From afd520f9a9b33dd6c87d07a97b3f5f6f77c8e92b Mon Sep 17 00:00:00 2001
From: cloveranon <cloveranon@nuke.africa>
Date: Mon, 23 Dec 2019 04:15:20 -0500
Subject: [PATCH] uses gpu by default

---
 config.ini       | 4 ++--
 gpt2generator.py | 6 ++++--
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/config.ini b/config.ini
index 0ba6480..28aa3f4 100644
--- a/config.ini
+++ b/config.ini
@@ -35,7 +35,7 @@ console-bell = on
 #		Not sure of a good default but 80 was considered an ideal standard number of columns in old PCs.
 text-wrap-width = 80
 
-cpu = off
+force-cpu = off
 
 log-level = 20
 
@@ -88,7 +88,7 @@ loading-message = 7;34
 message=7;35
 title = 31
 subtitle = 36
-subsubtitle = 35
+subsubtitle = 36;7
 instructions = 33
 selection-prompt = 7;32
 selection-value = 35
diff --git a/gpt2generator.py b/gpt2generator.py
index 94c8ff0..2447879 100644
--- a/gpt2generator.py
+++ b/gpt2generator.py
@@ -7,6 +7,8 @@ from transformers import GPT2LMHeadModel, GPT2Tokenizer
 from getconfig import settings, logger
 from story.utils import cut_trailing_sentence
 
+CPU = torch.cuda.is_available() and not settings.getboolean('force-cpu')
+
 # warnings.filterwarnings("ignore")
 MODEL_CLASSES = {
     "gpt2": (GPT2LMHeadModel, GPT2Tokenizer),
@@ -104,7 +106,7 @@ class GPT2Generator:
         self.top_p = top_p
         self.censor = censor
         self.samples = 1
-        self.dtype = torch.float32 if settings.getboolean('cpu') else torch.float16
+        self.dtype = torch.float32 if CPU else torch.float16
         self.repetition_penalty = repetition_penalty
         self.batch_size = 1
         self.stop_token = None
@@ -112,7 +114,7 @@ class GPT2Generator:
         self.model_name = "pytorch-gpt2-xl-aid2-v5"
         self.model_dir = "models"
         self.checkpoint_path = os.path.join(self.model_dir, self.model_name)
-        self.device = torch.device("cuda" if torch.cuda.is_available() and not settings.getboolean('cpu') else "cpu")
+        self.device = torch.device("cuda" if not CPU else "cpu")
         logger.info("Using device={}, checkpoint={}".format(self.device, self.checkpoint_path))
 
         # Load tokenizer and model