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Functions148 in github.com/CausalRL/DRL

⨍ Functions 148◇ Types & classes 8
↓ 38 callersFunctionfc_net
(opts, inp, in_layers, out_layers, scope, in_activation=tf.nn.softplus, reuse=tf.AUTO_REUSE)
model_decon_uBernoulli/utils.py:154
↓ 38 callersFunctionfc_net
(opts, inp, in_layers, out_layers, scope, in_activation=tf.nn.softplus, reuse=tf.AUTO_REUSE)
ac_decon/utils.py:154
↓ 38 callersFunctionfc_net
(opts, inp, in_layers, out_layers, scope, in_activation=tf.nn.softplus, reuse=tf.AUTO_REUSE)
model_decon_uGaussian/utils.py:154
↓ 7 callersFunctiongaussianNLL
(data, mu, cov, mask=None)
ac_decon/utils.py:267
↓ 5 callersFunctiongaussianNLL
(data, mu, cov, mask=None)
model_decon_uBernoulli/utils.py:275
↓ 5 callersFunctiongaussianNLL
(data, mu, cov, mask=None)
model_decon_uGaussian/utils.py:275
↓ 5 callersMethodp_r_g_z_a_u
(self, z, a, u)
ac_decon/model_decon.py:102
↓ 5 callersMethodq_z_g_z_x_a_r
(self, x_seq, a_seq, r_seq, mask=None)
ac_decon/model_decon.py:312
↓ 4 callersFunctionac_fc_net
(opts, inp, in_layers, out_layers, scope, is_training=True, in_activation=tf.nn.relu, reuse=tf.A
ac_decon/utils.py:175
↓ 4 callersFunctionencoder
(opts, inp, in_channels, out_channel, scope, in_activation=tf.nn.softplus, out_activation=tf.nn.so
model_decon_uBernoulli/utils.py:198
↓ 4 callersFunctionencoder
(opts, inp, in_channels, out_channel, scope, in_activation=tf.nn.softplus, out_activation=tf.nn.so
ac_decon/utils.py:198
↓ 4 callersFunctionencoder
(opts, inp, in_channels, out_channel, scope, in_activation=tf.nn.softplus, out_activation=tf.nn.so
model_decon_uGaussian/utils.py:198
↓ 4 callersMethodlstm_net
(self, lstm_input, suffix, mask=None)
model_decon_uBernoulli/model_decon.py:200
↓ 4 callersMethodlstm_net
(self, lstm_input, suffix, mask=None)
ac_decon/model_decon.py:198
↓ 4 callersMethodlstm_net
(self, lstm_input, suffix, mask=None)
model_decon_uGaussian/model_decon.py:198
↓ 4 callersMethodp_z_g_z_a
(self, z, a)
ac_decon/model_decon.py:123
↓ 4 callersMethodq_u_g_x_a_r
(self, x_seq, a_seq, r_seq, mask=None)
model_decon_uBernoulli/model_decon.py:399
↓ 4 callersMethodq_u_g_x_a_r
(self, x_seq, a_seq, r_seq, mask=None)
ac_decon/model_decon.py:397
↓ 4 callersMethodq_u_g_x_a_r
(self, x_seq, a_seq, r_seq, mask=None)
model_decon_uGaussian/model_decon.py:397
↓ 3 callersMethodcritic_net
(self, z, a, reuse, is_training, trainable)
ac_decon/decon_ac_test.py:207
↓ 3 callersMethodcritic_net
(self, z, a, reuse, is_training, trainable)
ac_decon/decon_ac_train.py:209
↓ 3 callersFunctionfully_connected_layer
(opts, inp, out_dim, scope, reuse=tf.AUTO_REUSE)
model_decon_uBernoulli/utils.py:16
↓ 3 callersFunctionfully_connected_layer
(opts, inp, out_dim, scope, reuse=tf.AUTO_REUSE)
ac_decon/utils.py:16
↓ 3 callersFunctionfully_connected_layer
(opts, inp, out_dim, scope, reuse=tf.AUTO_REUSE)
model_decon_uGaussian/utils.py:16
↓ 3 callersMethodp_r_g_z_a_u
(self, z, a, u)
model_decon_uBernoulli/model_decon.py:104
↓ 3 callersMethodp_r_g_z_a_u
(self, z, a, u)
model_decon_uGaussian/model_decon.py:102
↓ 3 callersMethodp_x_g_z_u
(self, z, u)
model_decon_uBernoulli/model_decon.py:42
↓ 3 callersMethodp_x_g_z_u
(self, z, u)
ac_decon/model_decon.py:40
↓ 3 callersMethodp_x_g_z_u
(self, z, u)
model_decon_uGaussian/model_decon.py:40
↓ 3 callersMethodq_z_g_z_x_a_r
(self, x_seq, a_seq, r_seq, mask=None)
model_decon_uBernoulli/model_decon.py:314
↓ 3 callersMethodq_z_g_z_x_a_r
(self, x_seq, a_seq, r_seq, mask=None)
model_decon_uGaussian/model_decon.py:312
↓ 2 callersMethodactor_net
(self, z, reuse, is_training, trainable)
ac_decon/decon_ac_test.py:199
↓ 2 callersMethodactor_net
(self, z, reuse, is_training, trainable)
ac_decon/decon_ac_train.py:201
↓ 2 callersFunctionconv2d_layer
(opts, inp, out_dim, scope, filter_size, d_h=2, d_w=2, padding='SAME', l2_norm=False, reuse=
model_decon_uBernoulli/utils.py:88
↓ 2 callersFunctionconv2d_layer
(opts, inp, out_dim, scope, filter_size, d_h=2, d_w=2, padding='SAME', l2_norm=False, reuse=
ac_decon/utils.py:88
↓ 2 callersFunctionconv2d_layer
(opts, inp, out_dim, scope, filter_size, d_h=2, d_w=2, padding='SAME', l2_norm=False, reuse=
model_decon_uGaussian/utils.py:88
↓ 2 callersFunctiondeconv2d_layer
(opts, inp, out_shape, scope, filter_size, d_h=2, d_w=2, padding='SAME', reuse= tf.AUTO_REUSE)
model_decon_uBernoulli/utils.py:121
↓ 2 callersFunctiondeconv2d_layer
(opts, inp, out_shape, scope, filter_size, d_h=2, d_w=2, padding='SAME', reuse= tf.AUTO_REUSE)
ac_decon/utils.py:121
↓ 2 callersFunctiondeconv2d_layer
(opts, inp, out_shape, scope, filter_size, d_h=2, d_w=2, padding='SAME', reuse= tf.AUTO_REUSE)
model_decon_uGaussian/utils.py:121
↓ 2 callersFunctiongaussianKL
(mu_p, cov_p, mu_q, cov_q, mask=None)
model_decon_uGaussian/utils.py:250
↓ 2 callersMethodp_a_g_z_u
(self, z, u)
model_decon_uBernoulli/model_decon.py:80
↓ 2 callersMethodp_a_g_z_u
(self, z, u)
ac_decon/model_decon.py:78
↓ 2 callersMethodp_a_g_z_u
(self, z, u)
model_decon_uGaussian/model_decon.py:78
↓ 2 callersMethodp_z_g_z_a
(self, z, a)
model_decon_uBernoulli/model_decon.py:125
↓ 2 callersMethodp_z_g_z_a
(self, z, a)
model_decon_uGaussian/model_decon.py:123
↓ 2 callersMethodq_a_g_x
(self, x)
model_decon_uBernoulli/model_decon.py:458
↓ 2 callersMethodq_a_g_x
(self, x)
ac_decon/model_decon.py:462
↓ 2 callersMethodq_a_g_x
(self, x)
model_decon_uGaussian/model_decon.py:458
↓ 2 callersMethodq_r_g_x_a
(self, x, a)
model_decon_uBernoulli/model_decon.py:473
↓ 2 callersMethodq_r_g_x_a
(self, x, a)
ac_decon/model_decon.py:477
↓ 2 callersMethodq_r_g_x_a
(self, x, a)
model_decon_uGaussian/model_decon.py:473
↓ 1 callersFunctionac_fully_connected_layer
(opts, inp, out_dim, scope, reuse=tf.AUTO_REUSE, trainable=True)
model_decon_uBernoulli/utils.py:51
↓ 1 callersFunctionac_fully_connected_layer
(opts, inp, out_dim, scope, reuse=tf.AUTO_REUSE, trainable=True)
ac_decon/utils.py:51
↓ 1 callersFunctionac_fully_connected_layer
(opts, inp, out_dim, scope, reuse=tf.AUTO_REUSE, trainable=True)
model_decon_uGaussian/utils.py:51
↓ 1 callersMethodadd_to_memory
(self, experience)
ac_decon/decon_ac_train.py:221
↓ 1 callersFunctionbernoulliKL
(u_p, u_q)
model_decon_uBernoulli/utils.py:267
↓ 1 callersFunctionbernoulliKL
(u_p, u_q)
ac_decon/utils.py:260
↓ 1 callersMethodchoose_action
(self, z, is_training)
ac_decon/decon_ac_test.py:215
↓ 1 callersMethodchoose_action
(self, z, is_training)
ac_decon/decon_ac_train.py:217
↓ 1 callersMethodclear_u
(self)
model_decon_uBernoulli/model_decon.py:563
↓ 1 callersMethodclear_u
(self)
ac_decon/model_decon.py:579
↓ 1 callersMethodclear_u
(self)
model_decon_uGaussian/model_decon.py:560
↓ 1 callersMethodcompute_r_g_cu
(self)
ac_decon/decon_ac_test.py:174
↓ 1 callersMethodcompute_r_g_cu
(self)
ac_decon/decon_ac_train.py:176
↓ 1 callersMethodcompute_u_init
(self, x, a, r)
ac_decon/decon_ac_test.py:170
↓ 1 callersMethodcompute_u_init
(self, x, a, r)
ac_decon/decon_ac_train.py:172
↓ 1 callersMethodcompute_z_init
(self, x, a, r)
ac_decon/decon_ac_test.py:166
↓ 1 callersMethodcompute_z_init
(self, x, a, r)
ac_decon/decon_ac_train.py:168
↓ 1 callersMethodcreate_env
(self)
ac_decon/decon_ac_test.py:160
↓ 1 callersMethodcreate_env
(self)
ac_decon/decon_ac_train.py:161
↓ 1 callersFunctiondecoder
(opts, inp, in_shape, out_shape, scope, in_activation=tf.nn.softplus, reuse=tf.AUTO_REUSE)
model_decon_uBernoulli/utils.py:217
↓ 1 callersFunctiondecoder
(opts, inp, in_shape, out_shape, scope, in_activation=tf.nn.softplus, reuse=tf.AUTO_REUSE)
ac_decon/utils.py:217
↓ 1 callersFunctiondecoder
(opts, inp, in_shape, out_shape, scope, in_activation=tf.nn.softplus, reuse=tf.AUTO_REUSE)
model_decon_uGaussian/utils.py:217
↓ 1 callersFunctiongaussianKL
(mu_p, cov_p, mu_q, cov_q, mask=None)
model_decon_uBernoulli/utils.py:250
↓ 1 callersFunctiongaussianKL
(mu_p, cov_p, mu_q, cov_q, mask=None)
ac_decon/utils.py:250
↓ 1 callersMethodgen_xar_seq_g_z
(self, z_0)
model_decon_uGaussian/model_decon.py:586
↓ 1 callersMethodgen_z_g_x
(self, x)
model_decon_uGaussian/model_decon.py:620
↓ 1 callersMethodload_data
(self, opts)
model_decon_uBernoulli/data_handler.py:28
↓ 1 callersMethodload_data
(self, opts)
ac_decon/data_handler.py:28
↓ 1 callersMethodload_data
(self, opts)
model_decon_uGaussian/data_handler.py:28
↓ 1 callersMethodload_dataset
(self, opts)
model_decon_uBernoulli/data_handler.py:35
↓ 1 callersMethodload_dataset
(self, opts)
ac_decon/data_handler.py:35
↓ 1 callersMethodload_dataset
(self, opts)
model_decon_uGaussian/data_handler.py:35
↓ 1 callersFunctionlstm_dropout
(h, dropout_prob)
model_decon_uBernoulli/utils.py:242
↓ 1 callersFunctionlstm_dropout
(h, dropout_prob)
ac_decon/utils.py:242
↓ 1 callersFunctionlstm_dropout
(h, dropout_prob)
model_decon_uGaussian/utils.py:242
↓ 1 callersFunctionmain
()
model_decon_uBernoulli/run.py:11
↓ 1 callersFunctionmain
()
ac_decon/train_policy.py:10
↓ 1 callersFunctionmain
()
ac_decon/test_policy.py:10
↓ 1 callersFunctionmain
()
model_decon_uGaussian/run.py:11
↓ 1 callersMethodneg_elbo
(self, x_seq, a_seq, r_seq, u_seq, anneal=1, mask=None)
model_decon_uBernoulli/model_decon.py:502
↓ 1 callersMethodneg_elbo
(self, x_seq, a_seq, r_seq, u_seq, anneal=1, mask=None)
ac_decon/model_decon.py:506
↓ 1 callersMethodneg_elbo
(self, x_seq, a_seq, r_seq, u_seq, anneal=1, mask=None)
model_decon_uGaussian/model_decon.py:502
↓ 1 callersMethodpolicy_test
(self, data)
ac_decon/decon_ac_test.py:229
↓ 1 callersFunctionrecons_loss
(cost, real, recons)
model_decon_uBernoulli/utils.py:296
↓ 1 callersFunctionrecons_loss
(cost, real, recons)
ac_decon/utils.py:289
↓ 1 callersFunctionrecons_loss
(cost, real, recons)
model_decon_uGaussian/utils.py:296
↓ 1 callersMethodrecons_xar_seq_g_xar_seq
(self, x_seq, a_seq, r_seq, mask)
model_decon_uBernoulli/model_decon.py:608
↓ 1 callersMethodrecons_xar_seq_g_xar_seq
(self, x_seq, a_seq, r_seq, mask)
ac_decon/model_decon.py:624
↓ 1 callersMethodrecons_xar_seq_g_xar_seq
(self, x_seq, a_seq, r_seq, mask)
model_decon_uGaussian/model_decon.py:605
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