forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathpyrefly.toml
More file actions
139 lines (138 loc) · 4.75 KB
/
pyrefly.toml
File metadata and controls
139 lines (138 loc) · 4.75 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
# A Pyrefly configuration for PyTorch
# Based on https://github.com/pytorch/pytorch/blob/main/mypy.ini
python-version = "3.12"
project-includes = [
"torch",
"caffe2",
"test/test_bundled_images.py",
"test/test_bundled_inputs.py",
"test/test_complex.py",
"test/test_datapipe.py",
# "test/test_futures.py", # uncomment when enabling pyrefly
"test/test_numpy_interop.py",
# We exclude test_torch.py because it is full of errors, but most functions lack type signatures,
# and mypy.ini specifies `check_untyped_defs = False` for this file.
# If you check even the unannotated stuff mypy produces 322 errors.
# "test/test_torch.py",
"test/test_type_hints.py",
"test/test_type_info.py",
# "test/test_utils.py", # uncomment when enabling pyrefly
]
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",
# formatting issues, will turn on after adjusting where suppressions can be
# in import statements
"torch/linalg/__init__.py",
"torch/package/importer.py",
"torch/package/_package_pickler.py",
"torch/jit/annotations.py",
"torch/utils/data/datapipes/_typing.py",
"torch/nn/functional.py",
"torch/_export/utils.py",
"torch/fx/experimental/unification/multipledispatch/__init__.py",
"torch/nn/modules/__init__.py",
"torch/nn/modules/rnn.py", # only remove when parsing errors are fixed
"torch/_inductor/codecache.py",
"torch/distributed/elastic/metrics/__init__.py",
"torch/_inductor/fx_passes/bucketing.py",
# ====
"benchmarks/instruction_counts/main.py",
"benchmarks/instruction_counts/definitions/setup.py",
"benchmarks/instruction_counts/applications/ci.py",
"benchmarks/instruction_counts/core/api.py",
"benchmarks/instruction_counts/core/expand.py",
"benchmarks/instruction_counts/core/types.py",
"benchmarks/instruction_counts/core/utils.py",
"benchmarks/instruction_counts/definitions/standard.py",
"benchmarks/instruction_counts/definitions/setup.py",
"benchmarks/instruction_counts/execution/runner.py",
"benchmarks/instruction_counts/execution/work.py",
"torch/include/**",
"torch/csrc/**",
"torch/distributed/elastic/agent/server/api.py",
"torch/testing/_internal/**",
"torch/distributed/fsdp/fully_sharded_data_parallel.py",
"torch/ao/quantization/pt2e/_affine_quantization.py",
"torch/nn/modules/pooling.py",
"torch/nn/parallel/_functions.py",
"torch/_appdirs.py",
"torch/multiprocessing/pool.py",
"torch/overrides.py",
"*/__pycache__/**",
"*/.*",
]
ignore-missing-imports = [
"torch._C._jit_tree_views.*",
"torch.for_onnx.onnx.*",
"torch.ao.quantization.experimental.apot_utils.*",
"torch.ao.quantization.experimental.quantizer.*",
"torch.ao.quantization.experimental.observer.*",
"torch.ao.quantization.experimental.APoT_tensor.*",
"torch.ao.quantization.experimental.fake_quantize_function.*",
"torch.ao.quantization.experimental.fake_quantize.*",
"triton.*",
"tensorflow.*",
"tensorboard.*",
"matplotlib.*",
"numpy.*",
"sympy.*",
"hypothesis.*",
"tqdm.*",
"multiprocessing.*",
"setuptools.*",
"distutils.*",
"nvd3.*",
"future.utils.*",
"past.builtins.*",
"numba.*",
"PIL.*",
"moviepy.*",
"cv2.*",
"torchvision.*",
"pycuda.*",
"tensorrt.*",
"tornado.*",
"pydot.*",
"networkx.*",
"scipy.*",
"IPython.*",
"google.protobuf.textformat.*",
"lmdb.*",
"mpi4py.*",
"skimage.*",
"librosa.*",
"mypy.*",
"xml.*",
"boto3.*",
"dill.*",
"usort.*",
"cutlass_library.*",
"deeplearning.*",
"einops.*",
"libfb.*",
"torch.fb.*",
"torch.*.fb.*",
"torch_xla.*",
"onnx.*",
"onnxruntime.*",
"onnxscript.*",
"redis.*",
]
# By default, mypy does not check untyped definitions.
# However, mypy has a configuration called check_untyped_defs which is used
# to typecheck the interior of untyped functions.
untyped-def-behavior = "check-and-infer-return-any"
# In lots of places they define their attributes in `_init` or similar.
# https://github.com/pytorch/pytorch/blob/75f3e5a88df60caef27fd9c9df3fd51161378fcc/torch/fx/experimental/symbolic_shapes.py#L3632C1-L3633C1
errors.implicitly-defined-attribute = false
# In many methods that are overridden, parameters are renamed.
# We can come up with a codemod for this in the future
errors.bad-param-name-override = false
# Mypy doesn't require that imports are explicitly imported, so be compatible with that.
# Might be a good idea to turn this on in future.
errors.implicit-import = false
permissive-ignores = true
replace-imports-with-any = ["!sympy.printing.*", "sympy.*", "onnxscript.onnx_opset.*"]