def next_frame_emily():
"""Emily's model hparams."""
hparams = next_frame_sv2p_params.next_frame_sv2p()
hparams.latent_loss_multiplier = 1e-4
hparams.learning_rate_constant = 0.002
hparams.add_hparam("z_dim", 10)
hparams.add_hparam("g_dim", 128)
hparams.add_hparam("rnn_size", 256)
hparams.add_hparam("posterior_rnn_layers", 1)
hparams.add_hparam("predictor_rnn_layers", 2)
return hparams
def next_frame_savp():
"""SAVP model hparams."""
hparams = next_frame_sv2p_params.next_frame_sv2p()
hparams.add_hparam("z_dim", 8)
hparams.add_hparam("num_discriminator_filters", 32)
hparams.add_hparam("use_vae", True)
hparams.add_hparam("use_gan", False)
hparams.add_hparam("use_spectral_norm", True)
hparams.add_hparam("gan_loss", "cross_entropy")
hparams.add_hparam("gan_loss_multiplier", 0.01)
hparams.add_hparam("gan_vae_loss_multiplier", 0.01)
hparams.add_hparam("gan_optimization", "joint")
hparams.target_modality = "video:l1raw"
hparams.input_modalities = "inputs:video:l1raw"
hparams.latent_loss_multiplier_schedule = "linear_anneal"
hparams.upsample_method = "bilinear_upsample_conv"
return hparams
def testSv2pTwoFrames(self):
self.TestOnVariousInputOutputSizes(
next_frame_sv2p_params.next_frame_sv2p(),
next_frame_sv2p.NextFrameSv2pTwoFrames, 1)
def testSv2pWithActionsAndRewards(self):
self.TestWithActionAndRewards(next_frame_sv2p_params.next_frame_sv2p(),
next_frame_sv2p.NextFrameSv2p, 1)