# Written by Francois Fleuret <francois@fleuret.org>
+# torch.backends.cuda.matmul.allow_tf23
+# torch.autocast(torch.bfloat16)
+
import math, sys, argparse, time, tqdm, itertools, os
import torch, torchvision
######################################################################
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+if torch.cuda.is_available():
+ device = torch.device("cuda")
+ torch.backends.cuda.matmul.allow_tf32 = True
+else:
+ device = torch.device("cpu")
######################################################################
parser = argparse.ArgumentParser(
- description="An implementation of GPT with cache to solve a toy geometric reasonning task."
+ description="An implementation of GPT with cache to solve a toy geometric reasoning task."
)
parser.add_argument("--log_filename", type=str, default="train.log")
parser.add_argument("--dropout", type=float, default=0.1)
-parser.add_argument("--nb_oneshot_blocks", type=int, default=-1)
-
parser.add_argument("--deterministic_synthesis", action="store_true", default=False)
parser.add_argument("--no_checkpoint", action="store_true", default=False)
print(f"result directory {args.result_dir} already exists")
exit(1)
-log_file = open(os.path.join(args.result_dir, args.log_filename), "w")
+log_file = open(os.path.join(args.result_dir, args.log_filename), "a")
if args.seed >= 0:
# torch.backends.cudnn.deterministic = True
f"property_{prefix}miss {n_epoch} {100*nb_missing_properties/nb_requested_properties:.02f}%"
)
- img = picoclvr.descr2img(
- result_descr, [0], height=self.height, width=self.width
- )
+ img = picoclvr.descr2img(result_descr, height=self.height, width=self.width)
if img.dim() == 5:
if img.size(1) == 1: