Merge branch 'main' into transforms/photometricdistort

Author: pmeier

.circleci/config.yml

@@ -146,7 +146,7 @@ commands:
         default: true
     steps:
       - pip_install:
-          args: --pre torch -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
+          args: --pre torch --extra-index-url https://download.pytorch.org/whl/nightly/cpu
           descr: Install PyTorch from nightly releases
       - pip_install:
           args: --no-build-isolation <<# parameters.editable >> --editable <</ parameters.editable >> .
@@ -158,11 +158,8 @@ commands:
           args: iopath
           descr: Install third-party dependencies
       - pip_install:
-          args: -r https://raw.githubusercontent.com/pytorch/data/main/requirements.txt
-          descr: Install torchdata build dependencies
-      - pip_install:
-          args: --no-build-isolation git+https://github.com/pytorch/data
-          descr: Install torchdata from source
+          args: --pre torchdata --extra-index-url https://download.pytorch.org/whl/nightly/cpu
+          descr: Install torchdata from nightly releases
 
   # Most of the test suite is handled by the `unittest` jobs, with completely different workflow and setup.
   # This command can be used if only a selection of tests need to be run, for ad-hoc files.
@@ -269,7 +266,7 @@ smoke_test_common: &smoke_test_common
 jobs:
   circleci_consistency:
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     steps:
       - checkout
       - pip_install:
@@ -282,7 +279,7 @@ jobs:
 
   lint_python_and_config:
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     steps:
       - checkout
       - pip_install:
@@ -301,7 +298,7 @@ jobs:
 
   lint_c:
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     steps:
       - apt_install:
           args: libtinfo5
@@ -323,7 +320,7 @@ jobs:
 
   type_check_python:
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     steps:
       - apt_install:
           args: libturbojpeg-dev
@@ -341,7 +338,7 @@ jobs:
 
   unittest_torchhub:
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     steps:
       - checkout
       - install_torchvision
@@ -350,7 +347,7 @@ jobs:
 
   unittest_onnx:
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     steps:
       - checkout
       - install_torchvision
@@ -362,7 +359,7 @@ jobs:
 
   unittest_prototype:
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     resource_class: xlarge
     steps:
       - checkout
@@ -376,7 +373,7 @@ jobs:
 
   unittest_extended:
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     resource_class: xlarge
     steps:
       - checkout
@@ -538,7 +535,7 @@ jobs:
   binary_android_build:
     <<: *torchvision_android_params
     docker:
-      - image: circleci/android:api-29-ndk
+      - image: cimg/android:2021.08-ndk
     resource_class: xlarge
     steps:
     - attach_workspace:
@@ -557,7 +554,7 @@ jobs:
   binary_android_upload:
     <<: *torchvision_android_params
     docker:
-      - image: circleci/android:api-29-ndk
+      - image: cimg/android:2021.08-ndk
     resource_class: xlarge
     steps:
     - attach_workspace:
@@ -616,7 +613,7 @@ jobs:
         description: "What whl subfolder to upload to, e.g., blank or cu100/ (trailing slash is important)"
         type: string
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     steps:
       - attach_workspace:
           at: ~/workspace
@@ -1040,7 +1037,7 @@ jobs:
   build_docs:
     <<: *binary_common
     docker:
-      - image: circleci/python:3.7
+      - image: cimg/python:3.7
     resource_class: 2xlarge+
     steps:
       - attach_workspace:

.circleci/config.yml.in

@@ -0,0 +1,7 @@
+# This file keeps git blame clean.
+# See https://docs.github.com/en/repositories/working-with-files/using-files/viewing-a-file#ignore-commits-in-the-blame-view
+
+# Add ufmt (usort + black) as code formatter (#4384)
+5f0edb97b46e5bff71dc19dedef05c5396eeaea2
+# update python syntax >=3.6 (#4585)
+d367a01a18a3ae6bee13d8be3b63fd6a581ea46f

.git-blame-ignore-revs

@@ -3,4 +3,6 @@ numpy
 sphinx-copybutton>=0.3.1
 sphinx-gallery>=0.9.0
 sphinx==3.5.4
+# This pin is only needed for sphinx<4.0.2. See https://github.com/pytorch/vision/issues/5673 for details
+Jinja2<3.1.*
 -e git+https://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme

docs/requirements.txt

@@ -1,3 +1,4 @@
+import bz2
 import collections.abc
 import csv
 import functools
@@ -9,6 +10,7 @@
 import pathlib
 import pickle
 import random
+import warnings
 import xml.etree.ElementTree as ET
 from collections import defaultdict, Counter
 
@@ -469,7 +471,10 @@ def imagenet(info, root, config):
         ]
         num_children = 1
         synsets.extend((0, "", "", "", num_children, [], 0, 0) for _ in range(5))
-        savemat(data_root / "meta.mat", dict(synsets=synsets))
+        with warnings.catch_warnings():
+            # The warning is not for savemat, but rather for some internals savemet is using
+            warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning)
+            savemat(data_root / "meta.mat", dict(synsets=synsets))
 
         make_tar(root, devkit_root.with_suffix(".tar.gz").name, compression="gz")
     else:  # config.split == "test"
@@ -1431,3 +1436,21 @@ def stanford_cars(info, root, config):
         make_tar(root, "car_devkit.tgz", devkit, compression="gz")
 
     return num_samples
+
+
+@register_mock
+def usps(info, root, config):
+    num_samples = {"train": 15, "test": 7}[config.split]
+
+    with bz2.open(root / f"usps{'.t' if not config.split == 'train' else ''}.bz2", "wb") as fh:
+        lines = []
+        for _ in range(num_samples):
+            label = make_tensor(1, low=1, high=11, dtype=torch.int)
+            values = make_tensor(256, low=-1, high=1, dtype=torch.float)
+            lines.append(
+                " ".join([f"{int(label)}", *(f"{idx}:{float(value):.6f}" for idx, value in enumerate(values, 1))])
+            )
+
+        fh.write("\n".join(lines).encode())
+
+    return num_samples

test/builtin_dataset_mocks.py

@@ -67,7 +67,7 @@ class TestRotate:
     IMG_W = 26
 
     @pytest.mark.parametrize("device", cpu_and_gpu())
-    @pytest.mark.parametrize("height, width", [(26, IMG_W), (32, IMG_W)])
+    @pytest.mark.parametrize("height, width", [(7, 33), (26, IMG_W), (32, IMG_W)])
     @pytest.mark.parametrize(
         "center",
         [
@@ -77,7 +77,7 @@ class TestRotate:
         ],
     )
     @pytest.mark.parametrize("dt", ALL_DTYPES)
-    @pytest.mark.parametrize("angle", range(-180, 180, 17))
+    @pytest.mark.parametrize("angle", range(-180, 180, 34))
     @pytest.mark.parametrize("expand", [True, False])
     @pytest.mark.parametrize(
         "fill",

test/test_functional_tensor.py

@@ -745,24 +745,24 @@ def test_detection_model_validation(model_fn):
     x = [torch.rand(input_shape)]
 
     # validate that targets are present in training
-    with pytest.raises(ValueError):
+    with pytest.raises(AssertionError):
         model(x)
 
     # validate type
     targets = [{"boxes": 0.0}]
-    with pytest.raises(TypeError):
+    with pytest.raises(AssertionError):
         model(x, targets=targets)
 
     # validate boxes shape
     for boxes in (torch.rand((4,)), torch.rand((1, 5))):
         targets = [{"boxes": boxes}]
-        with pytest.raises(ValueError):
+        with pytest.raises(AssertionError):
             model(x, targets=targets)
 
     # validate that no degenerate boxes are present
     boxes = torch.tensor([[1, 3, 1, 4], [2, 4, 3, 4]])
     targets = [{"boxes": boxes}]
-    with pytest.raises(ValueError):
+    with pytest.raises(AssertionError):
         model(x, targets=targets)
 
 

test/test_models.py

@@ -16,7 +16,7 @@ def test_incorrect_anchors(self):
         image1 = torch.randn(3, 800, 800)
         image_list = ImageList(image1, [(800, 800)])
         feature_maps = [torch.randn(1, 50)]
-        pytest.raises(ValueError, anc, image_list, feature_maps)
+        pytest.raises(AssertionError, anc, image_list, feature_maps)
 
     def _init_test_anchor_generator(self):
         anchor_sizes = ((10,),)

test/test_models_detection_anchor_utils.py

@@ -138,13 +138,13 @@ def test_autocast(self, x_dtype, rois_dtype):
 
     def _helper_boxes_shape(self, func):
         # test boxes as Tensor[N, 5]
-        with pytest.raises(ValueError):
+        with pytest.raises(AssertionError):
             a = torch.linspace(1, 8 * 8, 8 * 8).reshape(1, 1, 8, 8)
             boxes = torch.tensor([[0, 0, 3, 3]], dtype=a.dtype)
             func(a, boxes, output_size=(2, 2))
 
         # test boxes as List[Tensor[N, 4]]
-        with pytest.raises(ValueError):
+        with pytest.raises(AssertionError):
             a = torch.linspace(1, 8 * 8, 8 * 8).reshape(1, 1, 8, 8)
             boxes = torch.tensor([[0, 0, 3]], dtype=a.dtype)
             ops.roi_pool(a, [boxes], output_size=(2, 2))