fixing config reader

eval.py

@@ -7,7 +7,7 @@ Hacked together by / Copyright 2020 Ross Wightman (https://github.com/rwightman)
 
 --- Usage: ---
 
-model = ClassificationModel('configs/eval.yaml')
+model = ClassificationModel()
 img = Image.open("image.jpg")
 out = model.eval(img)
 print(out)
@@ -34,8 +34,8 @@ def _update_config(config, params):
     return config
 
 
-def _fit(config_path, **kwargs):
-    with open(config_path) as stream:
+def _fit(**kwargs):
+    with open('configs/eval.yaml') as stream:
         base_config = yaml.safe_load(stream)
 
     if "config" in kwargs.keys():
@@ -51,8 +51,8 @@ def _fit(config_path, **kwargs):
     return update_cfg
 
 
-def _parse_args(config_path):
-    args = Dict(Fire(_fit(config_path)))
+def _parse_args():
+    args = Dict(Fire(_fit))
 
     # Cache the args as a text string to save them in the output dir later
     args_text = yaml.safe_dump(args.__dict__, default_flow_style=False)
@@ -60,8 +60,8 @@ def _parse_args(config_path):
 
 
 class ClassificationModel:
-    def __init__(self, config_path: str):
-        self.args, self.args_text = _parse_args(config_path)
+    def __init__(self):
+        self.args, self.args_text = _parse_args()
 
         # might as well try to do something useful...
         self.args.pretrained = self.args.pretrained or not self.args.checkpoint

inference.py

@@ -31,8 +31,8 @@ def _update_config(config, params):
     return config
 
 
-def _fit(config_path, **kwargs):
-    with open(config_path) as stream:
+def _fit(**kwargs):
+    with open('configs/inference.yaml') as stream:
         base_config = yaml.safe_load(stream)
 
     if "config" in kwargs.keys():
@@ -48,8 +48,8 @@ def _fit(config_path, **kwargs):
     return update_cfg
 
 
-def _parse_args(config_path):
-    args = Dict(Fire(_fit(config_path)))
+def _parse_args():
+    args = Dict(Fire(_fit))
 
     # Cache the args as a text string to save them in the output dir later
     args_text = yaml.safe_dump(args.__dict__, default_flow_style=False)
@@ -58,7 +58,7 @@ def _parse_args(config_path):
 
 def main():
     setup_default_logging()
-    args, args_text = _parse_args('configs/inference.yaml')
+    args, args_text = _parse_args()
     # might as well try to do something useful...
     args.pretrained = args.pretrained or not args.checkpoint
 

train.py

@@ -66,8 +66,8 @@ def _update_config(config, params):
     return config
 
 
-def _fit(config_path, **kwargs):
-    with open(config_path) as stream:
+def _fit(**kwargs):
+    with open('configs/train.yaml') as stream:
         base_config = yaml.safe_load(stream)
 
     if "config" in kwargs.keys():
@@ -83,8 +83,8 @@ def _fit(config_path, **kwargs):
     return update_cfg
 
 
-def _parse_args(config_path):
-    args = Dict(Fire(_fit(config_path)))
+def _parse_args():
+    args = Dict(Fire(_fit))
 
     # Cache the args as a text string to save them in the output dir later
     args_text = yaml.safe_dump(args.__dict__, default_flow_style=False)
@@ -103,7 +103,7 @@ def set_deterministic(seed=42, precision=13):
 
 def main():
     setup_default_logging()
-    args, args_text = _parse_args('configs/train.yaml')
+    args, args_text = _parse_args()
     set_deterministic(args.seed)
 
     args.prefetcher = not args.no_prefetcher

validate.py

@@ -51,8 +51,8 @@ def _update_config(config, params):
     return config
 
 
-def _fit(config_path, **kwargs):
-    with open(config_path) as stream:
+def _fit(**kwargs):
+    with open('configs/validate.yaml') as stream:
         base_config = yaml.safe_load(stream)
 
     if "config" in kwargs.keys():
@@ -68,8 +68,8 @@ def _fit(config_path, **kwargs):
     return update_cfg
 
 
-def _parse_args(config_path):
-    args = Dict(Fire(_fit(config_path)))
+def _parse_args():
+    args = Dict(Fire(_fit))
 
     # Cache the args as a text string to save them in the output dir later
     args_text = yaml.safe_dump(args.__dict__, default_flow_style=False)
@@ -233,7 +233,7 @@ def validate(args):
 
 def main():
     setup_default_logging()
-    args, args_text = _parse_args('configs/validate.yaml')
+    args, args_text = _parse_args()
 
     model_cfgs = []
     model_names = []