allow for overriding all dropouts, as well as convenience method for …

…dynamically setting target crop length

enformer_pytorch/enformer_pytorch.py

@@ -258,9 +258,9 @@ def __init__(
         heads = 8,
         output_heads = dict(human = 5313, mouse= 1643),
         target_length = TARGET_LENGTH,
-        dropout_rate = 0.4,
         num_alphabet = 4,
         attn_dim_key = 64,
+        dropout_rate = 0.4,
         attn_dropout = 0.05,
         pos_dropout = 0.01
     ):
@@ -359,6 +359,10 @@ def __init__(
             nn.Softplus()
         ), output_heads))
 
+    def set_target_length(self, target_length):
+        crop_module = self._trunk[-2]
+        crop_module.target_length = target_length
+
     @property
     def trunk(self):
         return self._trunk

enformer_pytorch/model_loader.py

@@ -35,9 +35,8 @@ def remove_nones(d):
 def load_pretrained_model(
     slug,
     force = False,
-    target_length = None,
-    dropout_rate = None,
-    model = None
+    model = None,
+    **kwargs
 ):
     if slug not in CONFIG:
         print(f'model {slug} not found among available choices: [{", ".join(CONFIG.keys())}]')
@@ -58,7 +57,7 @@ def load_pretrained_model(
 
     # load
 
-    override_params = remove_nones({'target_length': target_length, 'dropout_rate': dropout_rate})
+    override_params = remove_nones(kwargs)
     params = {**config['params'], **override_params}
 
     if not exists(model):

setup.py

@@ -4,7 +4,7 @@
   name = 'enformer-pytorch',
   packages = find_packages(exclude=[]),
   include_package_data = True,
-  version = '0.1.19',
+  version = '0.1.20',
   license='MIT',
   description = 'Enformer - Pytorch',
   author = 'Phil Wang',