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Extend config

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This commit is contained in:
henryruhs
2025-03-12 16:21:47 +01:00
parent 8b465fce03
commit 2af4f2c8ab
6 changed files with 24 additions and 8 deletions
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embedding_converter/README.md
+3
View File
@@ -47,7 +47,10 @@ target_path = .models/arcface_simswap.pt
[training.trainer]
learning_rate = 0.001
max_epochs = 4096
strategy = auto
precision = 16-mixed
logger_path = .logs
logger_name = arcface_converter_simswap
```
```
embedding_converter/config.ini
+3
View File
@@ -13,7 +13,10 @@ target_path =
[training.trainer]
learning_rate =
max_epochs =
strategy =
precision =
logger_path =
logger_name =
[training.output]
directory_path =
embedding_converter/src/training.py
+5 -1
View File
@@ -89,15 +89,19 @@ def split_dataset(dataset : Dataset[Tensor]) -> Tuple[Dataset[Tensor], Dataset[T
def create_trainer() -> Trainer:
config_max_epochs = CONFIG_PARSER.getint('training.trainer', 'max_epochs')
config_strategy = CONFIG_PARSER.get('training.trainer', 'strategy')
config_precision = CONFIG_PARSER.get('training.trainer', 'precision')
config_logger_path = CONFIG_PARSER.get('training.trainer', 'logger_path')
config_logger_name = CONFIG_PARSER.get('training.trainer', 'logger_name')
config_directory_path = CONFIG_PARSER.get('training.output', 'directory_path')
config_file_pattern = CONFIG_PARSER.get('training.output', 'file_pattern')
logger = TensorBoardLogger('.logs', name = 'embedding_converter')
logger = TensorBoardLogger(config_logger_path, name = config_logger_name)
return Trainer(
logger = logger,
log_every_n_steps = 10,
max_epochs = config_max_epochs,
strategy = config_strategy,
precision = config_precision,
callbacks =
[
face_swapper/README.md
+4 -2
View File
@@ -89,9 +89,11 @@ expression_weight = 0.0
accumulate_size = 4
learning_rate = 0.0004
max_epochs = 50
precision = 16-mixed
preview_frequency = 250
strategy = auto
precision = 16-mixed
logger_path = .logs
logger_name = face_swapper
preview_frequency = 250
```
```
face_swapper/config.ini
+4 -2
View File
@@ -47,9 +47,11 @@ expression_weight =
accumulate_size =
learning_rate =
max_epochs =
precision =
preview_frequency =
strategy =
precision =
logger_path =
logger_name =
preview_frequency =
[training.output]
directory_path =
face_swapper/src/training.py
+5 -3
View File
@@ -208,18 +208,20 @@ def split_dataset(dataset : Dataset[Tensor]) -> Tuple[Dataset[Tensor], Dataset[T
def create_trainer() -> Trainer:
config_max_epochs = CONFIG_PARSER.getint('training.trainer', 'max_epochs')
config_precision = CONFIG_PARSER.get('training.trainer', 'precision')
config_strategy = CONFIG_PARSER.get('training.trainer', 'strategy')
config_precision = CONFIG_PARSER.get('training.trainer', 'precision')
config_logger_path = CONFIG_PARSER.get('training.trainer', 'logger_path')
config_logger_name = CONFIG_PARSER.get('training.trainer', 'logger_name')
config_directory_path = CONFIG_PARSER.get('training.output', 'directory_path')
config_file_pattern = CONFIG_PARSER.get('training.output', 'file_pattern')
logger = TensorBoardLogger('.logs', name = 'face_swapper')
logger = TensorBoardLogger(config_logger_path, name = config_logger_name)
return Trainer(
logger = logger,
log_every_n_steps = 10,
max_epochs = config_max_epochs,
precision = config_precision,
strategy = config_strategy,
precision = config_precision,
callbacks =
[
ModelCheckpoint(