"train_loader = torch.utils.data.DataLoader(train_data, batch_size=128, shuffle=True)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAI4AAACcCAYAAACp45OYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAA...
* Technical description of changes * During uploading, the users sees 2 or 3 bars rendered with `tqdm`: 1. [TIMESTAMP] Uploaded x scalars, y tensors (Y B), z binary objects (Z B) 2. (if any data was skipped): Skipped n tensors (N B), m binary objects (M B) 3. Uploading...
# 需要导入模块: import config [as 别名]# 或者: from config importDATA_DIR[as 别名]defmain():args = parse_args() path = os.path.abspath(args.PATH)ifpath.endswith(".manifest.template"):ifnotos.path.isfile(path): sys.exit("Cannot find file %r"% path) manifest_templates = [path]else...
"samples_filename_pattern": "", "save_images_add_number": true, "save_images_replace_action": "Replace", "grid_save": true, "grid_format": "png", "grid_extended_filename": false, "grid_only_if_multiple": true, "grid_prevent_empty_spots": false, "grid_zip_filename_pattern": "...
import core as bundles from sqlalchemy import create_engine import sys from logbook import Logger, StreamHandler from tqdm import tqdm from six import iteritems handler = StreamHandler(sys.stdout, format_string=" | {record.message}") logger = Logger(__name__) logger.handlers.append(handler) ...
iter_train = iter(data_loader) for step in tqdm(range(len(data_loader)), desc="forward step", leave=False): 169 changes: 121 additions & 48 deletions 169 smoe/entrypoint/analysis/scale_factor_simulation.py Original file line numberDiff line numberDiff line change @@ -6,9 +6,7 @@ ...
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