update pipeline & readme

Author: SivilTaram

awakening_latent_grounding/README.md

@@ -1,3 +1,7 @@
+# README
+
+This code is still incomplete. We will actively update it when the code is totally ready.
+
 # Environment Setup
 
 ```

awakening_latent_grounding/inference/pipeline_torchscript.py

@@ -5,22 +5,24 @@
 import torch
 from .pipeline_base import NLBindingInferencePipeline
 
+
 class NLBindingTorchScriptPipeline(NLBindingInferencePipeline):
     def __init__(self,
-        model_dir: str,
-        greedy_linking: bool,
-        threshold: float=0.2,
-        num_threads: int=8,
-        use_gpu: bool = torch.cuda.is_available()
-    ) -> None:
+                 model_dir: str,
+                 greedy_linking: bool,
+                 threshold: float = 0.2,
+                 num_threads: int = 8,
+                 use_gpu: bool = torch.cuda.is_available()
+                 ) -> None:
         super().__init__(model_dir, greedy_linking=greedy_linking, threshold=threshold)
 
         self.device = torch.device('cuda') if use_gpu else torch.device('cpu')
         model_file = "nl_binding.script.bin"
 
         torch.set_num_interop_threads(2)
         torch.set_num_threads(num_threads)
-        print('Torch model Threads: {}, {}, {}'.format(torch.get_num_interop_threads(), torch.get_num_threads(), self.device))
+        print('Torch model Threads: {}, {}, {}'.format(torch.get_num_interop_threads(), torch.get_num_threads(),
+                                                       self.device))
         model_ckpt_path = os.path.join(model_dir, model_file)
         self.model = torch.jit.load(model_ckpt_path, map_location=self.device)
         self.model.eval()