Update app.py

app.py

@@ -22,53 +22,53 @@ def generate_data(file, num_samples):
 
     return samples
 
-def generate_relational_data(parent_file, child_file, join_on):
-    parent_df = pd.read_csv(parent_file.name)
-    child_df = pd.read_csv(child_file.name)
-
-    #Make sure join_on column exists in both
-    assert ((join_on in parent_df.columns) and
-        (join_on in child_df.columns))
-
-    rtf_model.fit(parent_df.drop(join_on, axis=1), num_bootstrap=100)
-
-    pdir = Path("rtf_parent/")
-    rtf_model.save(pdir)
-
-    # # Get the most recently saved parent model,
-    # # or a specify some other saved model.
-    # parent_model_path = pdir / "idXXX"
-    parent_model_path = sorted([
-        p for p in pdir.glob("id*") if p.is_dir()],
-        key=os.path.getmtime)[-1]
-
-    child_model = REaLTabFormer(
-    model_type="relational",
-    parent_realtabformer_path=parent_model_path,
-    epochs = 25,
-    output_max_length=None,
-    train_size=0.8)
-
-    child_model.fit(
-    df=child_df,
-    in_df=parent_df,
-    join_on=join_on,
-    num_bootstrap=10)
-
-    # Generate parent samples.
-    parent_samples = rtf_model.sample(5)
-
-    # Create the unique ids based on the index.
-    parent_samples.index.name = join_on
-    parent_samples = parent_samples.reset_index()
-
-    # Generate the relational observations.
-    child_samples = child_model.sample(
-        input_unique_ids=parent_samples[join_on],
-        input_df=parent_samples.drop(join_on, axis=1),
-        gen_batch=5)
-
-    return parent_samples, child_samples, gr.update(visible = True)
+# def generate_relational_data(parent_file, child_file, join_on):
+#     parent_df = pd.read_csv(parent_file.name)
+#     child_df = pd.read_csv(child_file.name)
+
+#     #Make sure join_on column exists in both
+#     assert ((join_on in parent_df.columns) and
+#         (join_on in child_df.columns))
+
+#     rtf_model.fit(parent_df.drop(join_on, axis=1), num_bootstrap=100)
+
+#     pdir = Path("rtf_parent/")
+#     rtf_model.save(pdir)
+
+#     # # Get the most recently saved parent model,
+#     # # or a specify some other saved model.
+#     # parent_model_path = pdir / "idXXX"
+#     parent_model_path = sorted([
+#         p for p in pdir.glob("id*") if p.is_dir()],
+#         key=os.path.getmtime)[-1]
+
+#     child_model = REaLTabFormer(
+#     model_type="relational",
+#     parent_realtabformer_path=parent_model_path,
+#     epochs = 25,
+#     output_max_length=None,
+#     train_size=0.8)
+
+#     child_model.fit(
+#     df=child_df,
+#     in_df=parent_df,
+#     join_on=join_on,
+#     num_bootstrap=10)
+
+#     # Generate parent samples.
+#     parent_samples = rtf_model.sample(5)
+
+#     # Create the unique ids based on the index.
+#     parent_samples.index.name = join_on
+#     parent_samples = parent_samples.reset_index()
+
+#     # Generate the relational observations.
+#     child_samples = child_model.sample(
+#         input_unique_ids=parent_samples[join_on],
+#         input_df=parent_samples.drop(join_on, axis=1),
+#         gen_batch=5)
+
+#     return parent_samples, child_samples, gr.update(visible = True)
     
 
 
@@ -172,12 +172,12 @@ with gr.Blocks(css = css) as demo:
             num_samples = gr.Slider(label="Number of Samples", minimum=5, maximum=100, value=5, step=10)
             generate_data_btn = gr.Button('Generate Synthetic Data')
 
-        with gr.Tab("Upload Data as File: Relational Data"):
-            data_input_parent = gr.File(label = 'Upload Data File for Parent Dataset', file_types=[ ".csv"])
-            data_input_child = gr.File(label = 'Upload Data File for Child Dataset', file_types=[ ".csv"])
-            join_on = gr.Textbox(label = 'Column name to join on')
+        # with gr.Tab("Upload Data as File: Relational Data"):
+        #     data_input_parent = gr.File(label = 'Upload Data File for Parent Dataset', file_types=[ ".csv"])
+        #     data_input_child = gr.File(label = 'Upload Data File for Child Dataset', file_types=[ ".csv"])
+        #     join_on = gr.Textbox(label = 'Column name to join on')
             
-            generate_data_btn_relational = gr.Button('Generate Synthetic Data')
+        #     generate_data_btn_relational = gr.Button('Generate Synthetic Data')
 
         with gr.Row():
             #data_sample = gr.Dataframe(label = "Original Data")
@@ -187,7 +187,7 @@ with gr.Blocks(css = css) as demo:
     
     
     generate_data_btn.click(generate_data, inputs = [data_input_u,num_samples], outputs = [data_output])
-    generate_data_btn_relational.click(generate_relational_data, inputs = [data_input_parent,data_input_child,join_on], outputs = [data_output, data_output_child])
+    #generate_data_btn_relational.click(generate_relational_data, inputs = [data_input_parent,data_input_child,join_on], outputs = [data_output, data_output_child])
     examples = gr.Examples(examples=[['diabetes.arff',5], ["titanic.csv", 15]],inputs = [data_input_u,num_samples], outputs = [data_output], cache_examples = True, fn = generate_data)