Automating language learning with the power of Artificial Intelligence. This repository presents FluentAI, a tool that combines Fluent Forever techniques with AI-driven automation. It streamlines the process of creating Anki flashcards, making language acquisition faster and more efficient.
We are excited to announce the release of PyTorch® 2.2! PyTorch 2.2 offers ~2x performance improvements to scaled_dot_product_attention via FlashAttention-v2 integration, as well as AOTInductor, a new ahead-of-time compilation and deployment tool built for non-python server-side deployments.
This release also includes improved torch.compile support for Optimizers, a number of new inductor optimizations, and a new logging mechanism called TORCH_LOGS.
Please note that we are deprecating macOS x86 support, and PyTorch 2.2.x will be the last version that supports macOS x64.
Along with 2.2, we are also releasing a series of updates to the PyTorch domain libraries. More details can be found in the library updates blog.
This release is composed of 3,628 commits and 521 contributors since PyTorch 2.1. We want to sincerely thank our dedicated community for your contributions. As always, we encourage you to try these out and report any issues as we improve 2.2. More information about how to get started with the PyTorch 2-series can be found at our Getting Started page.
Summary:
scaled_dot_product_attention (SDPA) now supports FlashAttention-2, yielding around 2x speedups compared to previous versions.
PyTorch 2.2 introduces a new ahead-of-time extension of TorchInductor called AOTInductor, designed to compile and deploy PyTorch programs for non-python server-side.
torch.distributed supports a new abstraction for initializing and representing ProcessGroups called device_mesh.
PyTorch 2.2 ships a standardized, configurable logging mechanism called TORCH_LOGS.
A number of torch.compile improvements are included in PyTorch 2.2, including improved support for compiling Optimizers and improved TorchInductor fusion and layout optimizations.
Please note that we are deprecating macOS x86 support, and PyTorch 2.2.x will be the last version that supports macOS x64.
torch.ao.quantization now offers a prototype torch.export based flow
To provide a more stable migration for custom HTTPAdapters impacted
by the CVE changes in 2.32.0, we've renamed _get_connection to
a new public API, get_connection_with_tls_context. Existing custom
HTTPAdapters will need to migrate their code to use this new API.
get_connection is considered deprecated in all versions of Requests>=2.32.0.
A minimal (2-line) example has been provided in the linked PR to ease
migration, but we strongly urge users to evaluate if their custom adapter
is subject to the same issue described in CVE-2024-35195. (#6710)
v2.32.1
2.32.1 (2024-05-20)
Bugfixes
Add missing test certs to the sdist distributed on PyPI.
verify=True now reuses a global SSLContext which should improve
request time variance between first and subsequent requests. It should
also minimize certificate load time on Windows systems when using a Python
version built with OpenSSL 3.x. (#6667)
Requests now supports optional use of character detection
(chardet or charset_normalizer) when repackaged or vendored.
This enables pip and other projects to minimize their vendoring
surface area. The Response.text() and apparent_encoding APIs
will default to utf-8 if neither library is present. (#6702)
Bugfixes
Fixed bug in length detection where emoji length was incorrectly
calculated in the request content-length. (#6589)
Fixed deserialization bug in JSONDecodeError. (#6629)
Fixed bug where an extra leading / (path separator) could lead
urllib3 to unnecessarily reparse the request URI. (#6644)
To provide a more stable migration for custom HTTPAdapters impacted
by the CVE changes in 2.32.0, we've renamed _get_connection to
a new public API, get_connection_with_tls_context. Existing custom
HTTPAdapters will need to migrate their code to use this new API.
get_connection is considered deprecated in all versions of Requests>=2.32.0.
A minimal (2-line) example has been provided in the linked PR to ease
migration, but we strongly urge users to evaluate if their custom adapter
is subject to the same issue described in CVE-2024-35195. (#6710)
2.32.1 (2024-05-20)
Bugfixes
Add missing test certs to the sdist distributed on PyPI.
verify=True now reuses a global SSLContext which should improve
request time variance between first and subsequent requests. It should
also minimize certificate load time on Windows systems when using a Python
version built with OpenSSL 3.x. (#6667)
Requests now supports optional use of character detection
(chardet or charset_normalizer) when repackaged or vendored.
This enables pip and other projects to minimize their vendoring
surface area. The Response.text() and apparent_encoding APIs
will default to utf-8 if neither library is present. (#6702)
Bugfixes
Fixed bug in length detection where emoji length was incorrectly
calculated in the request content-length. (#6589)
Fixed deserialization bug in JSONDecodeError. (#6629)
Fixed bug where an extra leading / (path separator) could lead
urllib3 to unnecessarily reparse the request URI. (#6644)
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You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/StephanAkkerman/FluentAI/network/alerts).
Note
Automatic rebases have been disabled on this pull request as it has been open for over 30 days.
Bumps the pip group with 3 updates in the /transphoner_data directory: torch, requests and tqdm.
Updates
torch
from 2.0.1 to 2.2.0Release notes
Sourced from torch's releases.
... (truncated)
Commits
8ac9b20
Run docker release build on final tag (#117131) (#117182)2490352
Fix cuInit test on Windows (#117095)3a44bb7
[CI] Test that cuInit is not called during import (#117043)1c8ba38
[CI] Use jemalloc for CUDA builds (#116900) (#116988)96d2ddb
Store user model to simplify ONNXProgram.{adapt_torch_*,call} APIs (#1152...738b4a5
Update ONNX's IO Adapter to support FakeTensor with ExportedProgram (#114407)...4cf10bf
[Cherry-pick] [Quant] [PT2] Enable batchnorm in _move_exported_model_to_eval ...7e97e4b
[AARCH64] Fall back to GEMM if mkldnn_matmul fails (#115936) (#116666)1a3e3c7
[CUDA] baddmm should fall back to addmm for batch=1 (#114992) (#116518)ab7505f
Fix broken PyYAML 6.0 on MacOS x86 (#115956) (#116551)Updates
requests
from 2.31.0 to 2.32.2Release notes
Sourced from requests's releases.
... (truncated)
Changelog
Sourced from requests's changelog.
... (truncated)
Commits
88dce9d
v2.32.2c98e4d1
Merge pull request #6710 from nateprewitt/api_rename92075b3
Add deprecation warningaa1461b
Move _get_connection to get_connection_with_tls_context970e8ce
v2.32.1d6ebc4a
v2.32.09a40d12
Avoid reloading root certificates to improve concurrent performance (#6667)0c030f7
Merge pull request #6702 from nateprewitt/no_char_detection555b870
Allow character detection dependencies to be optional in post-packaging stepsd6dded3
Merge pull request #6700 from franekmagiera/update-redirect-to-invalid-uri-testUpdates
tqdm
from 4.66.2 to 4.66.3Release notes
Sourced from tqdm's releases.
Commits
4e613f8
Merge pull request from GHSA-g7vv-2v7x-gj9pb53348c
cli: eval safetyYou can trigger a rebase of this PR by commenting
@dependabot rebase
.Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot show