Visual watcher when training/evaluating or tensorboard equivalence?
Hi, As leveraging python ecosystem seems one of the main reasons for switching to pytorch from Torch 7, would you provide guidance to visually overseeing training/evaluating with 3rd party Python libraries that is hard to do in pure Torch 7 ? For example,
pengsun
smth
Atcold
Atcold
pengsun
edgarriba
Hi, noob question here - might be especially relevant for people moving over from TensorFlow? I just wonder if anyone has got Crayon working for multi-threads? I can’t figure it out? I keep getting this error <SCODE>Traceback (most recent call last):
  File "/home/ajay/anaconda3/envs/pyphi/lib/python3.6/multiprocessing/process.py", line 249, in _bootstrap
    self.run()
  File "/home/ajay/anaconda3/envs/pyphi/lib/python3.6/multiprocessing/process.py", line 93, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ajay/PythonProjects/PyT_Neural_Arch_Search_v1_2/train_v1.py", line 201, in train
    foo.get_scalar_values("Mean Reward")
  File "/home/ajay/anaconda3/envs/pyphi/lib/python3.6/site-packages/pycrayon/crayon.py", line 167, in get_scalar_values
    return json.loads(r.text)
  File "/home/ajay/anaconda3/envs/pyphi/lib/python3.6/json/__init__.py", line 354, in loads
    return _default_decoder.decode(s)
  File "/home/ajay/anaconda3/envs/pyphi/lib/python3.6/json/decoder.py", line 339, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/home/ajay/anaconda3/envs/pyphi/lib/python3.6/json/decoder.py", line 357, in raw_decode
    raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
<ECODE> It works fine through when I run the following from the interpreter, <SCODE>from pycrayon import CrayonClient
cc = CrayonClient( hostname="http://127.0.1.1" , port=8889)
foo = cc.create_experiment("train_" + str(rank))

foo.add_scalar_value("Mean Reward", mean_reward, step = episode_count)
foo.add_scalar_value("Max Reward" , max_reward,  step = episode_count)

foo.get_scalar_values("Mean Reward")
foo.get_scalar_values("Max Reward")
<ECODE>
AjayTalati
Nevermind, it works without the extra lines, <SCODE>foo.get_scalar_values("Mean Reward")
foo.get_scalar_values("Max Reward")
<ECODE> Also I needed to give distinct date time’s for each of the threads, <SCODE>cc = CrayonClient( hostname="http://127.0.1.1" , port=8889)
exp_name = "train_" + str(rank) + "_" + datetime.now().strftime('train_%m-%d_%H-%M') # prevents server errors ??
foo = cc.create_experiment(exp_name)<ECODE>
AjayTalati
ibadami