Fix lint: ruff E713

Author: Nugine

bins/svc/preprocess.py

@@ -145,7 +145,7 @@ def preprocess(cfg, args):
             continue
         dataset_dir = os.path.join(output_path, dataset)
         metadata = []
-        for split in ["train", "test"] if not "eval" in dataset else ["test"]:
+        for split in ["train", "test"] if "eval" not in dataset else ["test"]:
             metadata_file_path = os.path.join(src_dataset_dir, "{}.json".format(split))
             with open(metadata_file_path, "r") as f:
                 metadata.extend(json.load(f))

bins/tta/preprocess.py

@@ -157,7 +157,7 @@ def preprocess(cfg, args):
             continue
         dataset_dir = os.path.join(output_path, dataset)
         metadata = []
-        for split in ["train", "test"] if not "eval" in dataset else ["test"]:
+        for split in ["train", "test"] if "eval" not in dataset else ["test"]:
             metadata_file_path = os.path.join(src_dataset_dir, "{}.json".format(split))
             with open(metadata_file_path, "r") as f:
                 metadata.extend(json.load(f))

bins/tts/preprocess.py

@@ -198,7 +198,7 @@ def preprocess(cfg, args):
             continue
         dataset_dir = os.path.join(output_path, dataset)
         metadata = []
-        for split in ["train", "test"] if not "eval" in dataset else ["test"]:
+        for split in ["train", "test"] if "eval" not in dataset else ["test"]:
             metadata_file_path = os.path.join(src_dataset_dir, "{}.json".format(split))
             with open(metadata_file_path, "r") as f:
                 metadata.extend(json.load(f))

bins/vocoder/preprocess.py

@@ -119,7 +119,7 @@ def preprocess(cfg, args):
             continue
         dataset_dir = os.path.join(output_path, dataset)
         metadata = []
-        for split in ["train", "test"] if not "eval" in dataset else ["test"]:
+        for split in ["train", "test"] if "eval" not in dataset else ["test"]:
             metadata_file_path = os.path.join(src_dataset_dir, "{}.json".format(split))
             with open(metadata_file_path, "r") as f:
                 metadata.extend(json.load(f))

models/tts/base/tts_inferece.py

@@ -158,7 +158,7 @@ def _load_model(
             assert checkpoint_dir is not None
             # Load the latest accelerator state dicts
             ls = [
-                str(i) for i in Path(checkpoint_dir).glob("*") if not "audio" in str(i)
+                str(i) for i in Path(checkpoint_dir).glob("*") if "audio" not in str(i)
             ]
             ls.sort(key=lambda x: int(x.split("_")[-3].split("-")[-1]), reverse=True)
             checkpoint_path = ls[0]

models/vocoders/vocoder_inference.py

@@ -281,7 +281,7 @@ def _load_model(self, checkpoint_dir, from_multi_gpu=False):
                 ls = [
                     str(i)
                     for i in Path(checkpoint_dir).glob("*")
-                    if not "audio" in str(i)
+                    if "audio" not in str(i)
                 ]
                 ls.sort(
                     key=lambda x: int(x.split("/")[-1].split("_")[0].split("-")[-1]),
@@ -443,7 +443,7 @@ def load_nnvocoder(
     else:
         # Load from accelerator state dict
         weights_file = os.path.join(weights_file, "checkpoint")
-        ls = [str(i) for i in Path(weights_file).glob("*") if not "audio" in str(i)]
+        ls = [str(i) for i in Path(weights_file).glob("*") if "audio" not in str(i)]
         ls.sort(key=lambda x: int(x.split("_")[-3].split("-")[-1]), reverse=True)
         checkpoint_path = ls[0]
         accelerator = accelerate.Accelerator()

utils/data_utils.py

@@ -149,7 +149,7 @@ def load_frame_pitch(
         pitch_statistic = []
         for utt_info in meta_data:
             utt = utt_info["Dataset"] + "_" + utt_info["Uid"]
-            if not utt2spk[utt] in spk2utt:
+            if utt2spk[utt] not in spk2utt:
                 spk2utt[utt2spk[utt]] = []
             spk2utt[utt2spk[utt]].append(utt)
 
@@ -242,7 +242,7 @@ def load_phone_pitch(
         pitch_statistic = []
         for utt_info in tqdm(meta_data):
             utt = utt_info["Dataset"] + "_" + utt_info["Uid"]
-            if not utt2spk[utt] in spk2utt:
+            if utt2spk[utt] not in spk2utt:
                 spk2utt[utt2spk[utt]] = []
             spk2utt[utt2spk[utt]].append(utt)
 
@@ -364,7 +364,7 @@ def load_energy(
         energy_statistic = []
         for utt_info in meta_data:
             utt = utt_info["Dataset"] + "_" + utt_info["Uid"]
-            if not utt2spk[utt] in spk2utt:
+            if utt2spk[utt] not in spk2utt:
                 spk2utt[utt2spk[utt]] = []
             spk2utt[utt2spk[utt]].append(utt)
 
@@ -438,7 +438,7 @@ def load_frame_energy(
         energy_statistic = []
         for utt_info in meta_data:
             utt = utt_info["Dataset"] + "_" + utt_info["Uid"]
-            if not utt2spk[utt] in spk2utt:
+            if utt2spk[utt] not in spk2utt:
                 spk2utt[utt2spk[utt]] = []
             spk2utt[utt2spk[utt]].append(utt)