pytorch - ✅(Solved) Fix Dynamo `TritonHOPifier.call_run` doesn't propagate kernel_source -> `AssertionError`: Can't construct an AttrSource without a valid base source [1 pull requests, 1 participants]
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pytorch/pytorch#178447•Fetched 2026-04-08 01:30:26
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Error Message
#!/usr/bin/env python3 """ Reproducer: TritonHOPifier.call_run doesn't propagate kernel_source
AssertionError: Can't construct an AttrSource without a valid base source"""
import sys import traceback
import torch import torch.nn as nn import triton import triton.language as tl
def early_config_prune(configs, named_args, **kwargs): """No-op config pruner. The existence of prune_configs_by triggers Dynamo's wrap_user_defined_obj, which needs kernel_source.""" return configs
@triton.autotune( configs=[ triton.Config({"BLOCK": 64}, num_warps=4, num_stages=1), triton.Config({"BLOCK": 128}, num_warps=4, num_stages=1), ], key=["N"], prune_configs_by={"early_config_prune": early_config_prune}, ) @triton.jit def add_kernel(X, Y, N, BLOCK: tl.constexpr): """Simple vector add-one kernel.""" pid = tl.program_id(0) offs = pid * BLOCK + tl.arange(0, BLOCK) mask = offs < N x = tl.load(X + offs, mask=mask) tl.store(Y + offs, x + 1.0, mask=mask)
def kernel_fn(x): """Launch the kernel via .run() instead of grid.
kernel.run() goes through TritonHOPifier.call_run, which creates a new
TritonKernelVariable WITHOUT kernel_source. Then call_triton_kernel hits
prune_configs_by and crashes in wrap_user_defined_obj.
In practice this path is triggered indirectly: kernel[grid]() syntax returns
a lambda that calls .run(), and Dynamo traces into that lambda on
recompilation after a graph break.
"""
N = x.shape[0]
y = torch.empty_like(x)
grid = (triton.cdiv(N, 64),)
add_kernel.run(x, y, N, grid=grid, warmup=False)
return yclass MyModule(nn.Module): def init(self, dim): super().init() self.linear = nn.Linear(dim, dim)
def forward(self, x):
x = self.linear(x)
x = kernel_fn(x.view(-1)).view(x.shape)
return xdef main(): print("=" * 72) print("Dynamo bug: call_run doesn't propagate kernel_source") print("=" * 72) print() print(f"Python: {sys.version.split()[0]}") print(f"PyTorch: {torch.version}") print(f"Triton: {triton.version}") if torch.cuda.is_available(): print(f"GPU: {torch.cuda.get_device_name(0)}") print()
if not torch.cuda.is_available():
print("ERROR: No GPU available.")
sys.exit(1)
device = "cuda"
dim = 64
model = MyModule(dim).to(device).eval()
model.compile(dynamic=None, fullgraph=False)
torch._dynamo.reset()
try:
with torch.no_grad():
print("Running compiled model with kernel.run() + prune_configs_by ...")
x = torch.randn(128, dim, device=device)
y = model(x)
print(f" UNEXPECTED PASS: {y.shape}")
print(" Bug may be fixed in this PyTorch version.")
except AssertionError as e:
if "AttrSource" in str(e) or "valid base source" in str(e):
print()
print(f"EXPECTED CRASH: {e}")
sys.exit(0)
else:
print(f"UNEXPECTED AssertionError: {e}")
traceback.print_exc()
sys.exit(1)
except Exception as e:
print(f"UNEXPECTED ERROR: {type(e).__name__}: {e}")
traceback.print_exc()
sys.exit(1)if name == "main": main()
Root Cause
When a Triton kernel with @triton.autotune + prune_configs_by is called via run() under torch.compile, Dynamo's TritonHOPifier.call_run creates a new TritonKernelVariable WITHOUT copying kernel_source from the original variable. The subsequent call_triton_kernel hits prune_configs_by, which calls wrap_user_defined_obj, which needs kernel_source to construct an AttrSource. Since kernel_source is None, the assertion fails.
In TritonHOPifier.call_run:
def call_run(self, variable, args, kwargs, tx):
...
return self.call_triton_kernel(
type(variable)(
kernel=variable.kernel, kernel_idx=variable.kernel_idx, grid=grid
), # <-- NO kernel_source!
args, kwargs, tx,
)Compare with DynamoTritonHOPifier.call_getitem:
def call_getitem(self, variable, args):
return type(variable)(
kernel=variable.kernel,
kernel_idx=variable.kernel_idx,
grid=args[0],
kernel_source=variable.source, # <-- propagated
)The fix is to propagate kernel_source in call_run (and the other call sites in call_triton_kernel that create new variables.
Fix Action
Fix / Workaround
Workarounds
Traceback (most recent call last): File "dynamo_double_compile_bug.py", line 194, in <module> main() File "dynamo_double_compile_bug.py", line 172, in main y = model(x) ^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1774, in _wrapped_call_impl return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/eval_frame.py", line 953, in compile_wrapper return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1787, in _call_impl return forward_call(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 2202, in call result = self._torchdynamo_orig_backend( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1945, in call result = self._inner_convert( ^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 707, in call result = _compile( ^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1752, in _compile guarded_code, tracer_output = compile_inner(code, one_graph, hooks) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_utils_internal.py", line 97, in wrapper_function return function(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1433, in compile_inner return _compile_inner(code, one_graph, hooks) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1467, in _compile_inner dynamo_output = compile_frame( ^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1341, in compile_frame bytecode, tracer_output = transform_code_object(code, transform) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/bytecode_transformation.py", line 1600, in transform_code_object tracer_output = transformations(instructions, code_options) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1313, in transform tracer_output = trace_frame( ^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 328, in _fn return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 838, in trace_frame run_tracer() File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 819, in run_tracer tracer.run() File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1654, in run while self.step(): ^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1334, in step self.dispatch_table[inst.opcode](self, inst) File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 866, in wrapper return inner_fn(self, inst) ^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3807, in CALL self._call(inst) File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3798, in _call self.call_function(fn, args, kwargs) File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1240, in call_function self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/lazy.py", line 229, in realize_and_forward return getattr(self.realize(), name)(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 685, in call_function return super().call_function(tx, args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 401, in call_function return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs) # type: ignore[attr-defined] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1262, in inline_user_function_return return InliningInstructionTranslator.inline_call(self, fn, args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/dynamo/symbolic_convert.py", line 4718, in inline_call return tracer.inline_call() ^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/dynamo/symbolic_convert.py", line 4935, in inline_call self.run() File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1654, in run while self.step(): ^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1334, in step self.dispatch_table[inst.opcode](self, inst) File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 866, in wrapper return inner_fn(self, inst) ^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3807, in CALL self._call(inst) File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3798, in _call self.call_function(fn, args, kwargs) File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1240, in call_function self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/misc.py", line 1148, in call_function return self.obj.call_method(tx, self.name, args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 2806, in call_method return dynamo_triton_hopifier_singleton.call_run(self, args, kwargs, tx) # type: ignore[return-value] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_higher_order_ops/triton_kernel_wrap.py", line 1634, in call_run return self.call_triton_kernel( ^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_higher_order_ops/triton_kernel_wrap.py", line 1839, in call_triton_kernel wrapped_early_configs_prune = self.wrap_user_defined_obj( ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 2652, in wrap_user_defined_obj tx, AttrSource(variable.kernel_source, f"{name}") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "<string>", line 5, in init File ".venv/lib/python3.12/site-packages/torch/_dynamo/source.py", line 288, in post_init assert self.base, "Can't construct an AttrSource without a valid base source" ^^^^^^^^^ AssertionError: Can't construct an AttrSource without a valid base source
CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 46 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 160 On-line CPU(s) list: 0-159 Vendor ID: GenuineIntel Model name: INTEL(R) XEON(R) PLATINUM 8568Y+ CPU family: 6 Model: 207 Thread(s) per core: 1 Core(s) per socket: 80 Socket(s): 2 Stepping: 2 BogoMIPS: 4600.00 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq dtes64 vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx_vnni avx512_bf16 wbnoinvd arat vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b fsrm md_clear serialize tsxldtrk avx512_fp16 arch_capabilities Virtualization: VT-x Hypervisor vendor: KVM Virtualization type: full L1d cache: 5 MiB (160 instances) L1i cache: 5 MiB (160 instances) L2 cache: 640 MiB (160 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-79 NUMA node1 CPU(s): 80-159 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Unknown: No mitigations Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; TSX disabled
PR fix notes
PR #178996: Preserve Triton kernel_source across HOPifier rewrites
- Repository: pytorch/pytorch
- Author: bobrenjc93
- State: closed | merged: False
- Link: https://github.com/pytorch/pytorch/pull/178996
Description (problem / solution / changelog)
Fix #178179
Root cause problem
Dynamo only seeded Triton kernel_source at the edge of tracing, but later Triton kernel rewrites recreated wrapper variables without carrying that source forward. Once @triton.autotune(..., prune_configs_by=...) wraps user-defined pruning helpers, wrap_user_defined_obj needs that source to build an AttrSource, and the missing base source triggers the assertion from the issue. The same invariant break also affects the related .run() path from #178447.
Proposed fix
Add a single helper in TritonHOPifier that recreates Triton kernel variables while preserving the existing kernel_source (or the original source when seeding it for the first time). Route .run() and every autotune/heuristics/pruning rewrite through that helper, seed TritonKernelVariable.kernel_source from source at construction, and let TraceableTritonKernelWrapper carry the same optional field so both HOPifier paths share the same interface. Add regression tests for the reported heuristics + autotune + prune combination and for the direct .run() path.
Why this is the right long term fix
The bug is not one specific decorator combination; it is a broken source-tracking invariant. Centralizing Triton variable recreation makes that invariant explicit in one place, which prevents the same omission from reappearing in future rewrite paths and fixes the related .run() variant with the same mechanism.
Drafted via Codex, published after manual review by @bobrenjc93
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @kadeng @muchulee8 @amjames @chauhang @aakhundov @coconutruben @jataylo @Lucaskabela @azahed98
Changed files
test/inductor/test_triton_kernels.py(modified, +67/-0)torch/_dynamo/variables/functions.py(modified, +3/-3)torch/_higher_order_ops/triton_kernel_wrap.py(modified, +59/-7)
Code Example
def call_run(self, variable, args, kwargs, tx):
...
return self.call_triton_kernel(
type(variable)(
kernel=variable.kernel, kernel_idx=variable.kernel_idx, grid=grid
), # <-- NO kernel_source!
args, kwargs, tx,
)
---
def call_getitem(self, variable, args):
return type(variable)(
kernel=variable.kernel,
kernel_idx=variable.kernel_idx,
grid=args[0],
kernel_source=variable.source, # <-- propagated
)
---
#!/usr/bin/env python3
"""
Reproducer: TritonHOPifier.call_run doesn't propagate kernel_source
AssertionError: Can't construct an AttrSource without a valid base source
"""
import sys
import traceback
import torch
import torch.nn as nn
import triton
import triton.language as tl
def early_config_prune(configs, named_args, **kwargs):
"""No-op config pruner. The existence of prune_configs_by triggers
Dynamo's wrap_user_defined_obj, which needs kernel_source."""
return configs
@triton.autotune(
configs=[
triton.Config({"BLOCK": 64}, num_warps=4, num_stages=1),
triton.Config({"BLOCK": 128}, num_warps=4, num_stages=1),
],
key=["N"],
prune_configs_by={"early_config_prune": early_config_prune},
)
@triton.jit
def add_kernel(X, Y, N, BLOCK: tl.constexpr):
"""Simple vector add-one kernel."""
pid = tl.program_id(0)
offs = pid * BLOCK + tl.arange(0, BLOCK)
mask = offs < N
x = tl.load(X + offs, mask=mask)
tl.store(Y + offs, x + 1.0, mask=mask)
def kernel_fn(x):
"""Launch the kernel via .run() instead of [grid]().
kernel.run() goes through TritonHOPifier.call_run, which creates a new
TritonKernelVariable WITHOUT kernel_source. Then call_triton_kernel hits
prune_configs_by and crashes in wrap_user_defined_obj.
In practice this path is triggered indirectly: kernel[grid]() syntax returns
a lambda that calls .run(), and Dynamo traces into that lambda on
recompilation after a graph break.
"""
N = x.shape[0]
y = torch.empty_like(x)
grid = (triton.cdiv(N, 64),)
add_kernel.run(x, y, N, grid=grid, warmup=False)
return y
class MyModule(nn.Module):
def __init__(self, dim):
super().__init__()
self.linear = nn.Linear(dim, dim)
def forward(self, x):
x = self.linear(x)
x = kernel_fn(x.view(-1)).view(x.shape)
return x
def main():
print("=" * 72)
print("Dynamo bug: call_run doesn't propagate kernel_source")
print("=" * 72)
print()
print(f"Python: {sys.version.split()[0]}")
print(f"PyTorch: {torch.__version__}")
print(f"Triton: {triton.__version__}")
if torch.cuda.is_available():
print(f"GPU: {torch.cuda.get_device_name(0)}")
print()
if not torch.cuda.is_available():
print("ERROR: No GPU available.")
sys.exit(1)
device = "cuda"
dim = 64
model = MyModule(dim).to(device).eval()
model.compile(dynamic=None, fullgraph=False)
torch._dynamo.reset()
try:
with torch.no_grad():
print("Running compiled model with kernel.run() + prune_configs_by ...")
x = torch.randn(128, dim, device=device)
y = model(x)
print(f" UNEXPECTED PASS: {y.shape}")
print(" Bug may be fixed in this PyTorch version.")
except AssertionError as e:
if "AttrSource" in str(e) or "valid base source" in str(e):
print()
print(f"EXPECTED CRASH: {e}")
sys.exit(0)
else:
print(f"UNEXPECTED AssertionError: {e}")
traceback.print_exc()
sys.exit(1)
except Exception as e:
print(f"UNEXPECTED ERROR: {type(e).__name__}: {e}")
traceback.print_exc()
sys.exit(1)
if __name__ == "__main__":
main()
---
from user code:
File "dynamo_double_compile_bug.py", line 140, in forward
x = kernel_fn(x.view(-1)).view(x.shape)
File "dynamo_double_compile_bug.py", line 129, in kernel_fn
add_kernel.run(x, y, N, grid=grid, warmup=False)
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"
Traceback (most recent call last):
File "dynamo_double_compile_bug.py", line 194, in <module>
main()
File "dynamo_double_compile_bug.py", line 172, in main
y = model(x)
^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1774, in _wrapped_call_impl
return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/eval_frame.py", line 953, in compile_wrapper
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1787, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 2202, in __call__
result = self._torchdynamo_orig_backend(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1945, in __call__
result = self._inner_convert(
^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 707, in __call__
result = _compile(
^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1752, in _compile
guarded_code, tracer_output = compile_inner(code, one_graph, hooks)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_utils_internal.py", line 97, in wrapper_function
return function(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1433, in compile_inner
return _compile_inner(code, one_graph, hooks)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1467, in _compile_inner
dynamo_output = compile_frame(
^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1341, in compile_frame
bytecode, tracer_output = transform_code_object(code, transform)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/bytecode_transformation.py", line 1600, in transform_code_object
tracer_output = transformations(instructions, code_options)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1313, in transform
tracer_output = trace_frame(
^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 328, in _fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 838, in trace_frame
run_tracer()
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 819, in run_tracer
tracer.run()
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1654, in run
while self.step():
^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1334, in step
self.dispatch_table[inst.opcode](self, inst)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 866, in wrapper
return inner_fn(self, inst)
^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3807, in CALL
self._call(inst)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3798, in _call
self.call_function(fn, args, kwargs)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1240, in call_function
self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/lazy.py", line 229, in realize_and_forward
return getattr(self.realize(), name)(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 685, in call_function
return super().call_function(tx, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 401, in call_function
return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs) # type: ignore[attr-defined]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1262, in inline_user_function_return
return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 4718, in inline_call
return tracer.inline_call_()
^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 4935, in inline_call_
self.run()
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1654, in run
while self.step():
^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1334, in step
self.dispatch_table[inst.opcode](self, inst)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 866, in wrapper
return inner_fn(self, inst)
^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3807, in CALL
self._call(inst)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3798, in _call
self.call_function(fn, args, kwargs)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1240, in call_function
self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/misc.py", line 1148, in call_function
return self.obj.call_method(tx, self.name, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 2806, in call_method
return dynamo_triton_hopifier_singleton.call_run(self, args, kwargs, tx) # type: ignore[return-value]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_higher_order_ops/triton_kernel_wrap.py", line 1634, in call_run
return self.call_triton_kernel(
^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_higher_order_ops/triton_kernel_wrap.py", line 1839, in call_triton_kernel
wrapped_early_configs_prune = self.wrap_user_defined_obj(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 2652, in wrap_user_defined_obj
tx, AttrSource(variable.kernel_source, f"{name}")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<string>", line 5, in __init__
File ".venv/lib/python3.12/site-packages/torch/_dynamo/source.py", line 288, in __post_init__
assert self.base, "Can't construct an AttrSource without a valid base source"
^^^^^^^^^
AssertionError: Can't construct an AttrSource without a valid base source
from user code:
File "dynamo_double_compile_bug.py", line 140, in forward
x = kernel_fn(x.view(-1)).view(x.shape)
File "dynamo_double_compile_bug.py", line 129, in kernel_fn
add_kernel.run(x, y, N, grid=grid, warmup=False)
---
Collecting environment information...
PyTorch version: 2.10.0+rocm7.1
Is debug build: False
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: 7.1.25424
OS: Ubuntu 24.04.3 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version: Could not collect
CMake version: version 3.28.3
Libc version: glibc-2.39
Python version: 3.12.3 (main, Jan 8 2026, 11:30:50) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.8.0-85-generic-x86_64-with-glibc2.39
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: AMD Instinct MI300X VF (gfx942:sramecc+:xnack-)
Nvidia driver version: Could not collect
cuDNN version: Could not collect
Is XPU available: False
HIP runtime version: 7.1.25424
MIOpen runtime version: 3.5.1
Is XNNPACK available: True
Caching allocator config: N/A
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 160
On-line CPU(s) list: 0-159
Vendor ID: GenuineIntel
Model name: INTEL(R) XEON(R) PLATINUM 8568Y+
CPU family: 6
Model: 207
Thread(s) per core: 1
Core(s) per socket: 80
Socket(s): 2
Stepping: 2
BogoMIPS: 4600.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq dtes64 vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx_vnni avx512_bf16 wbnoinvd arat vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b fsrm md_clear serialize tsxldtrk avx512_fp16 arch_capabilities
Virtualization: VT-x
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 5 MiB (160 instances)
L1i cache: 5 MiB (160 instances)
L2 cache: 640 MiB (160 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-79
NUMA node1 CPU(s): 80-159
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Unknown: No mitigations
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] pytorch-lightning==2.5.0
[pip3] torch==2.10.0+rocm7.1
[pip3] torchmetrics==1.8.2
[pip3] torchvision==0.25.0+rocm7.1
[pip3] triton==3.6.0
[conda] Could not collectRAW_BUFFERClick to expand / collapse
🐛 Describe the bug
When using torch.compile with a Triton kernel that had @triton.autotune with prune_configs_by used in two separate modules that were both compiled and had graph breaks, I hit AssertionError: Can't construct an AttrSource without a valid base source.
I asked Claude Code to root cause and create a minimal reproducer and this is its analysis plus reproducer. I haven't fact-checked everything, but it seems right and the reproducer does reproduce the same error.
Root cause
When a Triton kernel with @triton.autotune + prune_configs_by is called via run() under torch.compile, Dynamo's TritonHOPifier.call_run creates a new TritonKernelVariable WITHOUT copying kernel_source from the original variable. The subsequent call_triton_kernel hits prune_configs_by, which calls wrap_user_defined_obj, which needs kernel_source to construct an AttrSource. Since kernel_source is None, the assertion fails.
In TritonHOPifier.call_run:
def call_run(self, variable, args, kwargs, tx):
...
return self.call_triton_kernel(
type(variable)(
kernel=variable.kernel, kernel_idx=variable.kernel_idx, grid=grid
), # <-- NO kernel_source!
args, kwargs, tx,
)Compare with DynamoTritonHOPifier.call_getitem:
def call_getitem(self, variable, args):
return type(variable)(
kernel=variable.kernel,
kernel_idx=variable.kernel_idx,
grid=args[0],
kernel_source=variable.source, # <-- propagated
)The fix is to propagate kernel_source in call_run (and the other call sites in call_triton_kernel that create new variables.
How this manifest in practice
The reproducer uses run directly rather than kernel[grid](*args) to enable a minimal reproducer. This issue was hit in the wild with a kernel[grid](*args) call but it was really hard to turn that into a minimal reproducer. The .run() path was triggered because:
kernel[grid]callskernel.__getitem__(grid), which returns a lambda:lambda *args, **kwargs: self.run(grid=grid, warmup=False, *args, **kwargs)- Normally, Dynamo intercepts
kernel[grid](*args)as__getitem__+__call__, routing through call_getitem (which propagateskernel_source). - But when the kernel call is in a Dynamo "resume function" (created after a graph break from
@torch.compiler.disable), Dynamo sometimes traces INTO the__getitem__lambda and seesself.run(), routing throughcall_runinstead. - This only happens on recompilation (batch 2 with different shapes), because the resume function's compilation context differs from the original.
Using kernel.run() directly triggers the same underlying bug without needing the full complexity.
Environment
- PyTorch 2.10.0+rocm7.1 (also likely affects CUDA builds)
- Triton 3.6.0
- AMD MI300X (not hardware-specific)
Related
- The "ListVariable already tracked for mutation" bug (https://github.com/pytorch/pytorch/issues/177600) is at the same crash site but has a different root cause (
._wrapvs__call__). - The
@triton.heuristics+prune_configs_bybug (https://github.com/pytorch/pytorch/issues/178179) is also at the same site but caused by Heuristics unwrapping dropping kernel_source. - All three bugs share the same underlying issue: kernel_source is not consistently propagated when creating new TritonKernelVariable instances.
Workarounds
- Remove
prune_configs_byfrom@triton.autotune. - Add
@torch.compiler.disableto the function containing the kernel call.
#!/usr/bin/env python3
"""
Reproducer: TritonHOPifier.call_run doesn't propagate kernel_source
AssertionError: Can't construct an AttrSource without a valid base source
"""
import sys
import traceback
import torch
import torch.nn as nn
import triton
import triton.language as tl
def early_config_prune(configs, named_args, **kwargs):
"""No-op config pruner. The existence of prune_configs_by triggers
Dynamo's wrap_user_defined_obj, which needs kernel_source."""
return configs
@triton.autotune(
configs=[
triton.Config({"BLOCK": 64}, num_warps=4, num_stages=1),
triton.Config({"BLOCK": 128}, num_warps=4, num_stages=1),
],
key=["N"],
prune_configs_by={"early_config_prune": early_config_prune},
)
@triton.jit
def add_kernel(X, Y, N, BLOCK: tl.constexpr):
"""Simple vector add-one kernel."""
pid = tl.program_id(0)
offs = pid * BLOCK + tl.arange(0, BLOCK)
mask = offs < N
x = tl.load(X + offs, mask=mask)
tl.store(Y + offs, x + 1.0, mask=mask)
def kernel_fn(x):
"""Launch the kernel via .run() instead of [grid]().
kernel.run() goes through TritonHOPifier.call_run, which creates a new
TritonKernelVariable WITHOUT kernel_source. Then call_triton_kernel hits
prune_configs_by and crashes in wrap_user_defined_obj.
In practice this path is triggered indirectly: kernel[grid]() syntax returns
a lambda that calls .run(), and Dynamo traces into that lambda on
recompilation after a graph break.
"""
N = x.shape[0]
y = torch.empty_like(x)
grid = (triton.cdiv(N, 64),)
add_kernel.run(x, y, N, grid=grid, warmup=False)
return y
class MyModule(nn.Module):
def __init__(self, dim):
super().__init__()
self.linear = nn.Linear(dim, dim)
def forward(self, x):
x = self.linear(x)
x = kernel_fn(x.view(-1)).view(x.shape)
return x
def main():
print("=" * 72)
print("Dynamo bug: call_run doesn't propagate kernel_source")
print("=" * 72)
print()
print(f"Python: {sys.version.split()[0]}")
print(f"PyTorch: {torch.__version__}")
print(f"Triton: {triton.__version__}")
if torch.cuda.is_available():
print(f"GPU: {torch.cuda.get_device_name(0)}")
print()
if not torch.cuda.is_available():
print("ERROR: No GPU available.")
sys.exit(1)
device = "cuda"
dim = 64
model = MyModule(dim).to(device).eval()
model.compile(dynamic=None, fullgraph=False)
torch._dynamo.reset()
try:
with torch.no_grad():
print("Running compiled model with kernel.run() + prune_configs_by ...")
x = torch.randn(128, dim, device=device)
y = model(x)
print(f" UNEXPECTED PASS: {y.shape}")
print(" Bug may be fixed in this PyTorch version.")
except AssertionError as e:
if "AttrSource" in str(e) or "valid base source" in str(e):
print()
print(f"EXPECTED CRASH: {e}")
sys.exit(0)
else:
print(f"UNEXPECTED AssertionError: {e}")
traceback.print_exc()
sys.exit(1)
except Exception as e:
print(f"UNEXPECTED ERROR: {type(e).__name__}: {e}")
traceback.print_exc()
sys.exit(1)
if __name__ == "__main__":
main()Error logs
<details><summary>Error logs</summary>from user code:
File "dynamo_double_compile_bug.py", line 140, in forward
x = kernel_fn(x.view(-1)).view(x.shape)
File "dynamo_double_compile_bug.py", line 129, in kernel_fn
add_kernel.run(x, y, N, grid=grid, warmup=False)
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"
Traceback (most recent call last):
File "dynamo_double_compile_bug.py", line 194, in <module>
main()
File "dynamo_double_compile_bug.py", line 172, in main
y = model(x)
^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1774, in _wrapped_call_impl
return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/eval_frame.py", line 953, in compile_wrapper
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1787, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 2202, in __call__
result = self._torchdynamo_orig_backend(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1945, in __call__
result = self._inner_convert(
^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 707, in __call__
result = _compile(
^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1752, in _compile
guarded_code, tracer_output = compile_inner(code, one_graph, hooks)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_utils_internal.py", line 97, in wrapper_function
return function(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1433, in compile_inner
return _compile_inner(code, one_graph, hooks)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1467, in _compile_inner
dynamo_output = compile_frame(
^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1341, in compile_frame
bytecode, tracer_output = transform_code_object(code, transform)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/bytecode_transformation.py", line 1600, in transform_code_object
tracer_output = transformations(instructions, code_options)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1313, in transform
tracer_output = trace_frame(
^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 328, in _fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 838, in trace_frame
run_tracer()
File ".venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 819, in run_tracer
tracer.run()
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1654, in run
while self.step():
^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1334, in step
self.dispatch_table[inst.opcode](self, inst)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 866, in wrapper
return inner_fn(self, inst)
^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3807, in CALL
self._call(inst)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3798, in _call
self.call_function(fn, args, kwargs)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1240, in call_function
self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/lazy.py", line 229, in realize_and_forward
return getattr(self.realize(), name)(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 685, in call_function
return super().call_function(tx, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 401, in call_function
return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs) # type: ignore[attr-defined]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1262, in inline_user_function_return
return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 4718, in inline_call
return tracer.inline_call_()
^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 4935, in inline_call_
self.run()
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1654, in run
while self.step():
^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1334, in step
self.dispatch_table[inst.opcode](self, inst)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 866, in wrapper
return inner_fn(self, inst)
^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3807, in CALL
self._call(inst)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 3798, in _call
self.call_function(fn, args, kwargs)
File ".venv/lib/python3.12/site-packages/torch/_dynamo/symbolic_convert.py", line 1240, in call_function
self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/misc.py", line 1148, in call_function
return self.obj.call_method(tx, self.name, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 2806, in call_method
return dynamo_triton_hopifier_singleton.call_run(self, args, kwargs, tx) # type: ignore[return-value]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_higher_order_ops/triton_kernel_wrap.py", line 1634, in call_run
return self.call_triton_kernel(
^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_higher_order_ops/triton_kernel_wrap.py", line 1839, in call_triton_kernel
wrapped_early_configs_prune = self.wrap_user_defined_obj(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/torch/_dynamo/variables/functions.py", line 2652, in wrap_user_defined_obj
tx, AttrSource(variable.kernel_source, f"{name}")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<string>", line 5, in __init__
File ".venv/lib/python3.12/site-packages/torch/_dynamo/source.py", line 288, in __post_init__
assert self.base, "Can't construct an AttrSource without a valid base source"
^^^^^^^^^
AssertionError: Can't construct an AttrSource without a valid base source
from user code:
File "dynamo_double_compile_bug.py", line 140, in forward
x = kernel_fn(x.view(-1)).view(x.shape)
File "dynamo_double_compile_bug.py", line 129, in kernel_fn
add_kernel.run(x, y, N, grid=grid, warmup=False)Versions
<details><summary>env</summary>Collecting environment information...
PyTorch version: 2.10.0+rocm7.1
Is debug build: False
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: 7.1.25424
OS: Ubuntu 24.04.3 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version: Could not collect
CMake version: version 3.28.3
Libc version: glibc-2.39
Python version: 3.12.3 (main, Jan 8 2026, 11:30:50) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.8.0-85-generic-x86_64-with-glibc2.39
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: AMD Instinct MI300X VF (gfx942:sramecc+:xnack-)
Nvidia driver version: Could not collect
cuDNN version: Could not collect
Is XPU available: False
HIP runtime version: 7.1.25424
MIOpen runtime version: 3.5.1
Is XNNPACK available: True
Caching allocator config: N/A
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 160
On-line CPU(s) list: 0-159
Vendor ID: GenuineIntel
Model name: INTEL(R) XEON(R) PLATINUM 8568Y+
CPU family: 6
Model: 207
Thread(s) per core: 1
Core(s) per socket: 80
Socket(s): 2
Stepping: 2
BogoMIPS: 4600.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq dtes64 vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx_vnni avx512_bf16 wbnoinvd arat vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b fsrm md_clear serialize tsxldtrk avx512_fp16 arch_capabilities
Virtualization: VT-x
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 5 MiB (160 instances)
L1i cache: 5 MiB (160 instances)
L2 cache: 640 MiB (160 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-79
NUMA node1 CPU(s): 80-159
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Unknown: No mitigations
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] pytorch-lightning==2.5.0
[pip3] torch==2.10.0+rocm7.1
[pip3] torchmetrics==1.8.2
[pip3] torchvision==0.25.0+rocm7.1
[pip3] triton==3.6.0
[conda] Could not collectcc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @kadeng @amjames @Lucaskabela @jataylo @oulgen @aakhundov @davidberard98
extent analysis
Fix Plan
To fix the issue, we need to propagate kernel_source in TritonHOPifier.call_run.
Here are the steps:
- Modify the
call_runmethod inTritonHOPifierto includekernel_sourcewhen creating a newTritonKernelVariable. - Update the
call_triton_kernelmethod to handle the newkernel_sourceattribute.
Example code:
def call_run(self, variable, args, kwargs, tx):
...
return self.call_triton_kernel(
type(variable)(
kernel=variable.kernel,
kernel_idx=variable.kernel_idx,
grid=grid,
kernel_source=variable.kernel_source # <-- Add this line
),
args, kwargs, tx,
)Verification
To verify that the fix worked, run the provided reproducer code again. If the fix is correct, the AssertionError should be resolved, and the code should execute without errors.
Extra Tips
- Make sure to update the
TritonHOPifierclass with the modifiedcall_runmethod. - If you're using a version of PyTorch that doesn't have the
TritonHOPifierclass, you may need to update your PyTorch version or apply the fix manually. - This fix assumes that the
kernel_sourceattribute is available in thevariableobject. If this attribute is not available, you may need to modify the fix accordingly.
Vote matrix · Quick signals
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×6Another batch ranked right after the header list — different links, same matching logic.
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- [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