Hi, problem when running with with U.make_session(8)

[Kalelv45]

config must be a tf.ConfigProto, but got <class 'int'>

I get this error and I wasn't able to resolve.

[Kalelv45]

I solved this one ( I removed the 8) and left blank

but now I get this problem

module 'baselines.common.tf_util' has no attribute 'BatchInput'

[AdrianP-]

What version of tensorflow do you use? Try with 1.5 version

[abk11]

Hi,

I solved this exact same issue by pasting the following code right before U.make_session()

`class TfInput(object):
def init(self, name="(unnamed)"):
"""Generalized Tensorflow placeholder. The main differences are:
- possibly uses multiple placeholders internally and returns multiple values
- can apply light postprocessing to the value feed to placeholder.
"""
self.name = name
def get(self):
"""Return the tf variable(s) representing the possibly postprocessed value
of placeholder(s).
"""
raise NotImplementedError
def make_feed_dict(data):
"""Given data input it to the placeholder(s)."""
raise NotImplementedError

class PlaceholderTfInput(TfInput):
def init(self, placeholder):
"""Wrapper for regular tensorflow placeholder."""
super().init(placeholder.name)
self._placeholder = placeholder
def get(self):
return self._placeholder
def make_feed_dict(self, data):
return {self._placeholder: data}

class BatchInput(PlaceholderTfInput):
def init(self, shape, dtype=tf.float32, name=None):
"""Creates a placeholder for a batch of tensors of a given shape and dtype
Parameters
----------
shape: [int]
shape of a single elemenet of the batch
dtype: tf.dtype
number representation used for tensor contents
name: str
name of the underlying placeholder
"""
super().init(tf.placeholder(dtype, [None] + list(shape), name=name))`

Hope it ehlps

[AchillesRevng]

i am also getting the same error

TypeError: config must be a tf.ConfigProto, but got <class 'int'>

please help

[ghost]

calling Batchinput from deepq.utils seems to be working
import baselines.deepq.utils as x
x.BatchInput(env.observation_space.shape, name=name)....