updating pipeline

Signed-off-by: Jacob Renn <77127228+jacobrenn@users.noreply.github.com>

instruct_pipeline.py

@@ -108,53 +108,58 @@ class InstructionTextGenerationPipeline(Pipeline):
         return {"generated_sequence": generated_sequence, "input_ids": input_ids, "instruction_text": instruction_text}
 
     def postprocess(self, model_outputs, response_key_token_id, end_key_token_id, return_instruction_text):
-        sequence = model_outputs["generated_sequence"]
+        generated_sequence = model_outputs["generated_sequence"][0]
         instruction_text = model_outputs["instruction_text"]
 
-        # The response will be set to this variable if we can identify it.
-        decoded = None
-
-        # If we have token IDs for the response and end, then we can find the tokens and only decode between them.
-        if response_key_token_id and end_key_token_id:
-            # Find where "### Response:" is first found in the generated tokens.  Considering this is part of the
-            # prompt, we should definitely find it.  We will return the tokens found after this token.
-            response_pos = None
-            response_positions = np.where(sequence == response_key_token_id)[0]
-            if len(response_positions) == 0:
-                pass
+        records = []
+        for sequence in generated_sequence:
+
+            # The response will be set to this variable if we can identify it.
+            decoded = None
+
+            # If we have token IDs for the response and end, then we can find the tokens and only decode between them.
+            if response_key_token_id and end_key_token_id:
+                # Find where "### Response:" is first found in the generated tokens.  Considering this is part of the
+                # prompt, we should definitely find it.  We will return the tokens found after this token.
+                response_pos = None
+                response_positions = np.where(sequence == response_key_token_id)[0]
+                if len(response_positions) == 0:
+                    pass
+                else:
+                    response_pos = response_positions[0]
+
+                if response_pos:
+                    # Next find where "### End" is located.  The model has been trained to end its responses with this
+                    # sequence (or actually, the token ID it maps to, since it is a special token).  We may not find
+                    # this token, as the response could be truncated.  If we don't find it then just return everything
+                    # to the end.  Note that even though we set eos_token_id, we still see the this token at the end.
+                    end_pos = None
+                    end_positions = np.where(sequence == end_key_token_id)[0]
+                    if len(end_positions) > 0:
+                        end_pos = end_positions[0]
+
+                    decoded = self.tokenizer.decode(sequence[response_pos + 1 : end_pos]).strip()
             else:
-                response_pos = response_positions[0]
-
-            if response_pos:
-                # Next find where "### End" is located.  The model has been trained to end its responses with this
-                # sequence (or actually, the token ID it maps to, since it is a special token).  We may not find
-                # this token, as the response could be truncated.  If we don't find it then just return everything
-                # to the end.  Note that even though we set eos_token_id, we still see the this token at the end.
-                end_pos = None
-                end_positions = np.where(sequence == end_key_token_id)[0]
-                if len(end_positions) > 0:
-                    end_pos = end_positions[0]
-
-                decoded = self.tokenizer.decode(sequence[response_pos + 1 : end_pos]).strip()
-        else:
-            # Otherwise we'll decode everything and use a regex to find the response and end.
-
-            fully_decoded = self.tokenizer.decode(sequence)
-
-            # The response appears after "### Response:".  The model has been trained to append "### End" at the
-            # end.
-            m = re.search(r"#+\s*Response:\s*(.+?)#+\s*End", fully_decoded, flags=re.DOTALL)
-
-            if m:
-                decoded = m.group(1).strip()
-            else:
-                # The model might not generate the "### End" sequence before reaching the max tokens.  In this case,
-                # return everything after "### Response:".
-                m = re.search(r"#+\s*Response:\s*(.+)", fully_decoded, flags=re.DOTALL)
+                # Otherwise we'll decode everything and use a regex to find the response and end.
+
+                fully_decoded = self.tokenizer.decode(sequence)
+
+                # The response appears after "### Response:".  The model has been trained to append "### End" at the
+                # end.
+                m = re.search(r"#+\s*Response:\s*(.+?)#+\s*End", fully_decoded, flags=re.DOTALL)
+
                 if m:
                     decoded = m.group(1).strip()
+                else:
+                    # The model might not generate the "### End" sequence before reaching the max tokens.  In this case,
+                    # return everything after "### Response:".
+                    m = re.search(r"#+\s*Response:\s*(.+)", fully_decoded, flags=re.DOTALL)
+                    if m:
+                        decoded = m.group(1).strip()
+
+            if return_instruction_text:
+                records.append({"instruction_text": instruction_text, "generated_text": decoded})
+            else:
+                records.append({'generated_text': decoded})
 
-        if return_instruction_text:
-            return {"instruction_text": instruction_text, "generated_text": decoded}
-
-        return {'generated_text': decoded}
+        return records