changing compilation for tf compatibility

kundajelab · Apr 11, 2023 · 875affc · 875affc
1 parent d501bf9
commit 875affc
Show file tree

Hide file tree

Showing 4 changed files with 4 additions and 4 deletions.
diff --git a/chrombpnet/evaluation/make_bigwigs/predict_to_bigwig.py b/chrombpnet/evaluation/make_bigwigs/predict_to_bigwig.py
@@ -116,7 +116,7 @@ def load_model_wrapper(model_hdf5):
     # read .h5 model
     custom_objects={"multinomial_nll":losses.multinomial_nll, "tf": tf}    
     get_custom_objects().update(custom_objects)    
-    model=load_model(model_hdf5)
+    model=load_model(model_hdf5, compile=False)
     print("got the model")
     model.summary()
     return model

diff --git a/chrombpnet/evaluation/marginal_footprints/marginal_footprinting.py b/chrombpnet/evaluation/marginal_footprints/marginal_footprinting.py
@@ -26,7 +26,7 @@ def load_model_wrapper(args):
     # read .h5 model
     custom_objects={"multinomial_nll":losses.multinomial_nll, "tf": tf}    
     get_custom_objects().update(custom_objects)    
-    model=load_model(args.model_h5)
+    model=load_model(args.model_h5, compile=False)
     print("got the model")
     model.summary()
     return model

diff --git a/chrombpnet/evaluation/variant_effect_prediction/snp_scoring.py b/chrombpnet/evaluation/variant_effect_prediction/snp_scoring.py
@@ -32,7 +32,7 @@ def load_model_wrapper(args):
     # read .h5 model
     custom_objects={"tf": tf, "multinomial_nll":losses.multinomial_nll}    
     get_custom_objects().update(custom_objects)    
-    model=load_model(args.model_h5)
+    model=load_model(args.model_h5, compile=False)
     print("model loaded succesfully")
     return model
 

diff --git a/chrombpnet/training/predict.py b/chrombpnet/training/predict.py
@@ -55,7 +55,7 @@ def load_model_wrapper(args):
     # read .h5 model
     custom_objects={"tf": tf, "multinomial_nll":losses.multinomial_nll}    
     get_custom_objects().update(custom_objects)    
-    model=load_model(args.model_h5)
+    model=load_model(args.model_h5, compile=False)
     print("got the model")
     #model.summary()
     return model