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Refine lib -> xautodl

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D-X-Y 2021-05-19 16:32:44 +08:00
parent 129c9e5251
commit a46095c2ee
4 changed files with 5 additions and 4 deletions
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3
CHANGE-LOG.md
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@ -8,4 +8,5 @@
- [2020.09.16] [7052265] Create NATS-BENCH. - [2020.09.16] [7052265] Create NATS-BENCH.
- [2020.10.15] [446262a](https://github.com/D-X-Y/AutoDL-Projects/tree/446262a) Update NATS-BENCH to version 1.0 - [2020.10.15] [446262a](https://github.com/D-X-Y/AutoDL-Projects/tree/446262a) Update NATS-BENCH to version 1.0
- [2020.12.20] [dae387a](https://github.com/D-X-Y/AutoDL-Projects/tree/dae387a) Update NATS-BENCH to version 1.1 - [2020.12.20] [dae387a](https://github.com/D-X-Y/AutoDL-Projects/tree/dae387a) Update NATS-BENCH to version 1.1
- [2021.05.18] [98fadf8](https://github.com/D-X-Y/AutoDL-Projects/tree/98fadf8086727f6311d477d0e4f2d5bb7e41ca59) Before moving to `xautodl` - [2021.05.18] [98fadf8](https://github.com/D-X-Y/AutoDL-Projects/tree/98fadf8) Before moving to `xautodl`
- [2021.05.19] [129c9e5](https://github.com/D-X-Y/AutoDL-Projects/tree/129c9e5) `xautodl` is close to ready

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docs/CVPR-2019-GDAS.md
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@ -11,7 +11,7 @@ Experiments on CIFAR-10, CIFAR-100, ImageNet, PTB, and WT2 are reported.
## Requirements and Preparation ## Requirements and Preparation
Please install `Python>=3.6` and `PyTorch>=1.2.0`. Please install `Python>=3.6` and `PyTorch>=1.5.0`.
CIFAR and ImageNet should be downloaded and extracted into `$TORCH_HOME`. CIFAR and ImageNet should be downloaded and extracted into `$TORCH_HOME`.

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xautodl/__init__.py
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@ -7,5 +7,5 @@
def version(): def version():
versions = ["0.9.9"] # 2021.05.18 versions = ["0.9.9"] # 2021.05.19
return versions[-1] return versions[-1]

2
xautodl/models/shape_searchs/generic_size_tiny_cell_model.py
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@ -11,7 +11,7 @@ import torch.nn as nn
from ..cell_operations import ResNetBasicblock from ..cell_operations import ResNetBasicblock
from ..cell_infers.cells import InferCell from ..cell_infers.cells import InferCell
from .shape_searchs.SoftSelect import select2withP, ChannelWiseInter from .SoftSelect import select2withP, ChannelWiseInter
class GenericNAS301Model(nn.Module): class GenericNAS301Model(nn.Module):