Add PyTorch 1.11.0 in GH Actions (#359)

* Add PyTorch 1.11.0 in GH Actions

* Add check_version from yolov5

* Compatibility updates

* GeneratorExp aren't supported in TorchScript

* Apply pre-commit

* Minor updates

* Upgrade PyTorch minimal version to 1.8.0, add Python 3.10 and remove Python 3.6

* Fix pre-commit

.github/workflows/ci-test.yml

@@ -15,7 +15,7 @@ jobs:
       fail-fast: false
       matrix:
         image: [ 'ubuntu-latest' ]
-        torch: [ 'PyTorch 1.9.1+cpu', 'PyTorch 1.10.2+cpu' ]
+        torch: [ 'PyTorch 1.9.1+cpu', 'PyTorch 1.10.2+cpu', 'PyTorch 1.11.0+cpu' ]
         include:
           - torch: 'PyTorch 1.9.1+cpu'
             torch_address: torch==1.9.1+cpu torchvision==0.10.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
@@ -25,6 +25,10 @@ jobs:
             torch_address: torch==1.10.2+cpu torchvision==0.11.3+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
             unittest_type: -v --cov=test --cov-report=xml
             torchvision: release/0.11
+          - torch: 'PyTorch 1.11.0+cpu'
+            torch_address: torch==1.11.0+cpu torchvision==0.12.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
+            unittest_type: -v --cov=test --cov-report=xml
+            torchvision: release/0.12
 
     steps:
       - name: Clone repository

README.md

@@ -60,7 +60,7 @@ There are no extra compiled components in `yolort` and package dependencies are
 
 ### Installation and Inference Examples
 
-- Above all, follow the [official instructions](https://pytorch.org/get-started/locally/) to install PyTorch 1.7.0+ and torchvision 0.8.1+
+- Above all, follow the [official instructions](https://pytorch.org/get-started/locally/) to install PyTorch 1.8.0+ and torchvision 0.9.0+
 
 - Installation via pip
 

setup.py

@@ -99,10 +99,10 @@ def load_requirements(path_dir=PATH_ROOT, file_name="requirements.txt", comment_
             "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
             # Specify the Python versions you support here.
             "Programming Language :: Python :: 3",
-            "Programming Language :: Python :: 3.6",
             "Programming Language :: Python :: 3.7",
             "Programming Language :: Python :: 3.8",
             "Programming Language :: Python :: 3.9",
+            "Programming Language :: Python :: 3.10",
         ],
         install_requires=load_requirements(),
         # This field adds keywords for your project which will appear on the
@@ -116,7 +116,7 @@ def load_requirements(path_dir=PATH_ROOT, file_name="requirements.txt", comment_
         # 'Programming Language' classifiers above, 'pip install' will check this
         # and refuse to install the project if the version does not match. See
         # https://packaging.python.org/guides/distributing-packages-using-setuptools/#python-requires
-        python_requires=">=3.6.2",
+        python_requires=">=3.7",
         # List additional URLs that are relevant to your project as a dict.
         #
         # This field corresponds to the "Project-URL" metadata fields:

yolort/utils/__init__.py

@@ -1,25 +1,29 @@
+# Copyright (c) 2020, yolort team. All rights reserved.
+
 from typing import Callable, Dict, Mapping, Sequence, Union
 
 try:
     from torch.hub import load_state_dict_from_url
 except ImportError:
     from torch.utils.model_zoo import load_url as load_state_dict_from_url
 
+from .dependency import check_version
 from .hooks import FeatureExtractor
 from .image_utils import cv2_imshow, get_image_from_url, read_image_to_tensor
 from .update_module_state import convert_yolov5_to_yolort, load_from_ultralytics
 from .visualizer import Visualizer
 
 
 __all__ = [
-    "FeatureExtractor",
+    "check_version",
     "cv2_imshow",
     "get_image_from_url",
     "get_callable_dict",
     "convert_yolov5_to_yolort",
     "load_from_ultralytics",
     "load_state_dict_from_url",
     "read_image_to_tensor",
+    "FeatureExtractor",
     "Visualizer",
 ]
 

yolort/utils/dependency.py

@@ -0,0 +1,28 @@
+import logging
+
+import pkg_resources as pkg
+
+logger = logging.getLogger(__name__)
+
+
+def check_version(
+    current: str = "0.0.0",
+    minimum: str = "0.0.0",
+    name: str = "version ",
+    pinned: bool = False,
+    hard: bool = False,
+    verbose: bool = False,
+):
+    """
+    Check version vs. required version.
+    Adapted from https://github.com/ultralytics/yolov5/blob/c6b4f84/utils/general.py#L293
+    """
+
+    current, minimum = (pkg.parse_version(x) for x in (current, minimum))
+    result = (current == minimum) if pinned else (current >= minimum)  # bool
+    verbose_info = f"{name}{minimum} required by yolort, but {name}{current} is currently installed"
+    if hard:
+        assert result, verbose_info  # assert min requirements met
+    if verbose and not result:
+        logger.warning(verbose_info)
+    return result

yolort/v5/helper.py

@@ -6,7 +6,7 @@
 import torch
 from torch import nn
 
-from .models.yolo import Detect, Model
+from .models.yolo import Detect
 from .utils import attempt_download
 
 __all__ = ["add_yolov5_context", "load_yolov5_model", "get_yolov5_size"]
@@ -71,11 +71,12 @@ def load_yolov5_model(checkpoint_path: str, fuse: bool = False):
             model = ckpt["ema" if ckpt.get("ema") else "model"].float().eval()
 
         # Compatibility updates
-        for m in model.modules():
-            if type(m) in [nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU, Detect, Model]:
-                if isinstance(m, Detect):
-                    if not isinstance(m.anchor_grid, list):  # new Detect Layer compatibility
-                        delattr(m, "anchor_grid")
-                        setattr(m, "anchor_grid", [torch.zeros(1)] * m.nl)
+        for sub_module in model.modules():
+            if isinstance(sub_module, Detect):
+                if not isinstance(sub_module.anchor_grid, list):  # new Detect Layer compatibility
+                    delattr(sub_module, "anchor_grid")
+                    setattr(sub_module, "anchor_grid", [torch.zeros(1)] * sub_module.nl)
+            if isinstance(sub_module, nn.Upsample) and not hasattr(sub_module, "recompute_scale_factor"):
+                sub_module.recompute_scale_factor = None  # torch 1.11.0 compatibility
 
         return model