pytorch/caffe2
Yinghai Lu e5e0bf4152 Add AdjustBatch Op (#16676)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16676

This op is used for changing batch size (first dimension) of the tensor.

Reviewed By: bertmaher, ipiszy

Differential Revision: D13929200

fbshipit-source-id: 4f2c3faec072d468be8301bf00c80d33adb3b5b3
2019-02-06 19:15:41 -08:00
..
contrib Rename IntList to IntArrayRef. (#16751) 2019-02-05 14:54:34 -08:00
core Rename IntList to IntArrayRef. (#16751) 2019-02-05 14:54:34 -08:00
cuda_rtc Back out "[pt1][tensor] Change ConvPoolOp<Context>::SetOutputSize to ConvPoolOp<Context>::GetOutputSize" (#16516) 2019-01-30 12:50:38 -08:00
db
distributed
experiments
ideep Fallback sum/add to CPU if needed (#15267) 2019-02-06 09:35:14 -08:00
image
mobile Try to turn off zero-out of tensors fully 2019-02-04 23:59:11 -08:00
mpi
observers
onnx Move away from ConstantFill (#16214) 2019-01-21 20:15:38 -08:00
operators Add AdjustBatch Op (#16676) 2019-02-06 19:15:41 -08:00
opt Use bound shape inference in onnxifi transform (#16598) 2019-02-06 16:34:37 -08:00
perfkernels more careful use of inline/template function in perfkernels (#15388) 2019-01-30 22:49:37 -08:00
predictor Fix/Improve bound shape inference with real net tests (#16597) 2019-02-06 10:41:07 -08:00
proto Add XLA / TPU device type, backend type and type id (#16763) 2019-02-05 12:56:44 -08:00
python Add AdjustBatch Op (#16676) 2019-02-06 19:15:41 -08:00
quantization int8 SpatialBN (#16796) 2019-02-06 15:32:01 -08:00
queue
serialize
sgd
share Back out "[pt1][tensor] Change ConvPoolOp<Context>::SetOutputSize to ConvPoolOp<Context>::GetOutputSize" (#16516) 2019-01-30 12:50:38 -08:00
test
transforms
utils Document hip-clang and its __HIP__ macro (#16771) 2019-02-05 15:13:52 -08:00
video
.clang-format
__init__.py
CMakeLists.txt Update the cmake build configuration for AppleClang compiler (#15820) 2019-02-04 08:53:47 -08:00
README.md
release-notes.md
requirements.txt
VERSION_NUMBER

Caffe2

Jenkins Build Status

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.

Further Resources on Caffe2.ai