Zennas score

.gitignore

@@ -1,3 +1,6 @@
+.base/*
+.torch/*
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

command.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+
+
+job_name=$1
+train_gpu=$2
+num_node=$3
+command=$4
+total_process=$((train_gpu*num_node))
+
+mkdir -p log
+
+now=$(date +"%Y%m%d_%H%M%S")
+
+# nohup 
+GLOG_vmodule=MemcachedClient=-1 \
+srun --partition=pat_dev \
+--mpi=pmi2 -n$total_process \
+--gres=gpu:$train_gpu \
+--ntasks-per-node=$train_gpu \
+--job-name=$job_name \
+--kill-on-bad-exit=1 \
+--cpus-per-task=5 \
+$command  2>&1|tee -a log/$job_name.log &
+# -x "SH-IDC1-10-198-4-[104,106]" \

configs/nas/mmcls/zennas/zennas_plainnet_search_8xb128_in1k.py

@@ -0,0 +1,15 @@
+_base_ = ['./zennas_plainnet_supernet_8xb128_in1k.py']
+
+# model = dict(norm_training=True)
+
+train_cfg = dict(
+    _delete_=True,
+    type='mmrazor.ZeroShotLoop',
+    dataloader=_base_.val_dataloader,
+    evaluator=_base_.val_evaluator,
+    search_space='mmrazor/models/architectures/backbones/SearchSpace/search_space_XXBL.py',
+    plainnet_struct_txt='./work_dirs/1ms/init_plainnet.txt',
+    max_epochs=480000, # evolution_max_iter
+    population_size=512,
+    num_classes=1000,
+)

configs/nas/mmcls/zennas/zennas_plainnet_supernet_8xb128_in1k.py

@@ -0,0 +1,28 @@
+_base_ = [
+    'mmrazor::_base_/settings/imagenet_bs1024_spos.py',
+    'mmcls::_base_/default_runtime.py',
+]
+
+# optim_wrapper=None
+model_wrapper_cfg = None
+optim_wrapper = dict(_delete_=True, type='OptimWrapper', optimizer=dict(type='SGD', lr=0.01))
+
+nas_backbone = dict(
+    _scope_='mmrazor',
+    type='MasterNet',
+    fix_subnet='./work_dirs/1ms/init_plainnet.txt',
+    no_create=True,
+    num_classes=1000)
+
+# model
+supernet = dict(
+    type='ImageClassifier',
+    data_preprocessor=_base_.preprocess_cfg,
+    backbone=nas_backbone)
+
+model = dict(
+    type='mmrazor.ZenNAS',
+    architecture=supernet
+)
+
+# find_unused_parameters = True

mmrazor/engine/runner/__init__.py

@@ -6,10 +6,11 @@
 from .slimmable_val_loop import SlimmableValLoop
 from .subnet_sampler_loop import GreedySamplerTrainLoop
 from .subnet_val_loop import SubnetValLoop
+from .zero_shot_loop import ZeroShotLoop
 
 __all__ = [
     'SingleTeacherDistillValLoop', 'DartsEpochBasedTrainLoop',
     'DartsIterBasedTrainLoop', 'SlimmableValLoop', 'EvolutionSearchLoop',
     'GreedySamplerTrainLoop', 'SubnetValLoop', 'SelfDistillValLoop',
-    'ItePruneValLoop'
+    'ItePruneValLoop', 'ZeroShotLoop'
 ]