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chore(deps): update all non-major dependencies #187

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merged 1 commit into from
Nov 16, 2021
Merged

chore(deps): update all non-major dependencies #187

merged 1 commit into from
Nov 16, 2021

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@renovate renovate bot commented Nov 16, 2021 •
edited

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This PR contains the following updates:

Package Change Age Adoption Passing Confidence
@iconify/iconify (source) ^2.0.4 -> ^2.1.0 age adoption passing confidence
@vitejs/plugin-vue ^1.9.2 -> ^1.9.4 age adoption passing confidence
@vue/compiler-sfc ^3.2.19 -> ^3.2.22 age adoption passing confidence
jest (source) ^27.2.4 -> ^27.3.1 age adoption passing confidence
playwright-chromium (source) ^1.15.1 -> ^1.16.3 age adoption passing confidence
prompts ^2.4.1 -> ^2.4.2 age adoption passing confidence
pytorch-ignite >=0.4.5 -> >=0.4.7 age adoption passing confidence
pytorch-ignite >=0.4.2 -> >=0.4.7 age adoption passing confidence
torch >=1.8.0 -> >=1.10.0 age adoption passing confidence
torchvision >=0.9.0 -> >=0.11.1 age adoption passing confidence
vite ^2.6.2 -> ^2.6.14 age adoption passing confidence
vue ^3.2.19 -> ^3.2.22 age adoption passing confidence
vue-router ^4.0.11 -> ^4.0.12 age adoption passing confidence

Release Notes

vitejs/vite

v1.9.4

Bug Fixes
  • plugin-vue: exclude direct css request from hmr target (#​5422) (4331c26)

v1.9.3

Bug Fixes
  • plugin-vue: don't use object spread in the config hook (#​5155) (c1ce471)
vuejs/vue-next

v3.2.22

Compare Source

Bug Fixes

v3.2.21

Compare Source

Bug Fixes
  • custom-element: fix custom element props access on initial render (4b7f76e), closes #​4792
  • custom-element: fix initial attr type casting for programmtically created elements (3ca8317), closes #​4772
  • devtools: avoid open handle in non-browser env (6916d72), closes #​4815
  • devtools: fix memory leak when devtools is not installed (#​4833) (6b32f0d), closes #​4829
  • runtime-core: add v-memo to built-in directives check (#​4787) (5eb7263)
  • runtime-dom: fix behavior regression for v-show + style display binding (3f38d59), closes #​4768
  • types: fix ref unwrapping type inference for nested shallowReactive & shallowRef (20a3615), closes #​4771

v3.2.20

Compare Source

Bug Fixes
Features
  • compiler-sfc: <script setup> defineProps destructure transform (#​4690) (467e113)
facebook/jest

v27.3.1

Compare Source

Fixes
  • [expect] Make expect extension properties configurable (#​11978)
  • [expect] Fix .any() checks on primitive wrapper classes (#​11976)
Chore & Maintenance
  • [expect] BigInt global is always defined, don't check for its existence at runtime (#​11979)
  • [jest-config, jest-util] Use ci-info instead of is-ci to detect CI environment (#​11973)

v27.3.0

Compare Source

Features
  • [jest-config] Add testEnvironmentOptions.html to apply to jsdom input (#​11950)
  • [jest-resolver] Support default export (.) in exports field if main is missing (#​11919)
Fixes
  • [expect] Tweak and improve types (#​11949)
  • [jest-runtime] Ensure absolute paths can be resolved within test modules (#​11943)
  • [jest-runtime] Fix instanceof for ModernFakeTimers and LegacyFakeTimers methods (#​11946)

v27.2.5

Compare Source

Features
  • [jest-config] Warn when multiple Jest configs are located (#​11922)
Fixes
  • [expect] Pass matcher context to asymmetric matchers (#​11926 & #​11930)
  • [expect] Improve TypeScript types (#​11931)
  • [expect] Improve typings of toThrow() and toThrowError() matchers (#​11929)
  • [jest-cli] Improve --help printout by removing defunct --browser option (#​11914)
  • [jest-haste-map] Use distinct cache paths for different values of computeDependencies (#​11916)
  • [@jest/reporters] Do not buffer console.logs when using verbose reporter (#​11054)
Chore & Maintenance
  • [expect] Export default matchers (#​11932)
  • [@jest/types] Mark deprecated configuration options as @deprecated (#​11913)
Microsoft/playwright

v1.16.3

Compare Source

Highlights

This patch includes bug fixes for the following issues:

https://github.com/microsoft/playwright/issues/9849 - [BUG]: toHaveCount fails with serialization error in 1.16 when elements do not yet existshttps://github.com/microsoft/playwright/issues/98977 - [Bug]: TraceViewer doesn't show actionhttps://github.com/microsoft/playwright/issues/990202 - [BUG] Warn if the html-report gets opened with file://

Browser Versions

  • Chromium 97.0.4666.0
  • Mozilla Firefox 93.0
  • WebKit 15.4

This version of Playwright was also tested against the following stable channels:

  • Google Chrome 94
  • Microsoft Edge 94

(1.16.3-1635814179000)

v1.16.2

Compare Source

Highlights

This patch includes bug fixes for the following issues:

https://github.com/microsoft/playwright/issues/7818 - [Bug]: dedup snapshot CSS imageshttps://github.com/microsoft/playwright/issues/97411 - [BUG] Error while an attempt to install Playwright in CI -> Failed at the playwright@1.16.1 install scriphttps://github.com/microsoft/playwright/issues/975656 - [Regression] Page.screenshot does not work inside Docker with BrowserServhttps://github.com/microsoft/playwright/issues/9759759 - [BUG] 1.16.x the package.json is not export anymhttps://github.com/microsoft/playwright/issues/97609760 - [BUG] snapshot updating causes failures for all tries except the https://github.com/microsoft/playwright/issues/9768/9768 - [BUG] ignoreHTTPSErrors not working on page.request

Browser Versions

  • Chromium 97.0.4666.0
  • Mozilla Firefox 93.0
  • WebKit 15.4

This version of Playwright was also tested against the following stable channels:

  • Google Chrome 94
  • Microsoft Edge 94

(1.16.2-1635322350000)

v1.16.1

Compare Source

Highlights

This patch includes bug fixes for the following issues:

https://github.com/microsoft/playwright/issues/9688 - [REGRESSION]: toHaveCount does not work anymore with 0 elementshttps://github.com/microsoft/playwright/issues/96922 - [BUG] HTML report shows locator._withElement for locator.evaluate

Browser Versions

  • Chromium 97.0.4666.0
  • Mozilla Firefox 93.0
  • WebKit 15.4

This version of Playwright was also tested against the following stable channels:

  • Google Chrome 94
  • Microsoft Edge 94

(1.16.0-1634781227000)

v1.16.0

Compare Source

🎭 Playwright Test

API Testing

Playwright 1.16 introduces new API Testing that lets you send requests to the server directly from Node.js!
Now you can:

  • test your server API
  • prepare server side state before visiting the web application in a test
  • validate server side post-conditions after running some actions in the browser

To do a request on behalf of Playwright's Page, use new [page.request][page.request] API:

import { test, expect } from '@&#8203;playwright/test';

test('context fetch', async ({ page }) => {
  // Do a GET request on behalf of page
  const response = await page.request.get('http://example.com/foo.json');
  // ... 
});

To do a stand-alone request from node.js to an API endpoint, use new [request fixture][request fixture]:

import { test, expect } from '@&#8203;playwright/test';

test('context fetch', async ({ request }) => {
  // Do a GET request on behalf of page
  const response = await request.get('http://example.com/foo.json');
  // ... 
});

Read more about it in our API testing guide.

Response Interception

It is now possible to do response interception by combining API Testing with request interception.

For example, we can blur all the images on the page:

import { test, expect } from '@&#8203;playwright/test';
import jimp from 'jimp'; // image processing library

test('response interception', async ({ page }) => {
  await page.route('**/*.jpeg', async route => {
    const response = await page._request.fetch(route.request());
    const image = await jimp.read(await response.body());
    await image.blur(5);
    route.fulfill({
      response,
      body: await image.getBufferAsync('image/jpeg'),
    });
  });
  const response = await page.goto('https://playwright.dev');
  expect(response.status()).toBe(200);
});

Read more about response interception.

New HTML reporter

Try it out new HTML reporter with either --reporter=html or a reporter entry
in playwright.config.ts file:

$ npx playwright test --reporter=html

The HTML reporter has all the information about tests and their failures, including surfacing
trace and image artifacts.

html reporter

Read more about our reporters.

🎭 Playwright Library

locator.waitFor

Wait for a locator to resolve to a single element with a given state.
Defaults to the state: 'visible'.

Comes especially handy when working with lists:

import { test, expect } from '@&#8203;playwright/test';

test('context fetch', async ({ page }) => {
  const completeness = page.locator('text=Success');
  await completeness.waitFor();
  expect(await page.screenshot()).toMatchSnapshot('screen.png');
});

Read more about [locator.waitFor()][locator.waitFor()].

🎭 Playwright Trace Viewer

  • web-first assertions inside trace viewer
  • run trace viewer with npx playwright show-trace and drop trace files to the trace viewer PWA
  • API testing is integrated with trace viewer
  • better visual attribution of action targets

Read more about Trace Viewer.

Browser Versions

  • Chromium 97.0.4666.0
  • Mozilla Firefox 93.0
  • WebKit 15.4

This version of Playwright was also tested against the following stable channels:

  • Google Chrome 94
  • Microsoft Edge 94

(1.16.0-1634781227000)

v1.15.2

Compare Source

Highlights

This patch includes bug fixes for the following issues:

https://github.com/microsoft/playwright/issues/9261 - [BUG] npm init playwright fails on path spaceshttps://github.com/microsoft/playwright/issues/92988 - [Question]: Should new Headers methods work in RouteAsync ?

Browser Versions

  • Chromium 96.0.4641.0
  • Mozilla Firefox 92.0
  • WebKit 15.0

This version of Playwright was also tested against the following stable channels:

  • Google Chrome 93
  • Microsoft Edge 93

1.15.2-1633455481000

terkelg/prompts

v2.4.2

Compare Source

What's Changed
New Contributors

Full Changelog: terkelg/prompts@v2.4.1...v2.4.2

pytorch/ignite

v0.4.7

Compare Source

PyTorch-Ignite 0.4.7 - Release Notes
New Features
Bug fixes
Housekeeping (docs, CI, examples, tests, etc)
Acknowledgments

🎉 Thanks to our community and all our contributors for the issues, PRs and 🌟 ⭐️ 🌟 !
💯 We really appreciate your implication into the project (in alphabetical order):

@​Chandan-h-509, @​Ishan-Kumar2, @​KickItLikeShika, @​Priyansi, @​fco-dv, @​gucifer, @​kennethleungty, @​logankilpatrick, @​mfoglio, @​sandylaker, @​sdesrozis, @​theory-in-progress, @​toxa23, @​trsvchn, @​vfdev-5, @​ydcjeff

v0.4.6

Compare Source

PyTorch-Ignite 0.4.6 - Release Notes
New Features
  • Added start_lr option to FastaiLRFinder (#​2111)
  • Added Model's EMA handler (#​2098, #​2102)
  • Improved SLURM support: added hostlist expansion without using scontrol (#​2092)
Metrics
Bug fixes
  • Modified auto_dataloader to not wrap user provided DistributedSampler (#​2119)
  • Raise error in DistributedProxySampler when sampler is already a DistributedSampler (#​2120)
  • Improved LRFinder error message (#​2127)
  • Added py.typed for type checkers (#​2095)
Housekeeping
Acknowledgments

🎉 Thanks to our community and all our contributors for the issues, PRs and 🌟 ⭐️ 🌟 !
💯 We really appreciate your implication into the project (in alphabetical order):

@​01-vyom, @​KickItLikeShika, @​gucifer, @​sandylaker, @​schuhschuh, @​sdesrozis, @​trsvchn, @​vfdev-5, @​ydcjeff

pytorch/vision

v0.11.1

Compare Source

Users were reporting issues installing torchvision on PyPI, this release contains an update to the dependencies for wheels to point directly to torch==0.10.0

v0.11.0

Compare Source

This release introduces the RegNet and EfficientNet architectures, a new FX-based utility to perform Feature Extraction, new data augmentation techniques such as RandAugment and TrivialAugment, updated training recipes that support EMA, Label Smoothing, Learning-Rate Warmup, Mixup and Cutmix, and many more.

Highlights

New Models

RegNet and EfficientNet are two popular architectures that can be scaled to different computational budgets. In this release we include 22 pre-trained weights for their classification variants. The models were trained on ImageNet and can be used as follows:

import torch
from torchvision import models

x = torch.rand(1, 3, 224, 224)

regnet = models.regnet_y_400mf(pretrained=True)
regnet.eval()
predictions = regnet(x)

efficientnet = models.efficientnet_b0(pretrained=True)
efficientnet.eval()
predictions = efficientnet(x)

The accuracies of the pre-trained models obtained on ImageNet val are seen below (see #​4403, #​4530 and #​4293 for more details)

Model Acc@1 Acc@5
regnet_x_400mf 72.834 90.95
regnet_x_800mf 75.212 92.348
regnet_x_1_6gf 77.04 93.44
regnet_x_3_2gf 78.364 93.992
regnet_x_8gf 79.344 94.686
regnet_x_16gf 80.058 94.944
regnet_x_32gf 80.622 95.248
regnet_y_400mf 74.046 91.716
regnet_y_800mf 76.42 93.136
regnet_y_1_6gf 77.95 93.966
regnet_y_3_2gf 78.948 94.576
regnet_y_8gf 80.032 95.048
regnet_y_16gf 80.424 95.24
regnet_y_32gf 80.878 95.34
EfficientNet-B0 77.692 93.532
EfficientNet-B1 78.642 94.186
EfficientNet-B2 80.608 95.31
EfficientNet-B3 82.008 96.054
EfficientNet-B4 83.384 96.594
EfficientNet-B5 83.444 96.628
EfficientNet-B6 84.008 96.916
EfficientNet-B7 84.122 96.908

We would like to thank Ross Wightman and Luke Melas-Kyriazi for contributing the weights of the EfficientNet variants.

FX-based Feature Extraction

A new Feature Extraction method has been added to our utilities. It uses PyTorch FX and enables us to retrieve the outputs of intermediate layers of a network which is useful for feature extraction and visualization. Here is an example of how to use the new utility:

import torch
from torchvision.models import resnet50
from torchvision.models.feature_extraction import create_feature_extractor

x = torch.rand(1, 3, 224, 224)

model = resnet50()

return_nodes = {
    "layer4.2.relu_2": "layer4"
}
model2 = create_feature_extractor(model, return_nodes=return_nodes)
intermediate_outputs = model2(x)

print(intermediate_outputs['layer4'].shape)

We would like to thank Alexander Soare for developing this utility.

New Data Augmentations

Two new Automatic Augmentation techniques were added: Rand Augment and Trivial Augment. Both methods can be used as drop-in replacement of the AutoAugment technique as seen below:

from torchvision import transforms

t = transforms.RandAugment()
### t = transforms.TrivialAugmentWide()
transformed = t(image)

transform = transforms.Compose([
    transforms.Resize(256),
    transforms.RandAugment(),  # transforms.TrivialAugmentWide()
    transforms.ToTensor()])

We would like to thank Samuel G. Müller for contributing Trivial Augment and for his help on refactoring the AA package.

Updated Training Recipes

We have updated our training reference scripts to add support of Exponential Moving Average, Label Smoothing, Learning-Rate Warmup, Mixup, Cutmix and other SOTA primitives. The above enabled us to improve the classification Acc@1 of some pre-trained models by over 4 points. A major update of the existing pre-trained weights is expected on the next release.

Backward-incompatible changes

[models] Use torch instead of scipy for random initialization of inception and googlenet weights (#​4256)

Deprecations

[models] Deprecate the C++ vision::models namespace (#​4375)

New Features

[datasets] Add iNaturalist dataset (#​4123)
[datasets] Download and Kinetics 400/600/700 Datasets (#​3680)
[datasets] Added LFW Dataset (#​4255)
[models] Add FX feature extraction as an alternative to intermediate_layer_getter (#​4302) (#​4418)
[models] Add RegNet Architecture in TorchVision (#​4403) (#​4530) (#​4550)
[ops] Add new masks_to_boxes op (#​4290) (#​4469)
[ops] Add StochasticDepth implementation (#​4301)
[reference scripts] Adding Mixup and Cutmix (#​4379)
[transforms] Integration of TrivialAugment with the current AutoAugment Code (#​4221)
[transforms] Adding RandAugment implementation (#​4348)
[models] Add EfficientNet Architecture in TorchVision (#​4293)

Improvements

Various documentation improvements (#​4239) (#​4251) (#​4275) (#​4342) (#​3894) (#​4159) (#​4133) (#​4138) (#​4089) (#​3944) (#​4349) (#​3754) (#​4308) (#​4352) (#​4318) (#​4244) (#​4362) (#​3863) (#​4382) (#​4484) (#​4503) (#​4376) (#​4457) (#​4505) (#​4363) (#​4361) (#​4337) (#​4546) (#​4553) (#​4565) (#​4567) (#​4574) (#​4575) (#​4383) (#​4390) (#​3409) (#​4451) (#​4340) (#​3967) (#​4072) (#​4028) (#​4132)
[build] Add CUDA-11.3 builds to torchvision (#​4248)
[ci, tests] Skip some CPU-only tests on CircleCI machines with GPU (#​4002) (#​4025) (#​4062)
[ci] New issue templates (#​4299)
[ci] Various CI improvements, in particular putting back GPU testing on windows (#​4421) (#​4014) (#​4053) (#​4482) (#​4475) (#​3998) (#​4388) (#​4179) (#​4394) (#​4162) (#​4065) (#​3928) (#​4081) (#​4203) (#​4011) (#​4055) (#​4074) (#​4419) (#​4067) (#​4201) (#​4200) (#​4202) (#​4496) (#​3925)
[ci] ping maintainers in case a PR was not properly labeled (#​3993) (#​4012) (#​4021) (#​4501)
[datasets] Add bzip2 file compression support to datasets (#​4097)
[datasets] Faster dataset indexing (#​3939)
[datasets] Enable logging of internal dataset instanciations. (#​4319) (#​4090)
[datasets] Removed copy=False in torch.from_numpy in MNIST to avoid warning (#​4184)
[io] Add warning for files with corrupt containers (#​3961)
[models, tests] Add test to check that classification models are FX-compatible (#​3662)
[tests] Speedup various tests (#​3929) (#​3933) (#​3936)
[models] Allow custom activation in SqueezeExcitation of EfficientNet (#​4448)
[models] Allow gradient backpropagation through GeneralizedRCNNTransform to inputs (#​4327)
[ops, tests] Add JIT tests (#​4472)
[ops] Make StochasticDepth FX-compatible (#​4373)
[ops] Added backward pass on CPU and CUDA for interpolation with anti-alias option (#​4208) (#​4211)
[ops] Small refactoring to support opt mode for torchvision ops (fb internal specific) (#​4080) (#​4095)
[reference scripts] Added Exponential Moving Average support to classification reference script (#​4381) (#​4406) (#​4407)
[reference scripts] Adding label smoothing on classification reference (#​4335)
[reference scripts] Further enhance Classification Reference (#​4444)
[reference scripts] Replaced to_tensor() with pil_to_tensor() + convert_image_dtype() (#​4452)
[reference scripts] Update the metrics output on reference scripts (#​4408)
[reference scripts] Warmup schedulers in References (#​4411)
[tests] Add check for fx compatibility on segmentation and video models (#​4131)
[tests] Mock redirection logic for tests (#​4197)
[tests] Replace set_deterministic with non-deprecated spelling (#​4212)
[tests] Skip building torchvision with ffmpeg when python==3.9 (#​4417)
[tests] [jit] Make operation call accept Stack& instead Stack* (#​63414) (#​4380)
[tests] make tests that involve GDrive more robust (#​4454)
[tests] remove dependency for dtype getters (#​4291)
[transforms] Replaced example usage of ToTensor() by PILToTensor() + ConvertImageDtype() (#​4494)
[transforms] Explicitly copying array in pil_to_tensor (#​4566) (#​4573)
[transforms] Make get_image_size and get_image_num_channels public. (#​4321)
[transforms] adding gray images support for adjust_contrast and adjust_saturation (#​4477) (#​4480)
[utils] Support single color in utils.draw_bounding_boxes (#​4075)
[video, documentation] Port the video_api.ipynb notebook to the example gallery (#​4241)
[video, io, tests] Added check for invalid input file (#​3932)
[video, io] remove deprecated function call (#​3861) (#​3989)
[video, tests] Removed test_audio_video_sync as it doesn't work as expected (#​4050)
[video] Build torchvision with ffmpeg only on Linux and ignore ffmpeg on other platforms (#​4413, #​4410, #​4041)

Bug Fixes

[build] Conda: Add numpy dependency (#​4442)
[build] Explicitly exclude PIL 8.3.0 from compatible dependencies (#​4148)
[build] More robust version check (#​4285)
[ci] Fix broken clang format test. (#​4320)
[ci] Remove mentions of conda-forge (#​4082)
[ci] fixup '' -> '/./' for CI filter (#​4059)
[datasets] Fix download from google drive which was downloading empty files in some cases (#​4109)
[datasets] Fix splitting CelebA dataset (#​4377)
[datasets] Add support for files with periods in name (#​4099)
[io, tests] Don't check transparency channel for pil >= 8.3 in test_decode_png (#​4167)
[io] Fix size_t issues across JPEG versions and platforms (#​4439)
[io] Raise proper error when decoding 16-bits jpegs (#​4101)
[io] Unpinned the libjpeg version and fixed jpeg_mem_dest's size type Wind… (#​4288)
[io] deinterlacing PNG images with read_image (#​4268)
[io] More robust ffmpeg version query in setup.py (#​4254)
[io] Fixed read_image bug (#​3948)
[models] Don't download backbone weights if pretrained=True (#​4283)
[onnx, tests] Do not disable profiling executor in ONNX tests (#​4324)
[ops, tests] Fix DeformConvTester::test_backward_cuda by setting threads per block to 512 (#​3942)
[ops] Fix typing issue to make

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@renovate renovate bot added the dependencies Pull requests that update dependencies label Nov 16, 2021
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@ydcjeff ydcjeff merged commit 6772735 into main Nov 16, 2021
@ydcjeff ydcjeff deleted the renovate/all-minor-patch branch November 16, 2021 17:37
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