首先,train_set_y_orig.shape[0]表示获取train_set_y_orig数组的第一维大小。接下来,(1, train_set_y_orig.shape[0])表示新的形状为(1, train_set_y_orig.shape[0])。最后,train_set_y_orig.reshape()函数将train_set_y_orig数组重新调整为指定的形状。 这里使用了 NumPy 数组的reshape()方法,因此...
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ImageDenoising ImageSuperResolution MultispectralCD Pretrain util engine_pretrain.py main_pretrain_Spat.py main_pretrain_Spec.py models_mae_Spat.py models_mae_Spec.py README.md Breadcrumbs HyperSIGMA /Pretrain / Latest commit DotWang Add files via upload ...
reshape(-1)] _, cost, error = model.train(train_batch) pbar.set_postfix(cost=cost, error='{0:.2f}%'.format(error)) if j % int(0.25 * n_batch + 1) == 0 and j > 0: model.save() model.save() Example 30Source File: xp_3conv.py From brainforge with GNU General Public ...
optimizer.zero_grad(set_to_none=True) # Let's make sure we don't update any embedding weights besides the newly added token with torch.no_grad(): accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[index_no_updates] = orig_embeds_params[ ...
rpn_cls_score_reshape:1 2 351 64 ##reshape成前后景两类的概率 rpn_bbox_pred:1 36 39 64 ##9个anchors × 4个坐标值 此时系统开始构造该roi网络结构,然后进入类class AnchorTargetLayer(caffe.Layer): 设为0,则取出任何超过图像边界的proposals,只要超出一点点,都要去除 1. 我们进入self._anchors = ...
Files main .asset demo groundingdino.egg-info groundingdino multimodal-data vis_Dataset vis_results .gitignore LICENSE README.md git_commit_push.sh gitconfig.sh requirements.txt setup.py test.py train.py
check if this save would set us over the `checkpoints_total_limit` if args.checkpoints_total_limit is not None: checkpoints = os.listdir(args.output_dir) checkpoints = [d for d in checkpoints if d.startswith("checkpoint")] checkpoints = sorted(checkpoints, key=lambda x: int(x.split...
reshape(labels, logits.get_shape()) predictions = tf.argmax(logits, 3) #predictions = tf.squeeze(predictions) tf.summary.image('segmented_outputs/',tf.cast(tf.expand_dims(predictions,-1),tf.uint8),max_outputs=FLAGS.batch_size) #TODO slim.losses.softmax_cross_entropy( logits, labels, ...
deldat2[[tileNo]]$rownames.orig <- as.numeric(row.names(new_rawdeldata[[i]][[tileNo]])) #constructing parent polygons par_tile_polygon[[tileNo]] <- matrix( c(polygon_info[[(i - 1)]][[which(par_tile_indices[[(i - 1)]] == sec_index)]][[last_index]]$x, polygon_info[...