Feeding issue for timestep placeholder in Ray 1.0.1.post1

kepricon · February 8, 2021, 7:19pm

@sven1977 Hi Sven,
I think [RLlib] Problem with TFModelV2 loading after having saved one with `TFPolicy.export_model()` - #2 by morsias is a similar issue.
Looks like you need to have a reproducible script, please check it out mine.

here’s my test code.

gist.github.com

https://gist.github.com/kepricon/516800ad7d8ef1b0b23df429c4d49490

gistfile1.txt

import random

import ray
from ray.tune import run, sample_from
from ray.tune.schedulers import PopulationBasedTraining

if __name__ == "__main__":
    class Stopper:
        def __init__(self):
            self.too_many_iter = False

This file has been truncated. show original

with Ray 1.0.0,
executed my test code and try to load the model.
tf.saved_model.load(‘model_1_0_0’) works well.

with Ray 1.0.1.post1
executed my test code and try to load the model.
tf.saved_model.load(‘model_1_0_1_post1’) doesn’t work.

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ValueError: Must pass in RNN state batches for placeholders [<tf.Tensor 'default_policy/Placeholder:0' shape=(?, 256) dtype=float32>, <tf.Tensor 'default_policy/Placeholder_1:0' shape=(?, 256) dtype=float32>], got [] RLlib	7	418	June 20, 2021
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Feeding issue for timestep placeholder in Ray 1.0.1.post1

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