Remove GradioDeprecationWarning

chatbot_constructor.py

@@ -38,7 +38,7 @@ def train(message: str = "", regularization: float = 0.0001, dropout: float = 0.
             if data in os.listdir("cache"): # data = filename
                 data_hash = data # set the hash to the file name
             else:
-                return "Dataset example:\nquestion→answer\nquestion→answer\netc."
+                return "Data example:\nquestion→answer\nquestion→answer\netc."
     dset, responses = todset(data)
     resps_len = len(responses)
     tokenizer = Tokenizer()
@@ -117,16 +117,16 @@ def train(message: str = "", regularization: float = 0.0001, dropout: float = 0.
 
 if __name__ == "__main__":
     iface = gr.Interface(fn=train, inputs=["text",
-                                           gr.inputs.Slider(0, 0.01, default=0.0001, step=1e-8, label="Regularization L1"),
-                                           gr.inputs.Slider(0, 0.5, default=0.1, step=1e-8, label="Dropout"),
-                                           gr.inputs.Slider(1e-8, 0.01, default=0.001, step=1e-8, label="Learning rate"),
-                                           gr.inputs.Slider(1, 64, default=32, step=1, label="Epochs"),
-                                           gr.inputs.Slider(1, 256, default=88, step=1, label="Embedding size"),
-                                           gr.inputs.Slider(1, 128, default=16, step=1, label="Input Length"),
-                                           gr.inputs.Slider(1, 128, default=64, step=1, label="Convolution kernel count"),
-                                           gr.inputs.Slider(1, 16, default=2, step=1, label="Convolution kernel size"),
-                                           gr.inputs.Checkbox(False, label="Use left padding"),
-                                           gr.inputs.Radio(['softmax', 'sigmoid', 'linear', 'softplus', 'exponential', 'log_softmax'], label="Output activation function"),
+                                           gr.components.Slider(0, 0.01, default=0.0001, step=1e-8, label="Regularization L1"),
+                                           gr.components.Slider(0, 0.5, default=0.1, step=1e-8, label="Dropout"),
+                                           gr.components.Slider(1e-8, 0.01, default=0.001, step=1e-8, label="Learning rate"),
+                                           gr.components.Slider(1, 64, default=32, step=1, label="Epochs"),
+                                           gr.components.Slider(1, 256, default=88, step=1, label="Embedding size"),
+                                           gr.components.Slider(1, 128, default=16, step=1, label="Input Length"),
+                                           gr.components.Slider(1, 128, default=64, step=1, label="Convolution kernel count"),
+                                           gr.components.Slider(1, 16, default=2, step=1, label="Convolution kernel size"),
+                                           gr.components.Checkbox(False, label="Use left padding"),
+                                           gr.components.Radio(['softmax', 'sigmoid', 'linear', 'softplus', 'exponential', 'log_softmax'], label="Output activation function"),
                                            "text"],
                          outputs="text")
     iface.launch()