Update pipeline.py

pipeline.py

@@ -25,14 +25,19 @@ class PreTrainedPipeline():
         self.model = model = LSTMTextGenerator.from_pretrained("miittnnss/lstm-textgen-pets")
  
     def __call__(self, inputs: str):
-        """
-        Args:
-            inputs (:obj:`str`):
-                a string containing some text
-        Return:
-            A :obj:`PIL.Image` with the raw image representation as PIL.
-        """
-        # IMPLEMENT_THIS
-        raise NotImplementedError(
-            "Please implement PreTrainedPipeline __call__ function"
-        )
+        seed_numerical_data = [char_to_index[char] for char in inputs]
+        with torch.no_grad():
+            input_sequence = torch.LongTensor([seed_numerical_data]).to(device)
+            hidden = model.init_hidden(1)
+
+            generated_text = inputs  # Initialize generated text with seed text
+            temperature = 0.7 # Temperature for temperature sampling
+
+            for _ in range(500):
+                output, hidden = model(input_sequence, hidden)
+                probabilities = nn.functional.softmax(output[-1, 0] / temperature, dim=0).cpu().numpy()
+                predicted_index = random.choices(range(output_size), weights=probabilities, k=1)[0]
+                generated_text += index_to_char[predicted_index]  # Append the generated character to the text
+                input_sequence = torch.LongTensor([[predicted_index]]).to(device)
+
+        return output