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Pyrefly suppressions 2 (#165692)

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This is the last directory to opt in for the regular mypy.ini file. Will put up a diff to remove unused ignores before making sure we're also type checking all the files in the mypy strict configurations

Test plan:
dmypy restart && python3 scripts/lintrunner.py -a
pyrefly check

step 1: delete lines in the pyrefly.toml file from the project-excludes field
step 2: run pyrefly check
step 3: add suppressions, clean up unused suppressions
before: https://gist.github.com/maggiemoss/4b3bf2037014e116bc00706a16aef199

after:
INFO 0 errors (6,884 ignored)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/165692
Approved by: https://github.com/oulgen
This commit is contained in:
Maggie Moss
2025-10-17 04:15:22 +00:00
committed by PyTorch MergeBot
parent fcbde24c1c
commit 43d78423ac
15 changed files with 54 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
pyrefly.toml
View File

@ -22,8 +22,10 @@ project-includes = [
project-excludes = [
# ==== below will be enabled directory by directory ====
# ==== to test Pyrefly on a specific directory, simply comment it out ====
"torch/_inductor/runtime",
"torch/_inductor/codegen/triton.py",
"torch/_inductor/runtime/triton_helpers.py",
"torch/_inductor/runtime/triton_heuristics.py",
"torch/_inductor/runtime/halide_helpers.py",
# formatting issues, will turn on after adjusting where suppressions can be
# in import statements
"torch/linalg/__init__.py",

1
torch/_inductor/codegen/common.py
View File

@ -1739,6 +1739,7 @@ class KernelArgs:
for outer, inner in chain(
# pyrefly: ignore # bad-argument-type
self.input_buffers.items(),
# pyrefly: ignore # bad-argument-type
self.output_buffers.items(),
):
if outer in self.inplace_buffers or isinstance(inner, RemovedArg):

2
torch/_inductor/codegen/cpp_gemm_template.py
View File

@ -1480,6 +1480,7 @@ class CppGemmTemplate(CppTemplate):
gemm_output_buffer = ir.Buffer(
# pyrefly: ignore # missing-attribute
name=gemm_output_name,
# pyrefly: ignore # missing-attribute
layout=template_buffer.layout,
)
current_input_buffer = gemm_output_buffer
@ -1503,6 +1504,7 @@ class CppGemmTemplate(CppTemplate):
current_input_buffer = ir.Buffer(
# pyrefly: ignore # missing-attribute
name=buffer_name,
# pyrefly: ignore # missing-attribute
layout=template_buffer.layout,
)

1
torch/_inductor/codegen/cpp_wrapper_gpu.py
View File

@ -824,6 +824,7 @@ class CppWrapperGpu(CppWrapperCpu):
call_args, arg_types = self.prepare_triton_wrapper_args(
# pyrefly: ignore # bad-argument-type
call_args,
# pyrefly: ignore # bad-argument-type
arg_types,
)
wrapper_name = f"call_{kernel_name}"

2
torch/_inductor/codegen/mps.py
View File

@ -683,6 +683,7 @@ class MetalKernel(SIMDKernel):
# pyrefly: ignore # missing-argument
t
for t in self.range_tree_nodes.values()
# pyrefly: ignore # missing-argument
if t.is_reduction
)
cmp_op = ">" if reduction_type == "argmax" else "<"
@ -865,6 +866,7 @@ class MetalKernel(SIMDKernel):
# pyrefly: ignore # missing-argument
t.numel
for t in self.range_trees
# pyrefly: ignore # missing-argument
if t.is_reduction
)
# If using dynamic shapes, set the threadgroup size to be the

1
torch/_inductor/codegen/simd.py
View File

@ -968,6 +968,7 @@ class SIMDKernel(Kernel[CSEVariableType], Generic[CSEVariableType]):
# pyrefly: ignore # missing-argument
t
for t in self.range_trees
# pyrefly: ignore # missing-argument
if not t.is_reduction or self.inside_reduction
]

1
torch/_inductor/codegen/wrapper_fxir.py
View File

@ -1004,6 +1004,7 @@ class FxConverter:
# pyrefly: ignore # missing-attribute
call_kwargs[key]
for key in signature
# pyrefly: ignore # missing-attribute
if key not in cfg.kwargs
]

8
torch/_inductor/runtime/autotune_cache.py
View File

@ -275,8 +275,11 @@ class AutotuneCache:
triton_cache_hash: str | None = None,
) -> None:
data = {
# pyrefly: ignore # missing-attribute
**config.kwargs,
# pyrefly: ignore # missing-attribute
"num_warps": config.num_warps,
# pyrefly: ignore # missing-attribute
"num_stages": config.num_stages,
"configs_hash": self.configs_hash,
"found_by_coordesc": found_by_coordesc,
@ -570,15 +573,20 @@ def _load_cached_autotuning(
)
# Create the triton_config with the appropriate arguments
# pyrefly: ignore # bad-argument-count
triton_config = Config(best_config, **config_args)
# pyrefly: ignore # missing-attribute
triton_config.found_by_coordesc = True
return triton_config
matching_configs = [
cfg
for cfg in configs
# pyrefly: ignore # missing-attribute
if all(val == best_config.get(key) for key, val in cfg.kwargs.items())
# pyrefly: ignore # missing-attribute
and cfg.num_warps == best_config.get("num_warps")
# pyrefly: ignore # missing-attribute
and cfg.num_stages == best_config.get("num_stages")
]
if len(matching_configs) != 1:

2
torch/_inductor/runtime/benchmarking.py
View File

@ -123,6 +123,7 @@ class Benchmarker:
- The runtime of `fn(*fn_args, **fn_kwargs)`, in milliseconds.
"""
inferred_device = None
# pyrefly: ignore # bad-assignment
for arg_or_kwarg in chain(fn_args, fn_kwargs.values()):
if not isinstance(arg_or_kwarg, torch.Tensor):
continue
@ -196,6 +197,7 @@ class TritonBenchmarker(Benchmarker):
@may_distort_benchmarking_result
@time_and_count
# pyrefly: ignore # bad-override
def benchmark_gpu(
self: Self,
_callable: Callable[[], Any],

1
torch/_inductor/runtime/caching/implementations.py
View File

@ -190,6 +190,7 @@ class _OnDiskCacheImpl(_CacheImpl):
Defaults to empty string if not specified.
"""
self._cache_dir: Path = self._base_dir / (sub_dir or "")
# pyrefly: ignore # bad-assignment
self._flock: FileLock = FileLock(str(self._cache_dir / "dir.lock"))
@property

11
torch/_inductor/runtime/coordinate_descent_tuner.py
View File

@ -186,6 +186,7 @@ class CoordescTuner:
def check_all_tuning_directions(
self,
# pyrefly: ignore # missing-attribute
func: Callable[["triton.Config"], float],
best_config,
best_timing,
@ -255,10 +256,12 @@ class CoordescTuner:
def autotune(
self,
func: Callable[["triton.Config"], float],
baseline_config: "triton.Config",
baseline_timing: float | None = None,
) -> "triton.Config":
func: Callable[
["triton.Config"], float # pyrefly: ignore # missing-attribute
],
baseline_config: "triton.Config", # pyrefly: ignore # missing-attribute
baseline_timing: float | None = None, # pyrefly: ignore # missing-attribute
) -> "triton.Config": # pyrefly: ignore # missing-attribute
if baseline_timing is None:
baseline_timing = self.call_func(func, baseline_config)

2
torch/_inductor/runtime/hints.py
View File

@ -88,11 +88,13 @@ if has_triton_package():
divisible_by_16=None,
equal_to_1=None,
):
# pyrefly: ignore # not-iterable
return {(x,): [["tt.divisibility", 16]] for x in divisible_by_16}
else:
# Define a namedtuple as a fallback when AttrsDescriptor is not available
AttrsDescriptorWrapper = collections.namedtuple( # type: ignore[no-redef, name-match]
# pyrefly: ignore # invalid-argument
"AttrsDescriptor",
["divisible_by_16", "equal_to_1"],
defaults=[(), ()],

5
torch/_inductor/runtime/runtime_utils.py
View File

@ -68,8 +68,11 @@ def triton_config_to_hashable(cfg: Config) -> Hashable:
Convert triton config to a tuple that can uniquely identify it. We can use
the return value as a dictionary key.
"""
# pyrefly: ignore # missing-attribute
items = sorted(cfg.kwargs.items())
# pyrefly: ignore # missing-attribute
items.append(("num_warps", cfg.num_warps))
# pyrefly: ignore # missing-attribute
items.append(("num_stages", cfg.num_stages))
return tuple(items)
@ -103,6 +106,7 @@ def get_max_y_grid() -> int:
try:
# pyrefly: ignore # import-error
import colorama
HAS_COLORAMA = True
@ -114,6 +118,7 @@ except ModuleNotFoundError:
if HAS_COLORAMA:
def _color_text(msg: str, color: str) -> str:
# pyrefly: ignore # missing-attribute
return getattr(colorama.Fore, color.upper()) + msg + colorama.Fore.RESET
else:

17
torch/_inductor/runtime/static_cuda_launcher.py
View File

@ -34,21 +34,29 @@ class StaticallyLaunchedCudaKernel:
"""
def __init__(self, kernel: CompiledKernel) -> None:
# pyrefly: ignore # missing-attribute
self.name = kernel.src.fn.__name__
# pyrefly: ignore # missing-attribute
self.cubin_raw = kernel.asm.get("cubin", None)
# pyrefly: ignore # missing-attribute
self.cubin_path = kernel._cubin_path
# Used by torch.compile to filter constants in older triton versions
# pyrefly: ignore # missing-attribute
self.arg_names = kernel.src.fn.arg_names
# Const exprs that are declared by the triton kernel directly
# Used to generate the kernel launcher's def args
# pyrefly: ignore # missing-attribute
self.declared_constexprs = kernel.src.fn.constexprs
# pyrefly: ignore # missing-attribute
self.hash = kernel.hash
if triton_knobs is None:
# pyrefly: ignore # missing-attribute
launch_enter = kernel.__class__.launch_enter_hook
# pyrefly: ignore # missing-attribute
launch_exit = kernel.__class__.launch_exit_hook
else:
launch_enter = triton_knobs.runtime.launch_enter_hook
@ -70,12 +78,15 @@ class StaticallyLaunchedCudaKernel:
raise NotImplementedError(
"We don't support launch enter or launch exit hooks"
)
# pyrefly: ignore # missing-attribute
self.num_warps = kernel.metadata.num_warps
self.shared = (
# pyrefly: ignore # missing-attribute
kernel.shared if hasattr(kernel, "shared") else kernel.metadata.shared
)
def needs_scratch_arg(scratch_name: str, param_name: str) -> bool:
# pyrefly: ignore # missing-attribute
if hasattr(kernel.metadata, param_name):
if getattr(kernel.metadata, param_name) > 0:
raise NotImplementedError(
@ -91,6 +102,7 @@ class StaticallyLaunchedCudaKernel:
# same situation for profile scratch - triton-lang/triton#7258
self.has_profile_scratch = needs_scratch_arg("Profile", "profile_scratch_size")
# pyrefly: ignore # missing-attribute
self.arg_tys = self.arg_ty_from_signature(kernel.src)
self.function: int | None = None # Loaded by load_kernel(on the parent process)
num_ctas = 1
@ -170,6 +182,7 @@ class StaticallyLaunchedCudaKernel:
def arg_ty_from_signature(self, src: ASTSource) -> str:
def index_key(i: Any) -> int:
if isinstance(i, str):
# pyrefly: ignore # missing-attribute
return src.fn.arg_names.index(i)
elif isinstance(i, tuple):
# In triton 3.3, src.fn.constants has tuples as a key
@ -177,6 +190,7 @@ class StaticallyLaunchedCudaKernel:
else:
return i
# pyrefly: ignore # missing-attribute
signature = {index_key(key): value for key, value in src.signature.items()}
# Triton uses these as the main way to filter out constants passed to their cubin
constants = [index_key(key) for key in getattr(src, "constants", dict())]
@ -198,6 +212,7 @@ class StaticallyLaunchedCudaKernel:
if ty == "constexpr" or i in constants:
pass
else:
# pyrefly: ignore # bad-argument-type
params.append(self.extract_type(ty))
return "".join(params)
@ -235,6 +250,7 @@ class StaticallyLaunchedCudaKernel:
if has_scratch:
arg_tys = arg_tys + "O"
args = (*args, None)
# pyrefly: ignore # bad-argument-type
assert len(args) == len(arg_tys)
# TODO: can handle grid functions here or in C++, so
@ -247,6 +263,7 @@ class StaticallyLaunchedCudaKernel:
self.num_warps,
self.shared,
arg_tys,
# pyrefly: ignore # bad-argument-type
args,
stream,
)

1
torch/fx/experimental/proxy_tensor.py
View File

@ -421,6 +421,7 @@ def get_proxy_slot(
else:
# Attempt to build it from first principles.
_build_proxy_for_sym_expr(tracer, obj.node.expr, obj)
# pyrefly: ignore # no-matching-overload
value = tracker.get(obj)
if value is None: