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Fix training times by fixing fp16 detection

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This commit is contained in:
kalomaze
2023-07-22 22:47:38 -05:00
parent b280c8c7bc
commit 593b740709
1 changed files with 53 additions and 11 deletions
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64
config.py
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@@ -1,20 +1,62 @@
import argparse
import sys
import torch
import json
from multiprocessing import cpu_count
global usefp16
usefp16 = False
def use_fp32_config():
for config_file in ["32k.json", "40k.json", "48k.json"]:
with open(f"configs/{config_file}", "r") as f:
strr = f.read().replace("true", "false")
with open(f"configs/{config_file}", "w") as f:
f.write(strr)
with open("trainset_preprocess_pipeline_print.py", "r") as f:
strr = f.read().replace("3.7", "3.0")
with open("trainset_preprocess_pipeline_print.py", "w") as f:
f.write(strr)
usefp16 = False
device_capability = 0
if torch.cuda.is_available():
device = torch.device("cuda:0") # Assuming you have only one GPU (index 0).
device_capability = torch.cuda.get_device_capability(device)[0]
if device_capability >= 7:
usefp16 = True
for config_file in ["32k.json", "40k.json", "48k.json"]:
with open(f"configs/{config_file}", "r") as d:
data = json.load(d)
if "train" in data and "fp16_run" in data["train"]:
data["train"]["fp16_run"] = True
with open(f"configs/{config_file}", "w") as d:
json.dump(data, d, indent=4)
print(f"Set fp16_run to true in {config_file}")
with open("trainset_preprocess_pipeline_print.py", "r", encoding="utf-8") as f:
strr = f.read()
strr = strr.replace("3.0", "3.7")
with open("trainset_preprocess_pipeline_print.py", "w", encoding="utf-8") as f:
f.write(strr)
else:
for config_file in ["32k.json", "40k.json", "48k.json"]:
with open(f"configs/{config_file}", "r") as f:
data = json.load(f)
if "train" in data and "fp16_run" in data["train"]:
data["train"]["fp16_run"] = False
with open(f"configs/{config_file}", "w") as d:
json.dump(data, d, indent=4)
print(f"Set fp16_run to false in {config_file}")
with open("trainset_preprocess_pipeline_print.py", "r", encoding="utf-8") as f:
strr = f.read()
strr = strr.replace("3.7", "3.0")
with open("trainset_preprocess_pipeline_print.py", "w", encoding="utf-8") as f:
f.write(strr)
else:
print("CUDA is not available. Make sure you have an NVIDIA GPU and CUDA installed.")
return (usefp16, device_capability)
class Config:
def __init__(self):
@@ -95,9 +137,9 @@ class Config:
):
print("Found GPU", self.gpu_name, ", force to fp32")
self.is_half = False
use_fp32_config()
else:
print("Found GPU", self.gpu_name)
use_fp32_config()
self.gpu_mem = int(
torch.cuda.get_device_properties(i_device).total_memory
/ 1024
@@ -143,4 +185,4 @@ class Config:
x_center = 30
x_max = 32
return x_pad, x_query, x_center, x_max
return x_pad, x_query, x_center, x_max