# we do not freeze the norm layers, as suggested by https://arxiv.org/abs/2103.05247 if 'norm' in name: continue else: p.requires_grad_(False) def forward_encoder(self, x: torch.Tensor, lead_times: torch.Tensor, variables): # x: `[B, T, V, H, W]` shape. if isinstance(vari...
表现这一点最明显的例子就是在Export Data时,用户可以选择是按this layers source data(数据源的坐标系统导出),还是按照the Data Frame(当前工作区的坐标系统)导出数据。 关于ArcMap的这种动态投影机制,我们可以利用一个北京54投影坐标系数据(乡镇.shp)和ArcGIS Installation Directory\DeveloperKit\SamepleCom\\data\...
Parts database 340 contains each part name and the various layers that are incorporated into each part. This can be better understood by visualizing the various layers as subparts for each part or each layer as being a sub-emplate that is one sub-template of the entire template, i.e. part...
TRAIN_DATA="data/RACE/train/middle" VALID_DATA="data/RACE/dev/middle \ data/RACE/dev/high" VOCAB_FILE=bert-vocab.txt PRETRAINED_CHECKPOINT=checkpoints/bert_345m CHECKPOINT_PATH=checkpoints/bert_345m_race COMMON_TASK_ARGS="--num-layers 24 \ --hidden-size 1024 \ --num-attention-heads 16...
basename = os.path.basename(self.mbtiles_file) self.remote =Falseelifself.wms_server:assertself.wms_layers, _("Request at least one layer") self.reader = WMSReader(self.wms_server, self.wms_layers, self.tile_size, **self.wms_options) ...
TRAIN_DATA="data/RACE/train/middle" VALID_DATA="data/RACE/dev/middle \ data/RACE/dev/high" VOCAB_FILE=bert-vocab.txt PRETRAINED_CHECKPOINT=checkpoints/bert_345m CHECKPOINT_PATH=checkpoints/bert_345m_race COMMON_TASK_ARGS="--num-layers 24 \ --hidden-size 1024 \ --num-attention-heads 16...
TRAIN_DATA="data/RACE/train/middle" VALID_DATA="data/RACE/dev/middle \ data/RACE/dev/high" VOCAB_FILE=bert-vocab.txt PRETRAINED_CHECKPOINT=checkpoints/bert_345m CHECKPOINT_PATH=checkpoints/bert_345m_race COMMON_TASK_ARGS="--num-layers 24 \ --hidden-size 1024 \ --num-attention-heads 16...