def nature_cnn(unscaled_images, **conv_kwargs):
    """
    CNN from Nature paper.
    """
    scaled_images = tf.cast(unscaled_images, tf.float32) / 255.
    activ = tf.nn.relu
    h = activ(conv(scaled_images, 'c1', nf=32, rf=8, stride=4, init_scale=np.sqrt(2),
                   **conv_kwargs))
    h2 = activ(conv(h, 'c2', nf=64, rf=4, stride=2, init_scale=np.sqrt(2), **conv_kwargs))
    h3 = activ(conv(h2, 'c3', nf=64, rf=3, stride=1, init_scale=np.sqrt(2), **conv_kwargs))
    h3 = conv_to_fc(h3)
    return activ(fc(h3, 'fc1', nh=512, init_scale=np.sqrt(2)))
def nature_cnn(unscaled_images, **conv_kwargs):
    """
    CNN from Nature paper.
    """
    scaled_images = tf.cast(unscaled_images, tf.float32) / 255.
    activ = tf.nn.relu
    h = activ(conv(scaled_images, 'c1', nf=32, rf=8, stride=4, init_scale=np.sqrt(2),
                   **conv_kwargs))
    h2 = activ(conv(h, 'c2', nf=64, rf=4, stride=2, init_scale=np.sqrt(2), **conv_kwargs))
    h3 = activ(conv(h2, 'c3', nf=64, rf=3, stride=1, init_scale=np.sqrt(2), **conv_kwargs))
    h3 = conv_to_fc(h3)
    return activ(fc(h3, 'fc1', nh=512, init_scale=np.sqrt(2)))
def nature_cnn ( unscaled_images , * * conv_kwargs ) : scaled_images = tf . cast ( unscaled_images , tf . float32 ) / 255. activ = tf . nn . relu h = activ ( conv ( scaled_images , 'c1' , nf = 32 , rf = 8 , stride = 4 , init_scale = np . sqrt ( 2 ) , * * conv_kwargs ) ) h2 = activ ( conv ( h , 'c2' , nf = 64 , rf = 4 , stride = 2 , init_scale = np . sqrt ( 2 ) , * * conv_kwargs ) ) h3 = activ ( conv ( h2 , 'c3' , nf = 64 , rf = 3 , stride = 1 , init_scale = np . sqrt ( 2 ) , * * conv_kwargs ) ) h3 = conv_to_fc ( h3 ) return activ ( fc ( h3 , 'fc1' , nh = 512 , init_scale = np . sqrt ( 2 ) ) )
CNN from Nature paper.
CNN from Nature paper .