Add int search space

exps/basic-eval.py

@@ -24,14 +24,24 @@ assert torch.cuda.is_available(), "torch.cuda is not available"
 
 def main(args):
 
-    assert os.path.isdir(args.data_path), "invalid data-path : {:}".format(args.data_path)
-    assert os.path.isfile(args.checkpoint), "invalid checkpoint : {:}".format(args.checkpoint)
+    assert os.path.isdir(args.data_path), "invalid data-path : {:}".format(
+        args.data_path
+    )
+    assert os.path.isfile(args.checkpoint), "invalid checkpoint : {:}".format(
+        args.checkpoint
+    )
 
     checkpoint = torch.load(args.checkpoint)
     xargs = checkpoint["args"]
-    train_data, valid_data, xshape, class_num = get_datasets(xargs.dataset, args.data_path, xargs.cutout_length)
+    train_data, valid_data, xshape, class_num = get_datasets(
+        xargs.dataset, args.data_path, xargs.cutout_length
+    )
     valid_loader = torch.utils.data.DataLoader(
-        valid_data, batch_size=xargs.batch_size, shuffle=False, num_workers=xargs.workers, pin_memory=True
+        valid_data,
+        batch_size=xargs.batch_size,
+        shuffle=False,
+        num_workers=xargs.workers,
+        pin_memory=True,
     )
 
     logger = PrintLogger()
@@ -41,7 +51,11 @@ def main(args):
     logger.log("model ====>>>>:\n{:}".format(base_model))
     logger.log("model information : {:}".format(base_model.get_message()))
     logger.log("-" * 50)
-    logger.log("Params={:.2f} MB, FLOPs={:.2f} M ... = {:.2f} G".format(param, flop, flop / 1e3))
+    logger.log(
+        "Params={:.2f} MB, FLOPs={:.2f} M ... = {:.2f} G".format(
+            param, flop, flop / 1e3
+        )
+    )
     logger.log("-" * 50)
     logger.log("valid_data : {:}".format(valid_data))
     optim_config = dict2config(checkpoint["optim-config"], logger)
@@ -54,23 +68,44 @@ def main(args):
 
     try:
         valid_loss, valid_acc1, valid_acc5 = valid_func(
-            valid_loader, network, criterion, optim_config, "pure-evaluation", xargs.print_freq_eval, logger
+            valid_loader,
+            network,
+            criterion,
+            optim_config,
+            "pure-evaluation",
+            xargs.print_freq_eval,
+            logger,
         )
     except:
         _, valid_func = get_procedures("basic")
         valid_loss, valid_acc1, valid_acc5 = valid_func(
-            valid_loader, network, criterion, optim_config, "pure-evaluation", xargs.print_freq_eval, logger
+            valid_loader,
+            network,
+            criterion,
+            optim_config,
+            "pure-evaluation",
+            xargs.print_freq_eval,
+            logger,
         )
 
     num_bytes = torch.cuda.max_memory_cached(next(network.parameters()).device) * 1.0
     logger.log(
         "***{:s}*** EVALUATION loss = {:.6f}, accuracy@1 = {:.2f}, accuracy@5 = {:.2f}, error@1 = {:.2f}, error@5 = {:.2f}".format(
-            time_string(), valid_loss, valid_acc1, valid_acc5, 100 - valid_acc1, 100 - valid_acc5
+            time_string(),
+            valid_loss,
+            valid_acc1,
+            valid_acc5,
+            100 - valid_acc1,
+            100 - valid_acc5,
         )
     )
     logger.log(
         "[GPU-Memory-Usage on {:} is {:} bytes, {:.2f} KB, {:.2f} MB, {:.2f} GB.]".format(
-            next(network.parameters()).device, int(num_bytes), num_bytes / 1e3, num_bytes / 1e6, num_bytes / 1e9
+            next(network.parameters()).device,
+            int(num_bytes),
+            num_bytes / 1e3,
+            num_bytes / 1e6,
+            num_bytes / 1e9,
         )
     )
     logger.close()
@@ -79,6 +114,8 @@ def main(args):
 if __name__ == "__main__":
     parser = argparse.ArgumentParser("Evaluate-CNN")
     parser.add_argument("--data_path", type=str, help="Path to dataset.")
-    parser.add_argument("--checkpoint", type=str, help="Choose between Cifar10/100 and ImageNet.")
+    parser.add_argument(
+        "--checkpoint", type=str, help="Choose between Cifar10/100 and ImageNet."
+    )
     args = parser.parse_args()
     main(args)