From 45d855ee2470e7b9cbe682eb7464f32242805b78 Mon Sep 17 00:00:00 2001 From: frgfm Date: Sun, 14 Feb 2021 23:00:53 +0100 Subject: [PATCH 1/4] chore: Enabled typing check for densenet --- mypy.ini | 4 ---- 1 file changed, 4 deletions(-) diff --git a/mypy.ini b/mypy.ini index b35ee60d907..0d8444e13f8 100644 --- a/mypy.ini +++ b/mypy.ini @@ -12,10 +12,6 @@ ignore_errors = True ignore_errors = True -[mypy-torchvision.models.densenet.*] - -ignore_errors=True - [mypy-torchvision.models.detection.*] ignore_errors = True From 7554a1c2db6b580bece80aa032d51671a03e38d6 Mon Sep 17 00:00:00 2001 From: frgfm Date: Sun, 14 Feb 2021 23:02:07 +0100 Subject: [PATCH 2/4] style: Added typing exceptions in densenet --- torchvision/models/densenet.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/torchvision/models/densenet.py b/torchvision/models/densenet.py index 02d18c1e22b..652f97ee967 100644 --- a/torchvision/models/densenet.py +++ b/torchvision/models/densenet.py @@ -71,13 +71,13 @@ def closure(*inputs): def forward(self, input: List[Tensor]) -> Tensor: pass - @torch.jit._overload_method # noqa: F811 + @torch.jit._overload_method # type: ignore[no-redef] # noqa: F811 def forward(self, input: Tensor) -> Tensor: pass # torchscript does not yet support *args, so we overload method # allowing it to take either a List[Tensor] or single Tensor - def forward(self, input: Tensor) -> Tensor: # noqa: F811 + def forward(self, input: Tensor) -> Tensor: # type: ignore[no-redef] # noqa: F811 if isinstance(input, Tensor): prev_features = [input] else: @@ -121,7 +121,7 @@ def __init__( ) self.add_module('denselayer%d' % (i + 1), layer) - def forward(self, init_features: Tensor) -> Tensor: + def forward(self, init_features: Tensor) -> Tensor: # type: ignore[override] features = [init_features] for name, layer in self.items(): new_features = layer(features) From 9e33fc844187d9825fd9765930ff6dc9d4ebe554 Mon Sep 17 00:00:00 2001 From: frgfm Date: Mon, 15 Feb 2021 11:32:40 +0100 Subject: [PATCH 3/4] style: Fixed type comments --- torchvision/models/densenet.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/torchvision/models/densenet.py b/torchvision/models/densenet.py index 652f97ee967..a0c6c0365ad 100644 --- a/torchvision/models/densenet.py +++ b/torchvision/models/densenet.py @@ -71,13 +71,13 @@ def closure(*inputs): def forward(self, input: List[Tensor]) -> Tensor: pass - @torch.jit._overload_method # type: ignore[no-redef] # noqa: F811 + @torch.jit._overload_method # noqa: F811 # type: ignore[no-redef] def forward(self, input: Tensor) -> Tensor: pass # torchscript does not yet support *args, so we overload method # allowing it to take either a List[Tensor] or single Tensor - def forward(self, input: Tensor) -> Tensor: # type: ignore[no-redef] # noqa: F811 + def forward(self, input: Tensor) -> Tensor: # noqa: F811 # type: ignore[no-redef] if isinstance(input, Tensor): prev_features = [input] else: From a0c4a85264db4cf9694c601a6fe44ee8675dcfcf Mon Sep 17 00:00:00 2001 From: F-G Fernandez <26927750+frgfm@users.noreply.github.com> Date: Sat, 16 Sep 2023 19:03:33 +0200 Subject: [PATCH 4/4] style: Updates typing --- torchvision/models/densenet.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/torchvision/models/densenet.py b/torchvision/models/densenet.py index b99d97c6ba0..569ed0ad3d0 100644 --- a/torchvision/models/densenet.py +++ b/torchvision/models/densenet.py @@ -1,7 +1,7 @@ import re from collections import OrderedDict from functools import partial -from typing import Any, List, Optional, Tuple +from typing import Any, Dict, List, Optional, Tuple, cast import torch import torch.nn as nn @@ -67,13 +67,13 @@ def closure(*inputs): def forward(self, input: List[Tensor]) -> Tensor: # noqa: F811 pass - @torch.jit._overload_method # noqa: F811 # type: ignore[no-redef] + @torch.jit._overload_method # noqa: F811 def forward(self, input: Tensor) -> Tensor: # noqa: F811 pass # torchscript does not yet support *args, so we overload method # allowing it to take either a List[Tensor] or single Tensor - def forward(self, input: Tensor) -> Tensor: # noqa: F811 # type: ignore[no-redef] + def forward(self, input: Tensor) -> Tensor: # noqa: F811 if isinstance(input, Tensor): prev_features = [input] else: @@ -227,7 +227,7 @@ def _load_state_dict(model: nn.Module, weights: WeightsEnum, progress: bool) -> r"^(.*denselayer\d+\.(?:norm|relu|conv))\.((?:[12])\.(?:weight|bias|running_mean|running_var))$" ) - state_dict = weights.get_state_dict(progress=progress, check_hash=True) + state_dict = cast(Dict[str, Tensor], weights.get_state_dict(progress=progress, check_hash=True)) for key in list(state_dict.keys()): res = pattern.match(key) if res: