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Richard Liaw
f34d705178
* init_changes * last_changes * addressing comments * fix comments * update * nit
48 lines
1.9 KiB
Python
48 lines
1.9 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import tensorflow as tf
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class Model(object):
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"""Defines an abstract network model for use with RLlib.
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Models convert input tensors to a number of output features. These features
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can then be interpreted by ActionDistribution classes to determine
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e.g. agent action values.
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The last layer of the network can also be retrieved if the algorithm
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needs to further post-processing (e.g. Actor and Critic networks in A3C).
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If `options["free_log_std"]` is True, the last half of the
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output layer will be free variables that are not dependent on
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inputs. This is often used if the output of the network is used
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to parametrize a probability distribution. In this case, the
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first half of the parameters can be interpreted as a location
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parameter (like a mean) and the second half can be interpreted as
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a scale parameter (like a standard deviation).
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Attributes:
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inputs (Tensor): The input placeholder for this model.
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outputs (Tensor): The output vector of this model.
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last_layer (Tensor): The network layer right before the model output.
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"""
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def __init__(self, inputs, num_outputs, options):
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self.inputs = inputs
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if options.get("free_log_std", False):
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assert num_outputs % 2 == 0
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num_outputs = num_outputs // 2
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self.outputs, self.last_layer = self._init(
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inputs, num_outputs, options)
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if options.get("free_log_std", False):
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log_std = tf.get_variable(name="log_std", shape=[num_outputs],
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initializer=tf.zeros_initializer)
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self.outputs = tf.concat(
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[self.outputs, 0.0 * self.outputs + log_std], 1)
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def _init(self):
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"""Builds and returns the output and last layer of the network."""
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raise NotImplementedError
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