コード例 #1
0
def conv_lstm_inputs_test():
    mycfg = {
        'test': False,
        'use_lstm': True,
        'batch_size': 32,
        'rollout_len': 2,
        'nlstm': 64,
        'hs_len': 64 * 2,
        'lstm_layer_norm': True
    }

    ob_space = spaces.Tuple([
        spaces.Tuple([
            spaces.Box(shape=(11, 11, 22), dtype=np.float32, low=0, high=1),
            spaces.Box(shape=[6], dtype=np.bool, low=0, high=1)
        ])
    ] * 2)
    ac_space = spaces.Tuple([spaces.Discrete(n=6)] * 2)

    nc = net_config_cls(ob_space, ac_space, **mycfg)
    inputs = net_inputs_placeholders_fun(nc)
    print(inputs.X)
    print(inputs.A)
    print(inputs.S)
    print(inputs.M)
    pass
コード例 #2
0
def conv_lstm_test():
    mycfg = {
        'test': False,
        'use_loss_type': 'rl_vtrace',
        'use_value_head': True,
        'n_v': 1,
        'sync_statistics': None,
        'use_lstm': True,
        'batch_size': 32,
        'rollout_len': 8,
        'nlstm': 64,
        'hs_len': 64 * 2,
        'lstm_layer_norm': True,
        'weight_decay': 0.0005,
        'lam': 0.99,
    }

    ob_space = spaces.Tuple([
        spaces.Tuple([
            spaces.Box(shape=(11, 11, 22), dtype=np.float32, low=0, high=1),
            spaces.Box(shape=(2, ), dtype=np.int32, low=0, high=10),
            spaces.Box(shape=[6], dtype=np.bool, low=0, high=1)
        ])
    ] * 2)
    ac_space = spaces.Tuple([spaces.Discrete(n=6)] * 2)

    nc = net_config_cls(ob_space, ac_space, **mycfg)
    nc.reward_weights = np.ones(shape=nc.reward_weights_shape,
                                dtype=np.float32)
    inputs = net_inputs_placeholders_fun(nc)
    out = net_build_fun(inputs, nc, scope='conv_lstm')

    print(out.value_head)
    assert out.value_head is not None

    print(out.loss.total_reg_loss)
    print(out.loss.loss_endpoints)
    print(out.loss.pg_loss)
    assert out.loss.pg_loss is not None
    print(out.loss.value_loss)
    assert out.loss.value_loss is not None

    print(out.vars.lstm_vars)
    print(len(out.vars.lstm_vars))
    print(out.vars.all_vars)
    print(len(out.vars.all_vars))

    for v in out.vars.all_vars:
        print(v.name)

    print(out.endpoints)
    pass
コード例 #3
0
def conv_lstm_actor_test():
    mycfg = {
        'test': False,
        'use_loss_type': 'none',
        'use_value_head': False,
        'n_v': 4,
        'sync_statistics': None,
        'use_lstm': True,
        'batch_size': 1,
        'rollout_len': 1,
        'nlstm': 64,
        'hs_len': 64 * 2,
        'lstm_layer_norm': True,
        'weight_decay': 0.0005
    }

    ob_space = spaces.Tuple([
        spaces.Tuple([
            spaces.Box(shape=(11, 11, 22), dtype=np.float32, low=0, high=1),
            spaces.Box(shape=(2, ), dtype=np.int32, low=0, high=10),
            spaces.Box(shape=[6], dtype=np.bool, low=0, high=1)
        ])
    ] * 2)
    ac_space = spaces.Tuple([spaces.Discrete(n=6)] * 2)

    nc = net_config_cls(ob_space, ac_space, **mycfg)
    inputs = net_inputs_placeholders_fun(nc)
    out = net_build_fun(inputs, nc, scope='conv_lstm')
    sample = ob_space.sample()
    sess = tf.Session()
    tf.global_variables_initializer().run(session=sess)
    feed_dict = {}
    for s, input in zip(sample, inputs.X):
        for x_np, x in zip(s, input):
            feed_dict[x] = [x_np]
    feed_dict[inputs.S] = np.zeros(shape=[1, nc.hs_len])
    feed_dict[inputs.M] = np.zeros(shape=[1])
    from tensorflow.contrib.framework import nest
    import tpolicies.tp_utils as tp_utils
    ac_structure = tp_utils.template_structure_from_gym_space(ac_space)
    a = nest.map_structure_up_to(ac_structure, lambda head: head.sam,
                                 out.self_fed_heads)
    sam = sess.run(a, feed_dict=feed_dict)
    print(sam)
    pass