↓ 3 callersMethod__init__(self, block, layers, channels, classes=10,
norm_layer=BatchNorm, norm_kwargs=None, **kwargs)
gluoncv/model_zoo/cifarresnet.py:167
↓ 3 callersMethod__init__(self, in_channels, atrous_rates, norm_layer, norm_kwargs,
height=60, width=60)
gluoncv/model_zoo/deeplabv3.py:132
↓ 3 callersFunctiondetector_to_simple_pose(img, class_IDs, scores, bounding_boxs,
output_shape=(256, 192), scale=1.25, ctx=m
gluoncv/data/transforms/pose.py:252
↓ 2 callersMethod__init__(self, dataset, batch_size=None, shuffle=False, sampler=None,
last_batch=None, batch_sampler=
gluoncv/data/dataloader.py:109
↓ 2 callersMethod__init__(self, network, outputs, num_filters, use_1x1_transition=True,
use_bn=True, reduce_ratio=1.0,
gluoncv/nn/feature.py:131
↓ 2 callersMethod__init__(self, block, layers, classes=1000, dilated=False, norm_layer=BatchNorm,
norm_kwargs=None, la
gluoncv/model_zoo/resnetv1b.py:146
↓ 2 callersMethod__init__(self, nclass, backbone='resnet50', aux=True, ctx=cpu(), pretrained_base=True,
base_size=520,
gluoncv/model_zoo/pspnet.py:36
↓ 2 callersMethod__init__(self, stages, channels, anchors, strides, classes, alloc_size=(128, 128),
nms_thresh=0.45, n
gluoncv/model_zoo/yolo/yolo3.py:276