.circleci/config.yml.in

@@ -105,7 +105,7 @@ binary_common: &binary_common
     pytorch_version:
       description: "PyTorch version to build against; by default, use a nightly"
       type: string
-      default: "1.10.0"
+      default: "1.10.1"
     # Don't edit these
     python_version:
       description: "Python version to build against (e.g., 3.7)"
@@ -216,6 +216,8 @@ jobs:
       - checkout
       - run:
           command: |
+            sudo apt-get update -y
+            sudo apt install -y libtinfo5
             curl https://oss-clang-format.s3.us-east-2.amazonaws.com/linux64/clang-format-linux64 -o clang-format
             chmod +x clang-format
             sudo mv clang-format /opt/clang-format

android/build.gradle

@@ -15,7 +15,7 @@ allprojects {
             androidSupportAppCompatV7Version = "28.0.0"
             fbjniJavaOnlyVersion = "0.0.3"
             soLoaderNativeLoaderVersion = "0.8.0"
-            pytorchAndroidVersion = "1.10.0-SNAPSHOT"
+            pytorchAndroidVersion = "1.10.0"
         }
 
         repositories {

android/ops/CMakeLists.txt

@@ -35,7 +35,7 @@ target_compile_options(${TARGET} PRIVATE
 
 set(BUILD_SUBDIR ${ANDROID_ABI})
 
-find_library(PYTORCH_LIBRARY pytorch_jni_lite
+find_library(PYTORCH_LIBRARY pytorch_jni
   PATHS ${PYTORCH_LINK_DIRS}
   NO_CMAKE_FIND_ROOT_PATH)
 

packaging/build_cmake.sh

@@ -36,7 +36,7 @@ else
   MKL_CONSTRAINT=''
 fi
 
-conda install -yq \pytorch=$PYTORCH_VERSION $CONDA_CUDATOOLKIT_CONSTRAINT $CONDA_CPUONLY_FEATURE $MKL_CONSTRAINT -c "pytorch-${UPLOAD_CHANNEL}"
+conda install -yq \pytorch=$PYTORCH_VERSION $CONDA_CUDATOOLKIT_CONSTRAINT $CONDA_CPUONLY_FEATURE $MKL_CONSTRAINT numpy -c "pytorch-${UPLOAD_CHANNEL}"
 TORCH_PATH=$(dirname $(python -c "import torch; print(torch.__file__)"))
 
 if [[ "$(uname)" == Darwin || "$OSTYPE" == "msys" ]]; then

packaging/build_wheel.sh

@@ -55,6 +55,6 @@ else
     if [[ "$OSTYPE" == "msys" ]]; then
         "$script_dir/windows/internal/vc_env_helper.bat" python $script_dir/wheel/relocate.py
     else
-        LD_LIBRARY_PATH="/usr/local/lib:$LD_LIBRARY_PATH" python $script_dir/wheel/relocate.py
+        LD_LIBRARY_PATH="/usr/local/lib:$CUDA_HOME/lib64:$LD_LIBRARY_PATH" python $script_dir/wheel/relocate.py
     fi
 fi

torchvision/datasets/widerface.py

@@ -37,13 +37,13 @@ class WIDERFace(VisionDataset):
 
     BASE_FOLDER = "widerface"
     FILE_LIST = [
-        # File ID                             MD5 Hash                          Filename
-        ("0B6eKvaijfFUDQUUwd21EckhUbWs", "3fedf70df600953d25982bcd13d91ba2", "WIDER_train.zip"),
-        ("0B6eKvaijfFUDd3dIRmpvSk8tLUk", "dfa7d7e790efa35df3788964cf0bbaea", "WIDER_val.zip"),
-        ("0B6eKvaijfFUDbW4tdGpaYjgzZkU", "e5d8f4248ed24c334bbd12f49c29dd40", "WIDER_test.zip")
+        # File ID                             MD5 Hash                            Filename
+        ("15hGDLhsx8bLgLcIRD5DhYt5iBxnjNF1M", "3fedf70df600953d25982bcd13d91ba2", "WIDER_train.zip"),
+        ("1GUCogbp16PMGa39thoMMeWxp7Rp5oM8Q", "dfa7d7e790efa35df3788964cf0bbaea", "WIDER_val.zip"),
+        ("1HIfDbVEWKmsYKJZm4lchTBDLW5N7dY5T", "e5d8f4248ed24c334bbd12f49c29dd40", "WIDER_test.zip"),
     ]
     ANNOTATIONS_FILE = (
-        "http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/support/bbx_annotation/wider_face_split.zip",
+        "http://shuoyang1213.me/WIDERFACE/support/bbx_annotation/wider_face_split.zip",
         "0e3767bcf0e326556d407bf5bff5d27c",
         "wider_face_split.zip"
     )

torchvision/extension.py

@@ -1,3 +1,8 @@
+import ctypes
+import os
+import sys
+from warnings import warn
+
 import torch
 
 from ._internally_replaced_utils import _get_extension_path
@@ -62,4 +67,22 @@ def _check_cuda_version():
     return _version
 
 
+def _load_library(lib_name):
+    lib_path = _get_extension_path(lib_name)
+    # On Windows Python-3.8+ has `os.add_dll_directory` call,
+    # which is called from _get_extension_path to configure dll search path
+    # Condition below adds a workaround for older versions by
+    # explicitly calling `LoadLibraryExW` with the following flags:
+    #  - LOAD_LIBRARY_SEARCH_DEFAULT_DIRS (0x1000)
+    #  - LOAD_LIBRARY_SEARCH_DLL_LOAD_DIR (0x100)
+    if os.name == "nt" and sys.version_info < (3, 8):
+        _kernel32 = ctypes.WinDLL("kernel32.dll", use_last_error=True)
+        if hasattr(_kernel32, "LoadLibraryExW"):
+            _kernel32.LoadLibraryExW(lib_path, None, 0x00001100)
+        else:
+            warn("LoadLibraryExW is missing in kernel32.dll")
+
+    torch.ops.load_library(lib_path)
+
+
 _check_cuda_version()

torchvision/io/_video_opt.py

@@ -8,12 +8,11 @@
 import numpy as np
 import torch
 
-from .._internally_replaced_utils import _get_extension_path
+from ..extension import _load_library
 
 
 try:
-    lib_path = _get_extension_path('video_reader')
-    torch.ops.load_library(lib_path)
+    _load_library("video_reader")
     _HAS_VIDEO_OPT = True
 except (ImportError, OSError):
     _HAS_VIDEO_OPT = False

torchvision/io/image.py

@@ -1,14 +1,14 @@
 import torch
 from enum import Enum
+from warnings import warn
 
-from .._internally_replaced_utils import _get_extension_path
+from ..extension import _load_library
 
 
 try:
-    lib_path = _get_extension_path('image')
-    torch.ops.load_library(lib_path)
-except (ImportError, OSError):
-    pass
+    _load_library("image")
+except (ImportError, OSError) as e:
+    warn(f"Failed to load image Python extension: {e}")
 
 
 class ImageReadMode(Enum):

torchvision/models/quantization/mobilenetv3.py

@@ -43,7 +43,7 @@ def _load_from_state_dict(
     ):
         version = local_metadata.get("version", None)
 
-        if version is None or version < 2:
+        if hasattr(self, "qconfig") and (version is None or version < 2):
             default_state_dict = {
                 "scale_activation.activation_post_process.scale": torch.tensor([1.]),
                 "scale_activation.activation_post_process.zero_point": torch.tensor([0], dtype=torch.int32),

torchvision/transforms/autoaugment.py

@@ -194,7 +194,7 @@ def _augmentation_space(self, num_bins: int, image_size: List[int]) -> Dict[str,
             "Contrast": (torch.linspace(0.0, 0.9, num_bins), True),
             "Sharpness": (torch.linspace(0.0, 0.9, num_bins), True),
             "Posterize": (8 - (torch.arange(num_bins) / ((num_bins - 1) / 4)).round().int(), False),
-            "Solarize": (torch.linspace(256.0, 0.0, num_bins), False),
+            "Solarize": (torch.linspace(255.0, 0.0, num_bins), False),
             "AutoContrast": (torch.tensor(0.0), False),
             "Equalize": (torch.tensor(0.0), False),
             "Invert": (torch.tensor(0.0), False),
@@ -287,7 +287,7 @@ def _augmentation_space(self, num_bins: int, image_size: List[int]) -> Dict[str,
             "Contrast": (torch.linspace(0.0, 0.9, num_bins), True),
             "Sharpness": (torch.linspace(0.0, 0.9, num_bins), True),
             "Posterize": (8 - (torch.arange(num_bins) / ((num_bins - 1) / 4)).round().int(), False),
-            "Solarize": (torch.linspace(256.0, 0.0, num_bins), False),
+            "Solarize": (torch.linspace(255.0, 0.0, num_bins), False),
             "AutoContrast": (torch.tensor(0.0), False),
             "Equalize": (torch.tensor(0.0), False),
         }
@@ -366,7 +366,7 @@ def _augmentation_space(self, num_bins: int) -> Dict[str, Tuple[Tensor, bool]]:
             "Contrast": (torch.linspace(0.0, 0.99, num_bins), True),
             "Sharpness": (torch.linspace(0.0, 0.99, num_bins), True),
             "Posterize": (8 - (torch.arange(num_bins) / ((num_bins - 1) / 6)).round().int(), False),
-            "Solarize": (torch.linspace(256.0, 0.0, num_bins), False),
+            "Solarize": (torch.linspace(255.0, 0.0, num_bins), False),
             "AutoContrast": (torch.tensor(0.0), False),
             "Equalize": (torch.tensor(0.0), False),
         }