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Use str(Path) instead of os.path.abspath(Path)

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oobabooga 2023-03-13 00:08:01 -03:00
parent b9e0712b92
commit 77294b27dd
3 changed files with 7 additions and 9 deletions
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3
extensions/silero_tts/script.py
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@ -1,4 +1,3 @@
import os
import time
from pathlib import Path
@ -113,7 +112,7 @@ def output_modifier(string):
output_file = Path(f'extensions/silero_tts/outputs/{shared.character}_{int(time.time())}.wav')
prosody = '<prosody rate="{}" pitch="{}">'.format(params['voice_speed'], params['voice_pitch'])
silero_input = f'<speak>{prosody}{xmlesc(string)}</prosody></speak>'
model.save_wav(ssml_text=silero_input, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=os.path.abspath(output_file))
model.save_wav(ssml_text=silero_input, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=str(output_file))
autoplay = 'autoplay' if params['autoplay'] else ''
string = f'<audio src="file/{output_file.as_posix()}" controls {autoplay}></audio>'

8
modules/RWKV.py
View file

@ -25,10 +25,10 @@ class RWKVModel:
tokenizer_path = Path(f"{path.parent}/20B_tokenizer.json")
if shared.args.rwkv_strategy is None:
model = RWKV(model=os.path.abspath(path), strategy=f'{device} {dtype}')
model = RWKV(model=str(path), strategy=f'{device} {dtype}')
else:
model = RWKV(model=os.path.abspath(path), strategy=shared.args.rwkv_strategy)
pipeline = PIPELINE(model, os.path.abspath(tokenizer_path))
model = RWKV(model=str(path), strategy=shared.args.rwkv_strategy)
pipeline = PIPELINE(model, str(tokenizer_path))
result = self()
result.pipeline = pipeline
@ -61,7 +61,7 @@ class RWKVTokenizer:
@classmethod
def from_pretrained(self, path):
tokenizer_path = path / "20B_tokenizer.json"
tokenizer = Tokenizer.from_file(os.path.abspath(tokenizer_path))
tokenizer = Tokenizer.from_file(str(tokenizer_path))
result = self()
result.tokenizer = tokenizer

5
modules/quantized_LLaMA.py
View file

@ -1,4 +1,3 @@
import os
import sys
from pathlib import Path
@ -7,7 +6,7 @@ import torch
import modules.shared as shared
sys.path.insert(0, os.path.abspath(Path("repositories/GPTQ-for-LLaMa")))
sys.path.insert(0, str(Path("repositories/GPTQ-for-LLaMa")))
from llama import load_quant
@ -41,7 +40,7 @@ def load_quantized_LLaMA(model_name):
print(f"Could not find {pt_model}, exiting...")
exit()
model = load_quant(path_to_model, os.path.abspath(pt_path), bits)
model = load_quant(path_to_model, str(pt_path), bits)
# Multi-GPU setup
if shared.args.gpu_memory: