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Add pyrefly suppressions (3/n) (#164588)
Adds suppressions to pyrefly will typecheck clean: https://github.com/pytorch/pytorch/issues/163283 Test plan: dmypy restart && python3 scripts/lintrunner.py -a pyrefly check step 1: uncomment lines in the pyrefly.toml file step 2: run pyrefly check step 3: add suppressions, clean up unused suppressions before: https://gist.github.com/maggiemoss/bb31574ac8a59893c9cf52189e67bb2d after: 0 errors (1,970 ignored) Pull Request resolved: https://github.com/pytorch/pytorch/pull/164588 Approved by: https://github.com/oulgen
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Maggie Moss
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PyTorch MergeBot
PyTorch MergeBot
parent
e438db2546
commit
f414aa8e0d
@ -404,7 +404,9 @@ class FakeTensorConverter:
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with no_dispatch():
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return FakeTensor(
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fake_mode,
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# pyrefly: ignore # bad-argument-type
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make_meta_t(),
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# pyrefly: ignore # bad-argument-type
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device,
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# TODO: callback might be used in recursive contexts, in
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# which case using t is wrong! BUG!
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@ -679,6 +681,7 @@ class FakeTensor(Tensor):
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_mode_key = torch._C._TorchDispatchModeKey.FAKE
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@property
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# pyrefly: ignore # bad-override
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def device(self) -> torch.device:
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if self.fake_mode.in_kernel_invocation:
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return torch.device("meta")
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@ -706,6 +709,7 @@ class FakeTensor(Tensor):
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# We don't support named tensors; graph break
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@property
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# pyrefly: ignore # bad-override
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def names(self) -> list[str]:
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raise UnsupportedFakeTensorException(
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"torch.compile doesn't support named tensors"
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@ -764,6 +768,7 @@ class FakeTensor(Tensor):
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)
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else:
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device = torch.device(f"{device.type}:0")
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# pyrefly: ignore # read-only
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self.fake_device = device
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self.fake_mode = fake_mode
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self.constant = constant
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@ -1493,6 +1498,7 @@ class FakeTensorMode(TorchDispatchMode):
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# Do this dispatch outside the above except handler so if it
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# generates its own exception there won't be a __context__ caused by
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# the caching mechanism.
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# pyrefly: ignore # bad-argument-type
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return self._dispatch_impl(func, types, args, kwargs)
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assert state is not None
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@ -1510,22 +1516,27 @@ class FakeTensorMode(TorchDispatchMode):
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# This represents a negative cache entry - we already saw that the
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# output is uncachable. Compute it from first principals.
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FakeTensorMode.cache_bypasses[entry.reason] += 1
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# pyrefly: ignore # bad-argument-type
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return self._dispatch_impl(func, types, args, kwargs)
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# We have a cache entry.
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# pyrefly: ignore # bad-argument-type
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output = self._output_from_cache_entry(state, entry, key, func, args)
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FakeTensorMode.cache_hits += 1
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if self.cache_crosscheck_enabled:
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# For debugging / testing: Validate that the output synthesized
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# from the cache matches the output created by normal dispatch.
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with disable_fake_tensor_cache(self):
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# pyrefly: ignore # bad-argument-type
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self._crosscheck_cache_output(output, func, types, args, kwargs)
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return output
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# We don't have a cache entry.
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# pyrefly: ignore # bad-argument-type
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output = self._dispatch_impl(func, types, args, kwargs)
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try:
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# pyrefly: ignore # bad-argument-type
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self._validate_cache_key(func, args, kwargs)
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except _BypassDispatchCache as e:
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# We ran "extra" checks on the cache key and determined that it's no
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@ -1545,6 +1556,7 @@ class FakeTensorMode(TorchDispatchMode):
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return output
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try:
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# pyrefly: ignore # bad-argument-type
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entry = self._make_cache_entry(state, key, func, args, kwargs, output)
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except _BypassDispatchCache as e:
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# We had trouble making the cache entry. Record the reason and mark
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@ -1587,13 +1599,16 @@ class FakeTensorMode(TorchDispatchMode):
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if state.known_symbols:
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# If there are symbols then include the epoch - this is really more
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# of a Shape env var which lives on the FakeTensorMode.
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# pyrefly: ignore # bad-argument-type
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key_values.append(self.epoch)
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# Collect the id_hashed objects to attach a weakref finalize later
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id_hashed_objects: list[object] = []
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# Translate any FakeTensor args to metadata.
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if args:
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# pyrefly: ignore # bad-argument-type
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self._prep_args_for_hash(key_values, args, state, id_hashed_objects)
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if kwargs:
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# pyrefly: ignore # bad-argument-type
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self._prep_args_for_hash(key_values, kwargs, state, id_hashed_objects)
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key = _DispatchCacheKey(tuple(key_values))
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@ -1909,27 +1924,53 @@ class FakeTensorMode(TorchDispatchMode):
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if isinstance(output, tuple):
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for out_element in output:
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self._validate_output_for_cache_entry(
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state, key, func, args, kwargs, out_element
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state,
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key,
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# pyrefly: ignore # bad-argument-type
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func,
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args,
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kwargs,
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out_element,
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)
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else:
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self._validate_output_for_cache_entry(
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state, key, func, args, kwargs, output
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state,
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key,
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# pyrefly: ignore # bad-argument-type
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func,
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args,
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kwargs,
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output,
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)
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if isinstance(output, tuple):
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output_infos = [
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self._get_output_info_for_cache_entry(
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state, key, func, args, kwargs, out_elem
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state,
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key,
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# pyrefly: ignore # bad-argument-type
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func,
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args,
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kwargs,
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out_elem,
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)
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for out_elem in output
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]
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return _DispatchCacheValidEntry(
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output_infos=tuple(output_infos), is_output_tuple=True
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# pyrefly: ignore # bad-argument-type
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output_infos=tuple(output_infos),
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is_output_tuple=True,
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)
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else:
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output_info = self._get_output_info_for_cache_entry(
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state, key, func, args, kwargs, output
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state,
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key,
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# pyrefly: ignore # bad-argument-type
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func,
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args,
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kwargs,
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output,
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)
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return _DispatchCacheValidEntry(
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output_infos=(output_info,), is_output_tuple=False
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@ -2472,6 +2513,7 @@ class FakeTensorMode(TorchDispatchMode):
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)
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with self, maybe_ignore_fresh_unbacked_symbols():
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# pyrefly: ignore # index-error
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return registered_hop_fake_fns[func](*args, **kwargs)
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self.invalidate_written_to_constants(func, flat_arg_fake_tensors, args, kwargs)
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@ -2625,6 +2667,7 @@ class FakeTensorMode(TorchDispatchMode):
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# TODO: Is this really needed?
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compute_unbacked_bindings(self.shape_env, fake_out, peek=True)
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# pyrefly: ignore # bad-return
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return fake_out
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# Try for fastpath
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@ -2906,6 +2949,7 @@ class FakeTensorMode(TorchDispatchMode):
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self, e, device or common_device
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)
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else:
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# pyrefly: ignore # bad-return
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return e
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return tree_map(wrap, r)
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