Skip to main content

PyTorch Implementation of the Spline-Based Convolution Operator of SplineCNN (ROCm Build)

Project description

The author of this package has not provided a project description

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

torch_spline_conv_rocm-1.2.2.post1-cp314-cp314-manylinux_2_32_x86_64.whl (937.3 kB view details)

Uploaded CPython 3.14manylinux: glibc 2.32+ x86-64

torch_spline_conv_rocm-1.2.2.post1-cp313-cp313-manylinux_2_32_x86_64.whl (937.4 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.32+ x86-64

torch_spline_conv_rocm-1.2.2.post1-cp312-cp312-manylinux_2_32_x86_64.whl (937.7 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.32+ x86-64

torch_spline_conv_rocm-1.2.2.post1-cp311-cp311-manylinux_2_32_x86_64.whl (933.3 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.32+ x86-64

torch_spline_conv_rocm-1.2.2.post1-cp310-cp310-manylinux_2_32_x86_64.whl (930.4 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.32+ x86-64

File details

Details for the file torch_spline_conv_rocm-1.2.2.post1-cp314-cp314-manylinux_2_32_x86_64.whl.

File metadata

File hashes

Hashes for torch_spline_conv_rocm-1.2.2.post1-cp314-cp314-manylinux_2_32_x86_64.whl
Algorithm Hash digest
SHA256 1d002e66fd94e8eaf8636053b7a9fe991bb57a113df78f179620b4b78f768edd
MD5 3793e299d809574f6ead1acf34c61a99
BLAKE2b-256 cec89cf4562c669f25011e1a2bddbd1fb2ec90617aecc4a7f3c4aa6268db0227

See more details on using hashes here.

File details

Details for the file torch_spline_conv_rocm-1.2.2.post1-cp313-cp313-manylinux_2_32_x86_64.whl.

File metadata

File hashes

Hashes for torch_spline_conv_rocm-1.2.2.post1-cp313-cp313-manylinux_2_32_x86_64.whl
Algorithm Hash digest
SHA256 59fcb81c88f4604ba040f66db3e3b27f77b71fb23f0375ab91717ee9db4b556d
MD5 cb86d7f628e89be9a7812d045016a5fa
BLAKE2b-256 ae43015d5a95920dcd4bdbf1c3b4a2fb3cdeb5fb5731458704f3d078512bf077

See more details on using hashes here.

File details

Details for the file torch_spline_conv_rocm-1.2.2.post1-cp312-cp312-manylinux_2_32_x86_64.whl.

File metadata

File hashes

Hashes for torch_spline_conv_rocm-1.2.2.post1-cp312-cp312-manylinux_2_32_x86_64.whl
Algorithm Hash digest
SHA256 f31c6d9d059d1bac0e39bd58dc46f73080772de84df7ca12c15788c9f93c8b72
MD5 88920c6f5dc3dda250ea0117d6dd4882
BLAKE2b-256 3c58c5ed5fe5d923296f427765711f785ec44e414e8c0aa5772515fddf611d51

See more details on using hashes here.

File details

Details for the file torch_spline_conv_rocm-1.2.2.post1-cp311-cp311-manylinux_2_32_x86_64.whl.

File metadata

File hashes

Hashes for torch_spline_conv_rocm-1.2.2.post1-cp311-cp311-manylinux_2_32_x86_64.whl
Algorithm Hash digest
SHA256 8f4b540ca271ab26863cd79e410e776a3f31d337242ed1e232eaff63cb77c3e5
MD5 1668d13fc7fcda44f4ae03d91f4dd6a7
BLAKE2b-256 bd114fb7fe9e9254b3c78f8b0173d0c7a5f4eb9445fa2ab4dbacc6ae29c85e8e

See more details on using hashes here.

File details

Details for the file torch_spline_conv_rocm-1.2.2.post1-cp310-cp310-manylinux_2_32_x86_64.whl.

File metadata

File hashes

Hashes for torch_spline_conv_rocm-1.2.2.post1-cp310-cp310-manylinux_2_32_x86_64.whl
Algorithm Hash digest
SHA256 96874d25e6b7c1ae83e8da6b36e9196a38d791a56bf2c5ce20055d3d04633979
MD5 e3b8685f4989f48031850969330b58aa
BLAKE2b-256 8e35cf0daa4fc15e627e6740335f70b359c2c497fd405f9f1e44c2ab2875f4b5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page