Bump thinc from 6.10.0 to 6.12.1

[dependabot-preview]

Bumps thinc from 6.10.0 to 6.12.1.

Release notes

Sourced from thinc's releases.

v6.12.1: Fix messagepack pin

🔴 Bug fixes

• Fix issue ValueError: 2539520 exceeds max_bin_len(1048576) when uses spacy.load() explosion/spaCy#2995: Pin msgpack to version <0.6.0, to avoid the low message-length limit introduced in v0.6.0, which breaks spaCy. We will relax the pin once spaCy is updated to set the max_xx_len argument to msgpack.dumps()

v6.12.0: Wheels and separate GPU ops

✨ New features and improvements

• Update dependencies to be able to provide binary wheels.
• Move GPU ops to separate package, thinc_gpu_ops.
• Support pip specifiers for GPU installation, e.g. pip install thinc[cuda92].

🔴 Bug fixes

• Update murmurhash pin to accept newer version.

v6.11.2: Improve GPU installation

✨ New features and improvements

You can now require GPU capability using the pip "extras" syntax. Thinc also now expects CUDA to be installed at /usr/local/cuda by default. If you've installed it elsewhere, you can specify the location with the CUDA_HOME environment variable. Once Thinc is able to find CUDA, you can tell pip to install Thinc with cupy, as follows:

• thinc[cuda]: Install cupy from source (compatible with a range of cuda versions)
• thinc[cuda80]: Install the cupy-cuda80 wheel
• thinc[cuda90]: Install the cupy-cuda90 wheel
• thinc[cuda91]: Install the cupy-cuda91 wheel

If you're installing Thinc from a local wheel file, the syntax for adding an "extras" specifier is a bit unintuitive. The trick is to make the file path into a URL, so you can use an #egg clause, as follows:

pip install file://path/to/wheel#egg=thinc[cuda]

6.11.1: Support direct linkage to BLAS libraries

✨ New features and improvements

• Thinc now vendorizes OpenBLAS's cblas_sgemm function, and delegates matrix multiplications to it by default. The provided function is single-threaded, making it easy to call Thinc from multiple processes. The default sgemm function can be overridden using the THINC_BLAS environment variable --- see below.
• thinc.neural.util.get_ops now understands device integers, e.g. 0 for GPU 0, as well as strings like "cpu" and "cupy".
• Update StaticVectors model, to make use of spaCy v2.0's Vectors class.
• New .gemm() method on NumpyOps and CupyOps classes, allowing matrix and vector multiplication to be handled with a simple function. Example usage:

Customizing the matrix multiplication backend

Previous versions of Thinc have relied on numpy for matrix multiplications. When numpy is installed via wheel using pip (the default), numpy will usually be linked against a suboptimal matrix multiplication kernel. This made it difficult to ensure that Thinc was well optimized for the target machine.

To fix this, Thinc now provides its own matrix multiplications, by bundling the source code for OpenBLAS's sgemm kernel within the library. To change the default BLAS library, you can specify an environment variable, giving the location of the shared library you want to link against:

THINC_BLAS=/opt/openblas/lib/libopenblas.so pip install thinc --no-cache-dir --no-binary
export LD_LIBRARY_PATH=/opt/openblas/lib
</tr></table> ... (truncated)

Commits

• a6badde Add build support to fabfile
• f6a1cff Add buildkite script
• 14c3cc2 Set version to v6.12.1
• 84b3181 Pin msgpack to <0.6.0
• 6e9091c Fix require_gpu
• b003ebe Fix require_gpu
• 45a032a Improve version pin
• cda35e1 Set thinc to 6.12.0
• 34b666e Set version to 6.10.6
• 4052dac Fix version pin
• Additional commits viewable in compare view

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[dependabot-preview]

Superseded by #155.