checks input

.gitignore

@@ -0,0 +1,4 @@
+# git ignore all the csvs they are too big
+models/
+
+__pycache__/

app.py

@@ -1,18 +1,35 @@
 import gradio as gr
-
+import torch
+import lightning
+from minicons import cwe
+import pandas as pd
 import numpy as np
 
-def greet (word, sentence, model, layer, norm):
-    inputs = [word, sentence, model, str(layer), norm]
+from model import FeatureNormPredictor
+
+import sys
+sys.path.insert(0, '/home/jjr4354/semantic-features')
+
+def predict (word, sentence, lm_name, layer, norm):
+    if word not in sentence: return "invalid input: word not in sentence"
+    model_name = lm_name + str(layer) + '_to_' + norm
+    lm = cwe.CWE('bert-base-uncased')
+    if layer not in range (lm.layers): return "invalid input: layer not in lm"
+    model = FeatureNormPredictor.load_from_checkpoint(
+        checkpoint_path=model_name+'.ckpt',
+        map_location=None
+        )
+    model.eval()
+    inputs = [word, sentence, lm_name, str(layer), norm]
     outputs = [input+'\t'+str(np.random.randint(0,100, size=1)[0]) for input in inputs]
     return "\n".join(outputs)
 
 demo = gr.Interface(
-    fn=greet,
+    fn=predict,
     inputs=[
         "text", 
         "text", 
-        gr.Radio(["bert", "gpt2"]),
+        gr.Radio(["bert", "roberta", "electra"]),
         "number",
         gr.Radio(["Binder", "McRae", "Buchanan"]),
     ],