Merge pull request #8 from anthony-wang/Fix-path-slash

Fix path (slash)
anthony-wang · Jun 21, 2021 · 9e0d79c · 9e0d79c
2 parents 1271f11 + dcc3649
commit 9e0d79c
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Showing 3 changed files with 10 additions and 10 deletions.
diff --git a/benchmark_crabnet.py b/benchmark_crabnet.py
@@ -32,8 +32,8 @@ def get_model(mat_prop, classification=False, batch_size=None,
         model.classification = True
 
     # Get the datafiles you will learn from
-    train_data = rf'data\benchmark_data\{mat_prop}\train.csv'
-    val_data = rf'data\benchmark_data\{mat_prop}\val.csv'
+    train_data = f'data/benchmark_data/{mat_prop}/train.csv'
+    val_data = f'data/benchmark_data/{mat_prop}/val.csv'
 
     # Load the train and validation data before fitting the network
     data_size = pd.read_csv(train_data).shape[0]
@@ -79,7 +79,7 @@ def load_model(mat_prop, classification, file_name, verbose=True):
         model.classification = True
 
     # Load the data you want to predict with
-    data = rf'data\benchmark_data\{mat_prop}\{file_name}'
+    data = f'data/benchmark_data/{mat_prop}/{file_name}'
     # data is reloaded to model.data_loader
     model.load_data(data, batch_size=2**9, train=False)
     return model

diff --git a/matbench_crabnet.py b/matbench_crabnet.py
@@ -32,8 +32,8 @@ def get_model(mat_prop, i, classification=False, batch_size=None,
         model.classification = True
 
     # Get the datafiles you will learn from
-    train_data = rf'data\matbench_cv\{mat_prop}\train{i}.csv'
-    val_data = rf'data\matbench_cv\{mat_prop}\val{i}.csv'
+    train_data = f'data/matbench_cv/{mat_prop}/train{i}.csv'
+    val_data = f'data/matbench_cv/{mat_prop}/val{i}.csv'
 
     # Load the train and validation data before fitting the network
     data_size = pd.read_csv(train_data).shape[0]
@@ -79,7 +79,7 @@ def load_model(mat_prop, i, classification, file_name, verbose=True):
         model.classification = True
 
     # Load the data you want to predict with
-    data = rf'data\matbench_cv\{mat_prop}\{file_name}'
+    data = f'data/matbench_cv/{mat_prop}/{file_name}'
     # data is reloaded to model.data_loader
     model.load_data(data, batch_size=2**9)
     return model

diff --git a/train_crabnet.py b/train_crabnet.py
@@ -32,12 +32,12 @@ def get_model(data_dir, mat_prop, classification=False, batch_size=None,
         model.classification = True
 
     # Get the datafiles you will learn from
-    train_data = rf'{data_dir}\{mat_prop}\train.csv'
+    train_data = f'{data_dir}/{mat_prop}/train.csv'
     try:
-        val_data = rf'{data_dir}\{mat_prop}\val.csv'
+        val_data = f'{data_dir}/{mat_prop}/val.csv'
     except:
         print('Please ensure you have train (train.csv) and validation data',
-               f'(val.csv) in folder "data\materials_data\{mat_prop}"')
+               f'(val.csv) in folder "data/materials_data/{mat_prop}"')
 
     # Load the train and validation data before fitting the network
     data_size = pd.read_csv(train_data).shape[0]
@@ -80,7 +80,7 @@ def load_model(data_dir, mat_prop, classification, file_name, verbose=True):
         model.classification = True
 
     # Load the data you want to predict with
-    data = rf'{data_dir}\{mat_prop}\{file_name}'
+    data = f'{data_dir}/{mat_prop}/{file_name}'
     # data is reloaded to model.data_loader
     model.load_data(data, batch_size=2**9, train=False)
     return model