ccbe291ec9859698a57147b1033d503a7739dfa9,tensorforce/core/distributions/gaussian.py,Gaussian,create_tf_operations,#Gaussian#Any#Any#,48

Before Change

        self.mean = layers["linear"](x=x, size=flat_size, bias=self.mean)
        self.mean = tf.reshape(tensor=self.mean, shape=((-1,) + self.shape))
        self.log_stddev = layers["linear"](x=x, size=flat_size, bias=self.log_stddev)
        self.log_stddev = tf.reshape(tensor=self.log_stddev, shape=((-1,) + self.shape))
        self.log_stddev = tf.minimum(x=self.log_stddev, y=10.0)  // prevent infinity when exp
        self.distribution = (self.mean, self.log_stddev)
        self.deterministic = deterministic

After Change

        self.log_stddev = tf.reshape(tensor=self.log_stddev, shape=shape)

        // clip log stddev for numerical stability
        log_eps = log(util.epsilon)
        self.log_stddev = tf.clip_by_value(t=self.log_stddev, clip_value_min=log_eps, clip_value_max=-log_eps)

        // standard deviation
        self.stddev = tf.exp(x=self.log_stddev)

        // general distribution values
        self.distribution = (self.mean, self.log_stddev)
        self.deterministic = deterministic

Instances