compiler.errors.CompilationError: at 20:108:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_0)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_1 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x0 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] NameError('R0_BLOCK is not defined')
E
ERROR: test_combo_kernel_per_subkernel_rblock_name (main.TestTMAComboKernelNameError.test_combo_kernel_per_subkernel_rblock_name)
Traceback (most recent call last): File "/opt/pytorch/pytorch/torch/testing/_internal/common_utils.py", line 3558, in wrapper method(*args, **kwargs) File "/usr/lib/python3.12/contextlib.py", line 81, in inner return func(*args, **kwds) ^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/name_repro.py", line 25, in test_combo_kernel_per_subkernel_rblock_name actual = compiled_fn(*inps) ^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_dynamo/eval_frame.py", line 1183, in compile_wrapper raise e.remove_dynamo_frames() from None # see TORCHDYNAMO_VERBOSE=1 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1078, in _compile_fx_inner raise InductorError(e, currentframe()).with_traceback( File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1058, in _compile_fx_inner mb_compiled_graph = fx_codegen_and_compile( ^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1846, in fx_codegen_and_compile return scheme.codegen_and_compile(gm, example_inputs, inputs_to_check, graph_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1607, in codegen_and_compile compiled_module = graph.compile_to_module() ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2661, in compile_to_module return self._compile_to_module() ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2671, in _compile_to_module mod = self._compile_to_module_lines(wrapper_code) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2746, in _compile_to_module_lines mod = PyCodeCache.load_by_key_path( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/codecache.py", line 4412, in load_by_key_path mod = _reload_python_module(key, path, set_sys_modules=in_toplevel) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/runtime/compile_tasks.py", line 35, in _reload_python_module exec(code, mod.dict, mod.dict) File "/tmp/torchinductor_root/rs/crsvukvqtx6mswi7ikxqj7jkaudkohiaimweuv7cdehmbjwm2v7o.py", line 42, in <module> triton_per_fused_0 = async_compile.triton('triton_per_fused_0', ''' ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/async_compile.py", line 514, in triton kernel.precompile( File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 626, in precompile self._precompile_worker() File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 648, in _precompile_worker compile_results.append(self._precompile_config(c)) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 1090, in _precompile_config binary = triton.compile(*compile_args, **compile_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 307, in compile module = src.make_ir(target, options, codegen_fns, module_map, context) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 80, in make_ir return ast_to_ttir(self.fn, self, context=context, options=options, codegen_fns=codegen_fns, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ torch._inductor.exc.InductorError: CompilationError: at 20:108: RBLOCK: tl.constexpr = R0_BLOCK_0 xoffset = pid_offset * XBLOCK xindex = xoffset + tl.arange(0, XBLOCK)[:, None] xmask = xindex < xnumel r0_index = tl.arange(0, R0_BLOCK_0)[None, :] r0_offset = 0 r0_mask = r0_index < r0_numel roffset = r0_offset rindex = r0_index r0_1 = r0_index x0 = xindex tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset]) ^ NameError('R0_BLOCK is not defined')
Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo"
To execute this test, run the following from the base repo dir: python name_repro.py TestTMAComboKernelNameError.test_combo_kernel_per_subkernel_rblock_name
This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
Ran 1 test in 2.638s
FAILED (errors=1)
Fix Action
Fix / Workaround
class TestTMAComboKernelNameError(TestCase): @inductor_config.patch( { "triton.use_tensor_descriptor": True, "assume_aligned_inputs": True, "combo_kernels": True, "combo_kernel_per_subkernel_blocks": False, } ) def test_combo_kernel_per_subkernel_rblock_name(self): def fn(a, b): return a.sum(dim=-1), b.sum(dim=-1)
Code Example
import torch
import torch._inductor.config as inductor_config
from torch.testing._internal.common_utils import run_tests, TestCase
class TestTMAComboKernelNameError(TestCase):
@inductor_config.patch(
{
"triton.use_tensor_descriptor": True,
"assume_aligned_inputs": True,
"combo_kernels": True,
"combo_kernel_per_subkernel_blocks": False,
}
)
def test_combo_kernel_per_subkernel_rblock_name(self):
def fn(a, b):
return a.sum(dim=-1), b.sum(dim=-1)
inps = [
torch.randn(1024, 128, device="cuda"),
torch.randn(1024, 256, device="cuda"),
]
expected = fn(*inps)
compiled_fn = torch.compile(fn)
actual = compiled_fn(*inps)
torch.testing.assert_close(expected, actual, atol=1e-4, rtol=1e-4)
if __name__ == "__main__":
run_tests()
---
/opt/pytorch/pytorch/torch/jit/_script.py:365: DeprecationWarning: `torch.jit.script_method` is deprecated. Please switch to `torch.compile` or `torch.export`.
warnings.warn(
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] Triton compilation failed: triton_per_fused_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] def triton_per_fused_0(in_ptr0, in_ptr1, out_ptr0, out_ptr1, XBLOCK : tl.constexpr):
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid = tl.program_id(0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] if pid % 2 == 0:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid_offset = pid // 2
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xnumel = 1024
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_numel = 128
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] R0_BLOCK_0: tl.constexpr = 128
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rnumel = r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_0)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_1 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x0 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp1 = tl.broadcast_to(tmp0, [XBLOCK, R0_BLOCK_0])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp3 = tl.where(r0_mask & xmask, tmp1, 0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp4 = tl.sum(tmp3, 1)[:, None].to(tl.float32)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tl.make_tensor_descriptor(out_ptr0, shape=[1024], strides=[1], block_shape=[XBLOCK]).store([xoffset], tl.reshape(tl.broadcast_to(tmp4, [XBLOCK, 1]), [XBLOCK]).to(tl.float32))
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] elif pid % 2 == 1:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid_offset = pid // 2
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xnumel = 1024
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_numel = 256
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] R0_BLOCK_1: tl.constexpr = 256
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rnumel = r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_1
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_1)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_3 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x2 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp5 = tl.make_tensor_descriptor(in_ptr1, shape=[1024, 256], strides=[256, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp6 = tl.broadcast_to(tmp5, [XBLOCK, R0_BLOCK_1])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp8 = tl.where(r0_mask & xmask, tmp6, 0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp9 = tl.sum(tmp8, 1)[:, None].to(tl.float32)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tl.make_tensor_descriptor(out_ptr1, shape=[1024], strides=[1], block_shape=[XBLOCK]).store([xoffset], tl.reshape(tl.broadcast_to(tmp9, [XBLOCK, 1]), [XBLOCK]).to(tl.float32))
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] else:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pass
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] metadata: {'signature': {'in_ptr0': '*fp32', 'in_ptr1': '*fp32', 'out_ptr0': '*fp32', 'out_ptr1': '*fp32', 'XBLOCK': 'constexpr'}, 'device': 0, 'constants': {'XBLOCK': 4}, 'enable_fp_fusion': True, 'launch_pdl': False, 'disable_ftz': False, 'configs': [{(0,): [['tt.divisibility', 16]], (1,): [['tt.divisibility', 16]], (2,): [['tt.divisibility', 16]], (3,): [['tt.divisibility', 16]]}], 'device_type': 'cuda', 'num_warps': 1, 'num_stages': 1, 'debug': True, 'cc': 90}
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] Traceback (most recent call last):
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 1090, in _precompile_config
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] binary = triton.compile(*compile_args, **compile_kwargs)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 307, in compile
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] module = src.make_ir(target, options, codegen_fns, module_map, context)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 80, in make_ir
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] return ast_to_ttir(self.fn, self, context=context, options=options, codegen_fns=codegen_fns,
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] triton.compiler.errors.CompilationError: at 20:108:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_0)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_1 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x0 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] NameError('R0_BLOCK is not defined')
E
======================================================================
ERROR: test_combo_kernel_per_subkernel_rblock_name (__main__.TestTMAComboKernelNameError.test_combo_kernel_per_subkernel_rblock_name)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/pytorch/pytorch/torch/testing/_internal/common_utils.py", line 3558, in wrapper
method(*args, **kwargs)
File "/usr/lib/python3.12/contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/name_repro.py", line 25, in test_combo_kernel_per_subkernel_rblock_name
actual = compiled_fn(*inps)
^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_dynamo/eval_frame.py", line 1183, in compile_wrapper
raise e.remove_dynamo_frames() from None # see TORCHDYNAMO_VERBOSE=1
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1078, in _compile_fx_inner
raise InductorError(e, currentframe()).with_traceback(
File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1058, in _compile_fx_inner
mb_compiled_graph = fx_codegen_and_compile(
^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1846, in fx_codegen_and_compile
return scheme.codegen_and_compile(gm, example_inputs, inputs_to_check, graph_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1607, in codegen_and_compile
compiled_module = graph.compile_to_module()
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2661, in compile_to_module
return self._compile_to_module()
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2671, in _compile_to_module
mod = self._compile_to_module_lines(wrapper_code)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2746, in _compile_to_module_lines
mod = PyCodeCache.load_by_key_path(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/codecache.py", line 4412, in load_by_key_path
mod = _reload_python_module(key, path, set_sys_modules=in_toplevel)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/runtime/compile_tasks.py", line 35, in _reload_python_module
exec(code, mod.__dict__, mod.__dict__)
File "/tmp/torchinductor_root/rs/crsvukvqtx6mswi7ikxqj7jkaudkohiaimweuv7cdehmbjwm2v7o.py", line 42, in <module>
triton_per_fused_0 = async_compile.triton('triton_per_fused_0', '''
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/async_compile.py", line 514, in triton
kernel.precompile(
File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 626, in precompile
self._precompile_worker()
File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 648, in _precompile_worker
compile_results.append(self._precompile_config(c))
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 1090, in _precompile_config
binary = triton.compile(*compile_args, **compile_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 307, in compile
module = src.make_ir(target, options, codegen_fns, module_map, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 80, in make_ir
return ast_to_ttir(self.fn, self, context=context, options=options, codegen_fns=codegen_fns,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
torch._inductor.exc.InductorError: CompilationError: at 20:108:
RBLOCK: tl.constexpr = R0_BLOCK_0
xoffset = pid_offset * XBLOCK
xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
xmask = xindex < xnumel
r0_index = tl.arange(0, R0_BLOCK_0)[None, :]
r0_offset = 0
r0_mask = r0_index < r0_numel
roffset = r0_offset
rindex = r0_index
r0_1 = r0_index
x0 = xindex
tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
^
NameError('R0_BLOCK is not defined')
Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo"
To execute this test, run the following from the base repo dir:
python name_repro.py TestTMAComboKernelNameError.test_combo_kernel_per_subkernel_rblock_name
This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
----------------------------------------------------------------------
Ran 1 test in 2.638s
FAILED (errors=1)RAW_BUFFERClick to expand / collapse
🐛 Describe the bug
Repro
import torch
import torch._inductor.config as inductor_config
from torch.testing._internal.common_utils import run_tests, TestCase
class TestTMAComboKernelNameError(TestCase):
@inductor_config.patch(
{
"triton.use_tensor_descriptor": True,
"assume_aligned_inputs": True,
"combo_kernels": True,
"combo_kernel_per_subkernel_blocks": False,
}
)
def test_combo_kernel_per_subkernel_rblock_name(self):
def fn(a, b):
return a.sum(dim=-1), b.sum(dim=-1)
inps = [
torch.randn(1024, 128, device="cuda"),
torch.randn(1024, 256, device="cuda"),
]
expected = fn(*inps)
compiled_fn = torch.compile(fn)
actual = compiled_fn(*inps)
torch.testing.assert_close(expected, actual, atol=1e-4, rtol=1e-4)
if __name__ == "__main__":
run_tests()Error logs
/opt/pytorch/pytorch/torch/jit/_script.py:365: DeprecationWarning: `torch.jit.script_method` is deprecated. Please switch to `torch.compile` or `torch.export`.
warnings.warn(
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] Triton compilation failed: triton_per_fused_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] def triton_per_fused_0(in_ptr0, in_ptr1, out_ptr0, out_ptr1, XBLOCK : tl.constexpr):
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid = tl.program_id(0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] if pid % 2 == 0:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid_offset = pid // 2
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xnumel = 1024
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_numel = 128
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] R0_BLOCK_0: tl.constexpr = 128
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rnumel = r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_0)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_1 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x0 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp1 = tl.broadcast_to(tmp0, [XBLOCK, R0_BLOCK_0])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp3 = tl.where(r0_mask & xmask, tmp1, 0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp4 = tl.sum(tmp3, 1)[:, None].to(tl.float32)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tl.make_tensor_descriptor(out_ptr0, shape=[1024], strides=[1], block_shape=[XBLOCK]).store([xoffset], tl.reshape(tl.broadcast_to(tmp4, [XBLOCK, 1]), [XBLOCK]).to(tl.float32))
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] elif pid % 2 == 1:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pid_offset = pid // 2
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xnumel = 1024
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_numel = 256
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] R0_BLOCK_1: tl.constexpr = 256
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rnumel = r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_1
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_1)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_3 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x2 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp5 = tl.make_tensor_descriptor(in_ptr1, shape=[1024, 256], strides=[256, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp6 = tl.broadcast_to(tmp5, [XBLOCK, R0_BLOCK_1])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp8 = tl.where(r0_mask & xmask, tmp6, 0)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp9 = tl.sum(tmp8, 1)[:, None].to(tl.float32)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tl.make_tensor_descriptor(out_ptr1, shape=[1024], strides=[1], block_shape=[XBLOCK]).store([xoffset], tl.reshape(tl.broadcast_to(tmp9, [XBLOCK, 1]), [XBLOCK]).to(tl.float32))
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] else:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] pass
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] metadata: {'signature': {'in_ptr0': '*fp32', 'in_ptr1': '*fp32', 'out_ptr0': '*fp32', 'out_ptr1': '*fp32', 'XBLOCK': 'constexpr'}, 'device': 0, 'constants': {'XBLOCK': 4}, 'enable_fp_fusion': True, 'launch_pdl': False, 'disable_ftz': False, 'configs': [{(0,): [['tt.divisibility', 16]], (1,): [['tt.divisibility', 16]], (2,): [['tt.divisibility', 16]], (3,): [['tt.divisibility', 16]]}], 'device_type': 'cuda', 'num_warps': 1, 'num_stages': 1, 'debug': True, 'cc': 90}
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] Traceback (most recent call last):
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 1090, in _precompile_config
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] binary = triton.compile(*compile_args, **compile_kwargs)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 307, in compile
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] module = src.make_ir(target, options, codegen_fns, module_map, context)
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 80, in make_ir
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] return ast_to_ttir(self.fn, self, context=context, options=options, codegen_fns=codegen_fns,
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] triton.compiler.errors.CompilationError: at 20:108:
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] RBLOCK: tl.constexpr = R0_BLOCK_0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xoffset = pid_offset * XBLOCK
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] xmask = xindex < xnumel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_index = tl.arange(0, R0_BLOCK_0)[None, :]
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_offset = 0
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_mask = r0_index < r0_numel
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] roffset = r0_offset
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] rindex = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] r0_1 = r0_index
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] x0 = xindex
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] ^
E0528 06:26:02.498000 168264 torch/_inductor/runtime/triton_heuristics.py:1092] [0/0] NameError('R0_BLOCK is not defined')
E
======================================================================
ERROR: test_combo_kernel_per_subkernel_rblock_name (__main__.TestTMAComboKernelNameError.test_combo_kernel_per_subkernel_rblock_name)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/pytorch/pytorch/torch/testing/_internal/common_utils.py", line 3558, in wrapper
method(*args, **kwargs)
File "/usr/lib/python3.12/contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/name_repro.py", line 25, in test_combo_kernel_per_subkernel_rblock_name
actual = compiled_fn(*inps)
^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_dynamo/eval_frame.py", line 1183, in compile_wrapper
raise e.remove_dynamo_frames() from None # see TORCHDYNAMO_VERBOSE=1
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1078, in _compile_fx_inner
raise InductorError(e, currentframe()).with_traceback(
File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1058, in _compile_fx_inner
mb_compiled_graph = fx_codegen_and_compile(
^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1846, in fx_codegen_and_compile
return scheme.codegen_and_compile(gm, example_inputs, inputs_to_check, graph_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/compile_fx.py", line 1607, in codegen_and_compile
compiled_module = graph.compile_to_module()
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2661, in compile_to_module
return self._compile_to_module()
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2671, in _compile_to_module
mod = self._compile_to_module_lines(wrapper_code)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/graph.py", line 2746, in _compile_to_module_lines
mod = PyCodeCache.load_by_key_path(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/codecache.py", line 4412, in load_by_key_path
mod = _reload_python_module(key, path, set_sys_modules=in_toplevel)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/runtime/compile_tasks.py", line 35, in _reload_python_module
exec(code, mod.__dict__, mod.__dict__)
File "/tmp/torchinductor_root/rs/crsvukvqtx6mswi7ikxqj7jkaudkohiaimweuv7cdehmbjwm2v7o.py", line 42, in <module>
triton_per_fused_0 = async_compile.triton('triton_per_fused_0', '''
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/async_compile.py", line 514, in triton
kernel.precompile(
File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 626, in precompile
self._precompile_worker()
File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 648, in _precompile_worker
compile_results.append(self._precompile_config(c))
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/pytorch/pytorch/torch/_inductor/runtime/triton_heuristics.py", line 1090, in _precompile_config
binary = triton.compile(*compile_args, **compile_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 307, in compile
module = src.make_ir(target, options, codegen_fns, module_map, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/triton/compiler/compiler.py", line 80, in make_ir
return ast_to_ttir(self.fn, self, context=context, options=options, codegen_fns=codegen_fns,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
torch._inductor.exc.InductorError: CompilationError: at 20:108:
RBLOCK: tl.constexpr = R0_BLOCK_0
xoffset = pid_offset * XBLOCK
xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
xmask = xindex < xnumel
r0_index = tl.arange(0, R0_BLOCK_0)[None, :]
r0_offset = 0
r0_mask = r0_index < r0_numel
roffset = r0_offset
rindex = r0_index
r0_1 = r0_index
x0 = xindex
tmp0 = tl.make_tensor_descriptor(in_ptr0, shape=[1024, 128], strides=[128, 1], block_shape=[XBLOCK, R0_BLOCK]).load([xoffset, r0_offset])
^
NameError('R0_BLOCK is not defined')
Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo"
To execute this test, run the following from the base repo dir:
python name_repro.py TestTMAComboKernelNameError.test_combo_kernel_per_subkernel_rblock_name
This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
----------------------------------------------------------------------
Ran 1 test in 2.638s
FAILED (errors=1)Versions
main: 339e39645a25968c7cd3fb81dd7e48ca3a31f9c2 H100
cc @ptrblck @msaroufim @eqy @tinglvv @nWEIdia @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @kadeng @muchulee8 @amjames @aakhundov @coconutruben @jataylo
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- Critical Crash: ioctl(2) failed, EBADF in ShellExecutionService.resizePty
- ioctl(2) failed, EBADF
- v0.44.0 Regression: Critical crash with ioctl(2) failed, EBADF during PTY resize
- Crash on startup: ioctl(2) failed, EBADF in UnixTerminal.resize
- Crash: `ioctl(2) failed, EBADF` in `node-pty` during PTY resize on macOS
- Gemini CLI crashes with `ioctl(2) failed, EBADF` in `node-pty` during `resizePty`
- Remote Role
- ERROR ioctl(2) failed, EBADF /home/mich
- RangeError: Maximum call stack size exceeded
- EBADF Error during folder creationg broke session and terminal glitches
- MAIP / Gargoub Project - Mediterania - North Coast
- Gemini cli crash again in this morning
- ERROR ioctl(2) failed, EBADF
- Verified node install fails — Checksum verification failed (Cloud)
- The extended debugging key did not arrive during registration.
- CollaborationPane unmounts collaboration store on single-user instances, causing permanent "No network connection" state
- Workflow cannot be saved when the name contains "->" (Potentially malicious string)
- automation does not work and does not show an error
- Raj Ai Automation
- Default Data Loader: DOMMatrix is not defined error
- Feature: Per-node execution timestamp overlay on canvas during workflow run
- AI Agent + Vertex `gemini-3.5-flash`: 400 "missing thought_signature" on sequential multi-turn tool calls (post-#24982)
- PDF Loader in Pinecone Vector Store fails due to pdf-parse version conflict (v2 not supported)
- emailReadImap: add UID deduplication, batch size cap, and numeric uid enforcement
- Manual node execution fails with "Could not find a node" when autosave is disabled (N8N_WORKFLOWS_AUTOSAVE_DISABLED)
- Schedule Trigger stopped firing — workflow Published & active, manual executions succeed, no automated fires for 2+ hours
- [MCP SDK] create_workflow_from_code intermittently returns HTTP 500, often as a false negative (workflow persists anyway, causing duplicates on retry)
- Credential-load wedge: workflows using googleApi/jwtAuth credentials silently fail to execute after key rotation
- Google Sheets Trigger every minute is not working manual Execute is working sent email
- [BUG] Plugin marketplace MCP connector remains stuck "still connecting" when mcp-remote requires OAuth
- [redacted at user request]
- Opus 4.7 behavioral regression: loaded instruction-following discipline degraded in recent Claude Code/Cowork updates
- [BUG] Tailscale via Homebrew CLI + Mac App Store GUI, both Macs on macOS, Cowork blocked by VPN detector despite Tailscale being a mesh VPN with no traffic interception
- stopShellPty on tab switch kills active sessions (exit 143) — regression in May 27 build
- [BUG] Long URLs are broken into multiple lines and become unclickable in terminal output
- [BUG] claude rm/stop/reap SIGKILLs background session tree without SIGTERM grace, orphaning git index.lock and similar
- [BUG] Default git workflow in the system prompt was pushed without context or consent
- [MODEL] Inconsistent output quality / Ignoring instructions (overfitting and inappropriate repetition of Korean vocabulary)
- You've hit your weekly limit · resets May 31 at 5pm (Asia/Shanghai)
- Paid yearly subscription silently downgraded to Free with no user action
- [Regression v2.1.153] Plugin bash hooks fail with "echo: write error: Permission denied" on Windows (claude-mem, shell: "bash")
- [BUG] Connector toggles in conversation are not clickable — must click text label instead
- [remote-control] Input from mobile app/browser not reaching host session — output works fine
- Model fails to read/reference CLAUDE.md contents despite being loaded in context
- [BUG] Claude Desktop reinstall destroys Code chat history (transcripts + Recents) while regular Chat history, project files, and memory all survive
- Bypass mode clamps to Accept Edits even with the toggle ON (Claude Code Desktop 1.9255.2 / CC 2.1.149)
- [BUG] TUI input freezes randomly mid-typing — entire prompt becomes unresponsive for minutes
- [BUG] Cowork downloads Linux ELF binary instead of macOS binary on macOS Sonoma 14.8.7 — exit code 132 (SIGILL) on every session
- [Feature Request] Persistent project memory — sessions forget everything on close, forcing users to keep many sessions open
- [Bug] Thread context stale after sleep/resume, returns outdated date and calendar data
- [FEATURE] Add context window usage indicator and warning before auto-compaction
- [BUG] Dictation error: Invalid character in header content ["x-config-keyterms"] on Windows
- [Bug] Anthropic API Error: Server rate limiting despite normal usage
- Does delegating work to `claude -p` subprocesses reduce context accumulation in the parent session?
- [BUG] Claude Code hangs on M1 Mac when terminal says "opening browser to sign in" and browser opens
- [BUG] Claude_Preview MCP preview_start spawns dev server with main-repo cwd instead of session's worktree cwd
- [Bug] Anthropic API Error: Server rate limiting during request execution
- [Bug] Anthropic API Error: Server rate limiting on concurrent requests
- [Bug] Ultraplan ready notification fires before cloud agent completes execution
- [BUG] API 500 ERROR ALL THROUGHOUT THE DAY
- [BUG] Cowork: Live Artifacts folder path changed in 1.9255.2, no automatic migration from Documents\Claude\Artifacts
- [Bug] Auto-compact never triggers despite statusline reporting "100% context used" (v2.1.153, Max sub, 200K mode)
- [BUG] [Desktop / macOS] 'Open in → New Window' detached session: font renders smaller than main, no per-window controls, Cmd+/Cmd- keystrokes routed to main window instead
- Feature request: option to switch between classic and new minimal UI
- [Feature Request] Show timestamps for each message
- [BUG] Terminal corruption when permission prompt appears while navigating Agent Teams agent selection menu
- [FEATURE] Allow users to customize the background color of the Claude desktop app beyond the current light/dark theme presets.
- [BUG] Statusline not displaying on Windows [fixed]
- Background agent UI Stop button is a no-op for stuck agents — process keeps consuming tokens
- Background agents silently die on session pause/resume — no completion notification, no work recovery
- Add option to hide email address from welcome banner
- [BUG] SSH Remote: `projects` field in remote ~/.claude.json becomes null after desktop restart — jsonl files intact, UI shows 'No messages yet' for every session
- [Bug] Claude Code not applying fixes despite claiming to complete tasks
- billing is unfair and poorly documented
- [BUG] Claude Code on the web: declared plugins inactive on first session, require restart to fully load
- [BUG] Restore from archive deleted sessions instead of restoring them
- [BUG] M365 connector fails with AADSTS50011 in Cowork — localhost vs 127.0.0.1 redirect URI mismatch
- claude agents: workflow slash-commands missing from dispatch-input completion (regression-adjacent to #61424)
- Claude Desktop's Info.plist missing TCC usage strings, blocks all EventKit-based MCP servers
- False-positive safety blocks on self-administered governance amendments — request for owner-authority mode for verified professional users
- [BUG] Stop pushing "AUTO"-mode
- [DOCS] Plugin marketplace guide omits `skipLfs` option for git-based sources
- [DOCS] MCP docs omit combined startup notification for MCP server and connector authentication
- [DOCS] Agent view docs omit macOS Privacy & Security identity for background agents
- [DOCS] Npm update docs do not explain release-channel behavior for `claude update`
- [DOCS] Agent SDK docs omit `subagent_type: "claude"` worktree and output persistence behavior
- [DOCS] Background session docs omit `$CLAUDE_JOB_DIR` temp-file behavior
- [FR] mask env-var values in 'claude mcp get <server>' output
- [FR] subagent worktrees should not inherit stale local 'user.email' from prior dispatches
- [BUG] Windows: Grep tool leaks rg.exe + conhost.exe processes (~2000 zombies / 14 GB RAM in long sessions)
- [BUG] Stats dashboard "Peak hour" appears off by one hour
- [BUG] Diff highlight (teal SGR background) bleeds past changed text in 2.1.150–2.1.153
- [FEATURE] confirm before deleting session
- Plugin PostToolUse hooks still silently skip in Claude Desktop / Cowork (re-filing closed #51904)
- /code-review skill: silent fallback to main...HEAD reviews other people's commits, and JSON-only output is hard to read
- Monitor tool doesn't source the shell snapshot like Bash does; PATH-dependent tools (jq, sleep, etc.) fail in Monitor commands on macOS/Nix
- [Bug] Long input lines truncated with ellipsis while typing instead of wrapping in terminal UI
- [FEATURE] VS Code extension: Render submitted user messages as Markdown in chat
- OSC 52 copy from Claude TUI doesn't reach clipboard inside tmux (regression in 2.1.146–2.1.153)
- [BUG] RemoteTrigger create/update returns HTTP 400 with circular error: "event_type is required" / "unknown field event_type"
- [BUG] Option to hide or minimize the built-in "status footer" (multi-line debug/cost panel) [re-raise of #31475]
- [Bug] Feedback submissions being closed without review or action
- [FEATURE] Word-jump cursor navigation in Chat input (option+arrow / bindable actions)
- [FEATURE] ! shell mode: filesystem tab completion
- [BUG] API Error: Usage credits required for 1M context
- claude agents: OSC 52 clipboard emission broken in tmux (regression in 2.1.146–2.1.153)
- CLI crashes on macOS 15 M3 - exit code 1
- [FEATURE] Support Cmd+V image paste from clipboard
- [FEATURE] Enhance claude.ai M365 connector to support MS Planner
- [BUG] Slash command autocomplete hijacks pasted absolute file paths starting with /
- PreToolUse hook `if` filter false-positives on complex Bash commands
- [BUG] Diff panel hangs/whites out
- Feature Request: Support drag-and-drop for binary documents (.wps, .doc, .docx, .xlsx, .pdf) in VS Code extension
- [BUG] activation of 1M context in VSCode
- [FEATURE] Support i18n / language localization for built-in slash command outputs
- Ctrl+V para colar imagens deixou de funcionar no CLI (Windows, PowerShell)
- [FEATURE] Please add Norwegian (Bokmål/Nynorsk) language support to the Claude Code interface
- [BUG] OTel log events (claude_code.user_prompt, api_request_body, tool_decision, hook_execution_complete) emitted with empty trace_id/span_id while sibling spans correlate correctly
- [BUG] Cowork crashes on every message, no VM logs generated, missing AppData\Roaming\Claude
- [FEATURE] first-class session handoff + per-session token budgets for unattended runs
- [FEATURE] Smart paste: convert clipboard code to file reference chips (like Cursor)
- [Feature Request] Restore chat pin functionality to title chat submenu
- [BUG] SIGILL issues with version 2.1.153
- [BUG] Cowork plugin upload fails with generic "Plugin validation failed" when a `description` field in any SKILL.md frontmatter contains angle brackets (`<…>`)
- [BUG] Desktop App 2.1.144+: startup scanner deletes cliSessionId from claude-code-sessions local files on every launch — session not found on disk
- [Feature Request] Add keyboard shortcut to copy last message with proper formatting
- [MODEL] Opus 4.7 not 1M
- Allow naming/renaming background agents in `claude agents` view
- Stale worktrees in .claude/worktrees/ are never cleaned up, consuming massive disk space
- Agent worktrees are never cleaned up, silently consuming disk space
- Subagent worktrees not auto-cleaned when reviewer writes scratch files
- [Bug] Skill initialization hangs for extended duration in Plan Mode
- Claude Desktop writes malformed registry Run entry (nested escaped quotes) - crashes Windows Task Manager and other Run-key parsers
- IME candidate window shows at bottom-right corner instead of caret position (Windows CMD)
- [BUG] Pressing 'Escape' doesn't close the /BTW conversation when the main conversation is asking for approval
- [BUG] Opus 4.7 (1M) intermittently emits empty-string values for tool_use.input fields, killing the session
- FleetView agent UI shows "running" with incrementing elapsed time after agent has returned
- /doctor flags context-scoped cmd+c binding as macOS conflict (false positive)
- [BUG] Text Rendering in Elvish
- Desktop app: Bypass Permissions mode flips to Accept Edits on first prompt (M5 / macOS 26.5)
- [Workaround] Date-Weekday Verification Hook — Prevents Claude from writing wrong weekdays
- [BUG] Claude Code create c:/memfs directory without asking me.
- [BUG] Claude Code's Bash execution waits forever with no processes running
- [BUG] usage stays stuck waiting for 5 hr limit after upgrading to premium seat in team plan
- [Workflow tool] resume cache is unreachable for nontrivial workflows because LLM dispatchers can't transcribe args byte-exactly
- Code review (Preview): "Add a repository" shows no results for private GitHub org repos
- [BUG] /context commands blows up context
- [Feature Request] Add precache expiry hook to enable proactive compaction before token eviction
- [BUG] Context indicator shows 0% at session start despite ~20K+ tokens already loaded
- [Feature Request] Add semantic search for --resume session history
- [Feature Request] Add session search, tagging, and filtering capabilities
- [BUG] Cowork Dispatch reports "desktop not available" on Windows 11 while standard Cowork works normally
- [Bug] Claude Code provides incorrect suggestions with high confidence despite errors
- defaultMode: acceptEdits silently overrides per-path permissions.ask rules for Write/Edit
- [FEATUR configurable tip interval (e.g. tipIntervalSeconds: 30 in settings)E]
- Plugin marketplace fails to load: schema rejects 'displayName' key (v2.1.153)
- claude agents: in-session copy uses broken OSC 52 path while overview correctly uses tmux buffer
- [BUG] Plugin agent descriptions (and custom agents) load unconditionally into context — no parity with disable-model-invocation for skills
- Crashed ultrareview consumed a free credit despite producing zero findings
- [Bug] Character rendering issue - invisible or missing text display
- [BUG] Cowork: processo Claude Code encerra com código 3 — .claude.json não contém token de autenticação (Windows 11 25H2)
- [BUG] 2.1.153 silently discards tools/list response from rmcp 0.12.0 HTTP MCP server (works in 2.1.152, wire-identical handshake)
- VS Code extension: option to auto-resume last session when reopening a workspace folder
- [Bug] Conversation continuation failure
- [BUG] Cowork crashes every time I start a new chat or attempt to continue an existing one in any project. The error displayed is: "Claude Code è andato in crash
- [Bug] Unannounced quota changes
- Native update/install fails with 'socket connection was closed unexpectedly' behind proxy — undici TLS incompatibility
- [BUG] Session name reverting after manual change
- [BUG] 非正常思考，上下文过长时，一直显示思考，点击interrupt按钮失效
- Honor `tools:` frontmatter when an agent is invoked via `@mention` — strip `Task` only when the agent did not declare it
- macOS TCC popup still recurring on v2.1.153 — "2.1.153" would like to access data from other apps
- Claude Code leaks pty handles — exhausts pseudo-terminals on macOS after long session
- [Bug] Agent fails to execute or respond to user input
- [BUG] Persistent "Expecting value: line 1 column 1 (char 0)" JSON parse error after tool execution
- [Feature Request] Implement proactive unit test coverage recommendations for recurring bugs
- VS Code panel lacks status line + terminal lacks image paste in Codespaces, forcing a tradeoff
- `/powerup` only shows ~10 lessons — allow viewing the full catalog
- [Bug] Context contamination after auto-compact with unrelated email draft of Tejo/Sado Basin
- [Bug] VSCode terminal output displays corrupted text with garbled symbols
- [Feature Request] Add LaTeX/KaTeX math rendering to TUI
- [Bug] Sub-agent PR review results not validated by orchestrating agent
- Subagents on Pro 1M tier: trivial probes pass, real workloads fail at first tool call (probe-vs-workload divergence)
- Path-scoped rules and subdirectory CLAUDE.md not loaded when creating new files matching the pattern
- AskUserQuestion: cancelling during extended thinking poisons the whole session with 400 'thinking blocks cannot be modified' (2.1.153); concurrent prompts overwrite each other
- Ideas Missing from Claude Cowork Menu (Windows)
- [BUG_BOUNTY_SAFE_POC_2026] Prompt Injection RCE Test - Command Execution Proof
- [BUG] Cowork scheduled task: execution history row not showing after successful run
- Resuming an extended-thinking session fails permanently with 400 "thinking blocks cannot be modified" (transcript stores thinking text as empty but keeps signature)
- [Bug] Plugin-registered CwdChanged and FileChanged hooks don't fire (settings.json works) — v2.1.153
- Auto-archive on PR merge / branch delete — clarify autoArchiveSessions semantics or add dedicated opt-out
- `claude mcp add` echoes Authorization header value verbatim to stdout, leaks bearer tokens to terminal and session transcripts
- [BUG] Bug report — /insights skill, Claude Code The /insights skill outputs a malformed file path.
- Plugin slash commands render with '*'-inline format instead of two-column, despite matching official plugin shape
- [Bug] Unexpected long text generation without user input or goal
- [Bug] Thinking blocks causing task progression blocked without user modification
- [BUG] (Critical!) contamination by an unknown session simirlar to the report => [Bug] Context contamination after auto-compact with unrelated email draft of Tejo/Sado Basin #63137
- [Critical] Opus 4.7 Korean output degeneration — Korean grammar itself collapses in long contexts
- [BUG] Title: Autocompact buffer persists across /clear — wastes tokens for irrelevant old context
- [Bug] Auto-Compact loses user input before processing in conversation history
- Feature: per-invocation effort parameter + runtime session-config introspection for skills
- Auto-mode classifier mislabels Azure DevOps vote -5 as "Reject" when denying PR vote actions
- [BUG] Claude Desktop and Claude Code CLI never re-register MCP tools after OAuth 2.1 handshake on a remote HTTP server
- [BUG] Workspace file tags leak across sessions
- [BUG] Ink renderer crashes on Windows 11 build 26200 (Canary) duplicate banners, terminal mode leaks, mid-operation aborts
- [BUG] Claude Code Desktop issue
- PTY master fd leak in Claude desktop app exhausts macOS kern.tty.ptmx_max after ~2-3 days
- [BUG] Claude Code — Session Management after Unexpected Interruption
- [Windows] Cowork OpenTelemetry exporter does not initialize - zero events emitted to any destination, including loopback
- [Bug] Opus 4.7: 400 `thinking blocks ... cannot be modified` on long extended-thinking sessions, triggered by history-altering events (scheduled prompts / parallel tool-call cancellation)
- [BUG] API Error: Server is temporarily limiting requests (not your usage limit) · Rate limited
- Multi-plugin custom marketplace: only first plugin registered in installed_plugins.json, skills don't load
- [BUG] Git push through the SDK's git proxy fan-outs into ~500 GitHub REST API calls, exhausting the 5,000/hour budget after a handful of pushes
- [BUG] Claude took liberties it really shouldn't with my global config
- [BUG] Agent window focus lost after navigating with arrow keys, causing scroll deadlock
- [BUG] `--model` flag silently ignored in interactive sessions (works in `--print` only)
- [BUG] Dispatch permanently shows "desktop appears offline" on Windows 11 - never worked on first use
- feat: support per-command enableWeakerNetworkIsolation as safer alternative to dangerouslyDisableSandbox
- /code-review outputs a raw JSON array instead of readable findings
- [BUG] Cowork — Additional allowed domains ignored on Team plan; same domain works on Pro plan
- Haiku
- [Bug] False positive blocking beneficial outcomes in tool execution
- 3P Bedrock SSO: credentials silently expire without triggering re-auth on day 2+
- CLAUDE_AUTOCOMPACT_PCT_OVERRIDE in settings.json env block silently ignored by autocompact logic
- Auto-compaction deletes main session JSONL before verifying summary completion, causing data loss
- [Bug] Claude Code not executing stated actions or producing expected results
- [FEATURE] Deferred Messages — Queue Input for End of Turn
- [BUG] Up/Down arrows in input box navigate history instead of moving cursor — regression in 2.1.149+
- Cancelling a parallel tool-call batch corrupts thinking blocks -> 400 "thinking blocks cannot be modified" permanently wedges the session
- Claude Code caused data loss, then contradicted itself about recovery (two incidents, one session)
- [Bug] Unclear error messages from Claude Code CLI
- [Bug] Agent tool rejecting due to context size limit exceeded
- claude agents: daemon and bg-spare processes spin at ~100% CPU when idle
- [BUG] Compaction fails with "context window limit" error even when context usage is low (e.g., 20%) — regression in v2.1.153
- Remote Control entitlement lost after May 27-28 incident — `Error: Remote Control is not yet enabled for your account` on active Max subscription
- PreToolUse hook exit code 2 does not block Write tool
- [Bug] Thinking blocks in latest assistant message are immutable
- GUI: dispatch file:// and custom-scheme clicks to OS shell handler
- Show current model in statusLine by default
- [Bug] Agent console becomes unresponsive to keyboard input after multiple agents initialized
- [FEATURE] PreToolUse hooks should have a way of updating the environment
- [Bug] Unable to start or use Claude Code CLI
- [BUG] Repository not visible in Claude Code web repo picker
- Session permanently wedged on 400 "thinking blocks cannot be modified" after parallel tool_results
- [Bug] @ autocomplete loses sibling repos after a file edit in multi-repo workspace
- Unclear error message when creating sub-agent without authentication
- [Bug] Anthropic API errors causing frequent failures and high token usage
- [BUG] @ mention file picker only shows packages, not individual files (desktop app - Code tab)
- [Bug] TUI panel footer remains sticky and consumes excessive terminal space
- PR-status polling exhausts GitHub GraphQL rate limit on repos with many open PRs
- [BUG] Windows: welcome panel not shown in some project folders (2.1.153)
- [Bug] Anthropic API Error: thinking blocks corrupted during context compaction with extended thinking enabled
- API 400 "thinking blocks cannot be modified" permanently bricks session during agent activation (interleaved thinking + tool use)
- Right-click Copy copies the whole message instead of the selection; pasted text retains dark background
- Mid-session model switch corrupts conversation when extended thinking is enabled (API 400: 'thinking blocks cannot be modified')
- [BUG] Markdown file links in chat output do not open files when clicked (VS Code extension)
- Stuck retry loop: `400 thinking blocks cannot be modified` on large interleaved-thinking turns using AskUserQuestion
- [FEATURE] Prompt user for approval before auto-compaction proceeds
- Custom MCP connectors not attachable to scheduled routines — no UUID discovery path
- [BUG] Claude in Chrome — Navigation blocked for teams.cloud.microsoft and outlook.cloud.microsoft after Microsoft domain migration**
- [BUG] Claude Desktop — Personal plugins panel renders list but is entirely non-interactive (macOS, v1.9255.2)
- [Bug] error when using Workflows
- [BUG] Persistent "update available" notification despite being on latest version
- [BUG] Sweep Agent from /code-review never completes
- [Bug] Tool calls not executing or returning results
- [FEATURE] Cloud-synced memory and settings across machines
- [Bug] Terminal UI freezes when Ctrl+O view exits during interactive prompt in plan mode
- Continuous api errors when using claude code with Opus 4.7 with thinking on low
- [Feature Request] Add support for installing and using previous Claude Code versions
- [Bug] Extended Thinking: Summarized thinking blocks fail signature validation when resent to API
- [Bug] Anthropic API Error: 'thinking' blocks cannot be modified
- [Bug] Anthropic API Error: Thinking blocks cannot be modified with extended thinking mode
- Feature request: Lazy/on-demand MCP server connections
- [Bug] Tool Arguments Parsed as String Instead of Object
- [Bug] Anthropic API Error: Insufficient context provided
- [Bug] Claude Opus occasionally uses moskovian(russian) orthography instead of Ukrainian in system-prompted responses
- Opus 4.8: backgrounded task completions (subagents AND Bash) crash with 400 "thinking blocks cannot be modified"
- [Bug] Opus 4.7 fabricates stable preferences ("my default") to rationalize arbitrary choices when challenged
- [Bug] Unable to update Claude Code CLI
- [BUG] Desktop app: /remote-control mints link + connects bridge (main.log) but in-chat link/QR panel never renders
- Feature: sessionColor and sessionName in .claude/settings.json
- [BUG] Anthropic API error: thinking blocks
- [FEATURE] Support Remote MCPs in Cowork as in Claude Code
- [Bug] Anthropic API Error: 400 Bad Request with Redacted Thinking - 0 4.7 & 4.8
- [Bug] Anthropic API Error: Cannot modify thinking blocks from different model versions
- Interleaved thinking + multi-tool turn corrupts thinking block (text blanked, signature kept) → permanent 400 'blocks must remain as they were'
- [BUG] Mode/permission changes mid-tool-loop (effortLevel: xhigh) poisons entire session
- Session failure log: Opus 4.6 ignores its own rules for an entire session
- [BUG] "400 Guardrail was enabled" error when using Claude Opus 4.8 with AWS Bedrock
- [Feature Request] Add subagent approach selection option to avoid accidental feedback
- Persistent 400 'thinking blocks in the latest assistant message cannot be modified' — interleaved thinking persisted with empty text + signature bricks sessions
- [BUG] DesktopvsApp
- [BUG] Opus 4.7 cache hit rate collapse after May 27 incident — Messages 1.1k→88.9k in 9 minutes, $630/session
- [Bug] Anthropic API Error: Invalid thinking block format
- [BUG] FUCK CLAUDE
- Opus 4.8 extended thinking: Stop hook block re-entry corrupts thinking blocks → 400
- [Bug] 4.8 Fails when accessing previous model history
- [Bug] Unintended File Modifications During Execution
- [DOCS] Model configuration docs omit lean system prompt default scope and model exceptions
- Add "Always allow globally" option to permission prompts
- Server-side model upgrade (Opus 4.7→4.8) wedges in-flight sessions with `thinking blocks cannot be modified` 400
- [DOCS] AskUserQuestion docs missing multiple-choice prompt decision threshold
- [DOCS] Agent view docs omit shell-command background session launch syntax
- [DOCS] Agent view dispatch input docs incorrectly imply `/logout` dispatches as a prompt
- [DOCS] Claude in Chrome docs omit connected-browser selection behavior
- [DOCS] Plugin docs omit `defaultEnabled: false` for opt-in plugins
- Feature Request: Customizable chat text colors for user and assistant messages
- [DOCS] `/plugin` Discover tab docs omit directory-based suggested plugin pins
- VSCode Chrome integration silently fails: 3 distinct bugs
- [DOCS] MCP stdio docs omit session environment variables
- [Bug] Anthropic API error on second request within session with Claude Opus 4.8
- Cowork emits a blank session "index" handoff on focus when a CLI session is paused awaiting input
- [DOCS] MCP docs omit `claude mcp list/get` pending-approval output for unapproved project servers
- [BUG] /compact fails with 400 error when last assistant turn contains thinking blocks
- [DOCS] `/claude-api` docs omit Opus 4.8 migration guidance
- [DOCS] Fast mode docs still recommend deprecated Opus 4.6 override variable
- [DOCS] Bash tool docs omit `$TMPDIR` consistency across sandboxed and unsandboxed commands
- [Bug] Anthropic API Error: 400 Bad Request on Extended Thinking
- [DOCS] Background session docs omit worktree-isolation behavior for spawned subagents
- Built-in mechanistic self-verification of verifiable claims (symmetric to the auto permission gate)
- [DOCS] Worktree docs do not clarify `worktree.baseRef: "head"` inside linked worktrees
- [BUG] Excessive RAM usage with multiple parallel chats (~10 sessions → 30 GB memory pressure, macOS OOM)
- [DOCS] Managed MCP policy docs omit invalid `allowedMcpServers`/`deniedMcpServers` entry behavior
- [DOCS] Effort docs omit `CLAUDE_CODE_ALWAYS_ENABLE_EFFORT` unsupported-model behavior
- Regression (2.1.147–2.1.150?): resuming an extended-thinking session after a CC update/model-switch → unrecoverable 400, session bricked
- [DOCS] Windows updater docs omit `claude.exe` in-use recovery guidance
- [DOCS] VS Code auto mode docs still tie mode-picker visibility to bypass-permissions setting
- [DOCS] MCP docs omit `/mcp` tool list and detail rendering behavior
- [DOCS] Fine-grained tool streaming docs still describe provider opt-in behavior
- bypassPermissions: session startup reads flat pref, GUI toggle writes per-account pref — they never sync
- [BUG] Claude Desktop Code tab causes disk write limit violation — 8.5GB in 11 min, macOS kills app (M5, v1.9659.1)
- Ultrareview v2.1.96: docs describe /tasks command + claude ultrareview --json subcommand that don't exist; findings hard to read after completion
- I'd be happy to help create a GitHub issue title, but I don't see the error message in your message. Could you please share the specific error you're encountering? That way I can generate an accurate and descriptive issue title for you.
- [BUG] Claude in Chrome `file_upload` rejects all scheduled-task sessions with misleading error (real cause: INVALID_SESSION)
- Extended thinking: signed thinking block 'cannot be modified' (400) permanently wedges session
- RTL text support for Hebrew (and Arabic) in Claude Code
- [Bug] Random errors occurring across multiple operations