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ee8d5e5249
Summary: Implementation of the cosine learning rate in: https://arxiv.org/pdf/1608.03983.pdf. Mostly inspired from: https://github.com/pytorch/fairseq/blob/master/fairseq/optim/lr_scheduler/cosine_lr_scheduler.py Pull Request resolved: https://github.com/pytorch/pytorch/pull/29017 Test Plan: buck test -v 2 caffe2/caffe2/fb/dper/layer_models/tests/split_1:sparse_nn_test -- test_composite_cosine_lr_policy learning rate log with max_lr=0.3, initial_period=20, t_mult=0.95, lr_shrink=0.95: P120327179 https://pxl.cl/PrcP full canary: https://fburl.com/fblearner/mw69ylsd Differential Revision: D18195868 Pulled By: grantlj fbshipit-source-id: 67bdb0b8dd31d040d16b29d0da3115907bd141ef |
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| core | ||
| cuda_rtc | ||
| db | ||
| distributed | ||
| experiments | ||
| ideep | ||
| image | ||
| mobile | ||
| mpi | ||
| observers | ||
| onnx | ||
| operators | ||
| opt | ||
| perfkernels | ||
| predictor | ||
| proto | ||
| python | ||
| quantization | ||
| queue | ||
| serialize | ||
| sgd | ||
| share | ||
| test | ||
| transforms | ||
| utils | ||
| video | ||
| __init__.py | ||
| .clang-format | ||
| c2_aten_srcs.bzl | ||
| CMakeLists.txt | ||
| README.md | ||
| release-notes.md | ||
| requirements.txt | ||
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Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind.
Questions and Feedback
Please use Github issues (https://github.com/pytorch/pytorch/issues) to ask questions, report bugs, and request new features.