Delete untitled32.py

untitled32.py

@@ -1,243 +0,0 @@
-import random
-import gradio as gr
-import openai
-import os
-
-openai.api_key = os.environ.get("open_ai_key")
-
-prompt = ['''
-You are a ''', 
-'''
-machine learning developer, trying to debug this code:
-
-StackTrace: 
-
-    Traceback (most recent call last):
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/process.py”, line 258, in _bootstrap
-    self.run()
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/process.py”, line 93, in run
-    self._target(*self._args, **self._kwargs)
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/site-packages/torch/utils/data/dataloader.py”, line 61, in _worker_loop
-    data_queue.put((idx, samples))
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/queues.py”, line 341, in put
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/reduction.py”, line 51, in dumps
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/site-packages/torch/multiprocessing/reductions.py”, line 121, in reduce_storage
-    RuntimeError: unable to open shared memory object </torch_54163_3383444026> in read-write mode at /opt/conda/conda-bld/pytorch_1525909934016/work/aten/src/TH/THAllocator.c:342
-
-    During handling of the above exception, another exception occurred:
-
-    Traceback (most recent call last):
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/util.py”, line 262, in _run_finalizers
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/util.py”, line 186, in call
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/shutil.py”, line 476, in rmtree
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/shutil.py”, line 474, in rmtree
-    OSError: [Errno 24] Too many open files: ‘/tmp/pymp-sgew4xdn’
-    Process Process-1:
-    Traceback (most recent call last):
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/process.py”, line 258, in _bootstrap
-    self.run()
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/process.py”, line 93, in run
-    self._target(*self._args, **self._kwargs)
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/site-packages/torch/utils/data/dataloader.py”, line 61, in _worker_loop
-    data_queue.put((idx, samples))
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/queues.py”, line 341, in put
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/reduction.py”, line 51, in dumps
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/site-packages/torch/multiprocessing/reductions.py”, line 121, in reduce_storage
-    RuntimeError: unable to open shared memory object </torch_54163_3383444026> in read-write mode at /opt/conda/conda-bld/pytorch_1525909934016/work/aten/src/TH/THAllocator.c:342
-    Traceback (most recent call last):
-    File “/home/nlpgpu3/LinoHong/FakeNewsByTitle/main.py”, line 25, in
-    for mini_batch in trainloader :
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/site-packages/torch/utils/data/dataloader.py”, line 280, in next
-    idx, batch = self._get_batch()
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/site-packages/torch/utils/data/dataloader.py”, line 259, in _get_batch
-    return self.data_queue.get()
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/queues.py”, line 335, in get
-    res = self._reader.recv_bytes()
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/connection.py”, line 216, in recv_bytes
-    buf = self._recv_bytes(maxlength)
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/connection.py”, line 407, in _recv_bytes
-    buf = self._recv(4)
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/multiprocessing/connection.py”, line 379, in _recv
-    chunk = read(handle, remaining)
-    File “/home/nlpgpu3/anaconda3/envs/linohong3/lib/python3.6/site-packages/torch/utils/data/dataloader.py”, line 178, in handler
-    _error_if_any_worker_fails()
-    RuntimeError: DataLoader worker (pid 54163) exited unexpectedly with exit code 1.
-
-    Process finished with exit code 1
-
-Question: Any idea how I can solve this problem?
-Are follow up questions needed here: Yes
-Follow up: Does your code run with less num_workers or num_workers=0? 
-Intermediate Answer: It worked when I set num_workers equals to 0, but doesn’t work greater or equal to 1
-Follow up: Could you try to increase the shared memory and try setting num_workers>0 again?
-Intermediate Answer: It worked! Can you explain what happened here? 
-So the final answer is: The error usually means that your system doesn’t provide enough shared memory for multiple workers (used via num_workers>0). Check the shared memory limitation of your system and try to increase it.
-
-
-StackTrace: 
-
-RuntimeError: size mismatch (got input: [100000], target: [1000]) 
-
-Question: Any idea how I can solve this problem?
-Are follow up questions needed here: No
-So the final answer is: I don’t know which line of code creates the shape mismatch but would guess it’s raised in the loss calculation: loss = criterion(output.view(-1), batch['input_ids'].view(-1).to(device)). Print the shapes of both tensors and make sure they are expected in the used criterion. PS you can post code snippets by wrapping them into three backticks ```, which would make your code easier to read.
-
-StackTrace: ''',
-'''
-Question: ''', 
-'''
-Are follow up questions needed here:''',]
-
-
-
-def extract_answer(generated):
-    if '\n' not in generated:
-        last_line =  generated
-    else: 
-        last_line = generated.split('\n')[-1]
-
-    if ':' not in last_line:
-        after_colon = last_line
-    else:
-        after_colon = generated.split(':')[-1]
-    
-    if ' ' == after_colon[0]:
-        after_colon = after_colon[1:]
-    if '.' == after_colon[-1]:
-        after_colon = after_colon[:-1]
-
-    return after_colon
-
-def extract_question(generated):
-    if '\n' not in generated:
-        last_line =  generated
-    else: 
-        last_line = generated.split('\n')[-1]
-
-    if 'Follow up:' not in last_line:
-      print('we probably should never get here...' + generated)
-
-    if ':' not in last_line:
-        after_colon = last_line
-    else:
-        after_colon = generated.split(':')[-1]
-    
-    if ' ' == after_colon[0]:
-        after_colon = after_colon[1:]
-    if '?' != after_colon[-1]:
-        print('we probably should never get here...' + generated)
-
-    return after_colon
-
-def get_last_line(generated):
-    if '\n' not in generated:
-        last_line =  generated
-    else: 
-        last_line = generated.split('\n')[-1]
-
-
-    return last_line
-  
-def greenify(input):
-  return "\x1b[102m" + input + "\x1b[0m"
-
-def yellowfy(input):
-  return "\x1b[106m" + input + "\x1b[0m"
-
-def call_gpt(cur_prompt, stop):
-    ans = openai.Completion.create(
-                model="text-davinci-002",
-                max_tokens=256,
-                stop=stop,
-                prompt=cur_prompt,
-                temperature=0.7,
-                top_p=1,
-                frequency_penalty=0,
-                presence_penalty=0
-              )  
-    returned = ans['choices'][0]['text']
-    print( greenify(returned), end='')
-    return returned
-
-def initial_query_builder(language, code, question, intermediate = "\nIntermediate Answer:", followup = "\nFollow up:", finalans= '\nSo the final answer is:'):
-  cur_prompt = prompt[0] +  language + prompt[1] + code + prompt[2] + question + prompt[3]
-
-  # print("prompt: ", cur_prompt, end ='')
-
-  ret_text = call_gpt(cur_prompt, intermediate)
-  print("ret_text: ", ret_text)
-  print("get_last_line(ret_text): ", get_last_line(ret_text))
-  return ret_text
-
-def subsequent_query_builder(curr_prompt, external_answer, intermediate = "\nIntermediate Answer:", followup = "\nFollow up:", finalans= '\nSo the final answer is:'):
-  curr_prompt += intermediate + ' ' + external_answer + '.'
-  print(intermediate + ' ' + yellowfy(external_answer) + '.', end='' )
-  ret_text = call_gpt(curr_prompt, intermediate)
-  return ret_text
-
-"""subsequent query builder: 
-
-the way to rebuild the prompt for each subsequent call: 
-
-1. every user response is 'intermediate answer' 
-2. until you hit 'so the final answer is: ' you're good
-3. 
-"""
-
-def prompt_builder(history, intermediate = "\nIntermediate Answer:", followup = "\nFollow up:", finalans= '\nSo the final answer is:'): 
-  #set language 
-  language = history[1][0]
-  #set stack trace 
-  stacktrace = history[0][0]
-  #set question (hardcoded)
-  question = "Any idea how I can solve this problem?"
-
-  # initial prompt
-  curr_prompt = prompt[0] +  language + prompt[1] + stacktrace + prompt[2] + question + prompt[3]
-
-  #set subsequent conversation thread
-  if len(history) > 2: #subsequent conversations have occurred 
-    curr_prompt += history[1][1] ## get the first response to the stacktrace prompt
-    for conversation in history[2:]:
-      #grab intermediate answer
-      curr_prompt += intermediate + ' ' + conversation[0] + '.'
-      #grab the follow up
-      curr_prompt += conversation[1]
-  return curr_prompt
-
-def chat(message, history):
-    history = history or []
-    print(len(history))
-    if len(history) == 0: ## just the stacktrace
-      response = "which language is this in? (python, java, c++, kotlin, etc.)"
-    elif len(history) == 1: ## stacktrace + just entered the language 
-      # get stacktrace
-      stacktrace = history[0][0]
-      # get language
-      language = message
-      # set question (hardcoded for v1)
-      question = "Any idea how I can solve this problem?"
-      response = initial_query_builder(language, stacktrace, question)
-    else: # subsequent prompts
-      # get stacktrace
-      stacktrace = history[0][0]
-      # get language
-      language = history[1][0]
-      # set question (hardcoded for v1)
-      question = "Any idea how I can solve this problem?"
-      curr_prompt = prompt_builder(history)
-      response = subsequent_query_builder(curr_prompt, message)
-      # response = query_builder(language, stacktrace, question)
-      print("response: ", response)
-    history.append((message, response))
-    return history, history
-
-chatbot = gr.Chatbot().style(color_map=("green", "pink"))
-demo = gr.Interface(
-    chat,
-    [gr.Textbox(placeholder="enter your stacktrace here"), "state"],
-    [chatbot, "state"],
-    allow_flagging="never",
-)
-if __name__ == "__main__":
-    demo.launch(debug=True)