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Add EdgeTPU models to sotabench, remove some unicode chars from model names

pull/30/head
Ross Wightman 2019-08-24 14:42:51 -07:00
parent 9ec6824bab
commit 9816ca3ab4
1 changed files with 12 additions and 5 deletions
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17
sotabench.py
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@ -1,6 +1,7 @@
from torchbench.image_classification import ImageNet
from timm import create_model, list_models
from timm.data import resolve_data_config, create_transform
import os
NUM_GPU = 1
BATCH_SIZE = 256 * NUM_GPU
@ -86,13 +87,13 @@ model_map = dict(
gluon_xception65=_attrib(
paper_model_name='Modified Aligned Xception', paper_arxiv_id='1802.02611', batch_size=BATCH_SIZE//2),
ig_resnext101_32x8d=_attrib(
paper_model_name='ResNeXt-101 32×8d', paper_arxiv_id='1805.00932'),
paper_model_name='ResNeXt-101 32x8d', paper_arxiv_id='1805.00932'),
ig_resnext101_32x16d=_attrib(
paper_model_name='ResNeXt-101 32×16d', paper_arxiv_id='1805.00932'),
paper_model_name='ResNeXt-101 32x16d', paper_arxiv_id='1805.00932'),
ig_resnext101_32x32d=_attrib(
paper_model_name='ResNeXt-101 32×32d', paper_arxiv_id='1805.00932', batch_size=BATCH_SIZE//2),
paper_model_name='ResNeXt-101 32x32d', paper_arxiv_id='1805.00932', batch_size=BATCH_SIZE//2),
ig_resnext101_32x48d=_attrib(
paper_model_name='ResNeXt-101 32×48d', paper_arxiv_id='1805.00932', batch_size=BATCH_SIZE//4),
paper_model_name='ResNeXt-101 32x48d', paper_arxiv_id='1805.00932', batch_size=BATCH_SIZE//4),
inception_resnet_v2=_attrib(
paper_model_name='Inception ResNet V2', paper_arxiv_id='1602.07261'),
#inception_v3=dict(paper_model_name='Inception V3', paper_arxiv_id=), # same weights as torchvision
@ -167,6 +168,12 @@ model_map = dict(
paper_model_name='EfficientNet-B6', paper_arxiv_id='1905.11946', batch_size=BATCH_SIZE//8),
tf_efficientnet_b7=_attrib(
paper_model_name='EfficientNet-B7', paper_arxiv_id='1905.11946', batch_size=BATCH_SIZE//8),
tf_efficientnet_es=_attrib(
paper_model_name='EfficientNet-EdgeTPU-S', paper_arxiv_id='1905.11946'),
tf_efficientnet_em=_attrib(
paper_model_name='EfficientNet-EdgeTPU-M', paper_arxiv_id='1905.11946'),
tf_efficientnet_el=_attrib(
paper_model_name='EfficientNet-EdgeTPU-L', paper_arxiv_id='1905.11946', batch_size=BATCH_SIZE//2),
tf_inception_v3=_attrib(
paper_model_name='Inception V3', paper_arxiv_id='1512.00567'),
tf_mixnet_l=_attrib(
@ -208,7 +215,7 @@ for model_name in model_names:
input_transform=input_transform,
batch_size=model_map[model_name]['batch_size'],
num_gpu=NUM_GPU,
#data_root=DATA_ROOT
data_root=os.environ.get('IMAGENET_DIR', './imagenet')
)