add is_half argument to extract_feature_print.py (#1683)

* for GTX1650

* testing torch-profiler

* no more profiler & change default audio

* longer slice

* fluid container

* cache rmvpe and ui tweaks

* get my changes back after merge

* format code

* only load rmvpe when necessary

* fix rmvpe & config bug

* fix is_half again

* manual sync with upstream

* revert other changes for pull request

infer/modules/train/extract_feature_print.py

@@ -8,14 +8,16 @@ os.environ["PYTORCH_MPS_HIGH_WATERMARK_RATIO"] = "0.0"
 device = sys.argv[1]
 n_part = int(sys.argv[2])
 i_part = int(sys.argv[3])
-if len(sys.argv) == 6:
+if len(sys.argv) == 7:
     exp_dir = sys.argv[4]
     version = sys.argv[5]
+    is_half = bool(sys.argv[6])
 else:
     i_gpu = sys.argv[4]
     exp_dir = sys.argv[5]
     os.environ["CUDA_VISIBLE_DEVICES"] = str(i_gpu)
     version = sys.argv[6]
+    is_half = bool(sys.argv[7])
 import fairseq
 import numpy as np
 import soundfile as sf
@@ -91,8 +93,9 @@ models, saved_cfg, task = fairseq.checkpoint_utils.load_model_ensemble_and_task(
 model = models[0]
 model = model.to(device)
 printt("move model to %s" % device)
-if device not in ["mps", "cpu"]:
-    model = model.half()
+if is_half:
+    if device not in ["mps", "cpu"]:
+        model = model.half()
 model.eval()
 
 todo = sorted(list(os.listdir(wavPath)))[i_part::n_part]
@@ -113,9 +116,7 @@ else:
                 feats = readwave(wav_path, normalize=saved_cfg.task.normalize)
                 padding_mask = torch.BoolTensor(feats.shape).fill_(False)
                 inputs = {
-                    "source": feats.half().to(device)
-                    if device not in ["mps", "cpu"]
-                    else feats.to(device),
+                    "source": feats.half().to(device) if is_half and device not in ["mps", "cpu"] else feats.to(device),
                     "padding_mask": padding_mask.to(device),
                     "output_layer": 9 if version == "v1" else 12,  # layer 9
                 }