def next_frame_svglp(): """SVG with learned prior model hparams.""" hparams = sv2p_params.next_frame_sv2p() hparams.video_num_input_frames = 2 hparams.video_num_target_frames = 10 hparams.learning_rate_constant = 1e-4 seq_length = hparams.video_num_input_frames + hparams.video_num_target_frames # The latent_loss_multiplier is divided by the number of frames because # the image sequence loss in t2t is averaged instead of added through # time as they do in the SVG-LP paper hparams.latent_loss_multiplier = 1e-4 / seq_length hparams.reward_prediction = False hparams.num_iterations_1st_stage = -1 hparams.num_iterations_2nd_stage = -1 hparams.optimizer_adam_beta1 = 0.9 hparams.optimizer_adam_beta2 = 0.999 hparams.optimizer_adam_epsilon = 1e-08 hparams.anneal_end = -1 hparams.clip_grad_norm = 5.0 hparams.add_hparam("learned_prior", True) hparams.add_hparam("z_dim", 64) hparams.add_hparam("g_dim", 128) hparams.add_hparam("rnn_size", 256) hparams.add_hparam("rnn_type", "lstm") hparams.add_hparam("prior_rnn_layers", 1) hparams.add_hparam("posterior_rnn_layers", 1) hparams.add_hparam("predictor_rnn_layers", 2) hparams.add_hparam("has_skips", True) hparams.add_hparam("has_batchnorm", True) return hparams
def next_frame_svglp(): """SVG with learned prior model hparams.""" hparams = sv2p_params.next_frame_sv2p() hparams.video_num_input_frames = 2 hparams.video_num_target_frames = 10 hparams.learning_rate_constant = 1e-4 seq_length = hparams.video_num_input_frames + hparams.video_num_target_frames # The latent_loss_multiplier is divided by the number of frames because # the image sequence loss in t2t is averaged instead of added through # time as they do in the SVG-LP paper hparams.latent_loss_multiplier = 1e-4 / seq_length hparams.reward_prediction = False hparams.num_iterations_1st_stage = -1 hparams.num_iterations_2nd_stage = -1 hparams.optimizer_adam_beta1 = 0.9 hparams.optimizer_adam_beta2 = 0.999 hparams.optimizer_adam_epsilon = 1e-08 hparams.anneal_end = -1 hparams.clip_grad_norm = 5.0 hparams.add_hparam("learned_prior", True) hparams.add_hparam("z_dim", 64) hparams.add_hparam("g_dim", 128) hparams.add_hparam("rnn_size", 256) hparams.add_hparam("rnn_type", "lstm") hparams.add_hparam("prior_rnn_layers", 1) hparams.add_hparam("posterior_rnn_layers", 1) hparams.add_hparam("predictor_rnn_layers", 2) hparams.add_hparam("has_skips", True) hparams.add_hparam("has_batchnorm", True) return hparams
def next_frame_savp(): """SAVP model hparams.""" hparams = 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.bottom = { "inputs": modalities.video_raw_bottom, "targets": modalities.video_raw_targets_bottom, } hparams.loss = { "targets": modalities.video_l1_raw_loss, } hparams.top = { "targets": modalities.video_raw_top, } hparams.latent_loss_multiplier_schedule = "linear" hparams.upsample_method = "bilinear_upsample_conv" hparams.internal_loss = False hparams.reward_prediction = False hparams.anneal_end = 100000 hparams.num_iterations_1st_stage = 0 hparams.num_iterations_2nd_stage = 50000 return hparams
def testSv2pWithActionsAndRewardsExternalLoss(self): hp = sv2p_params.next_frame_sv2p() hp.internal_loss = False self.TestWithActionAndRewards( hp, sv2p.NextFrameSv2p, 1, False)
def next_frame_emily(): """Emily's model hparams.""" hparams = sv2p_params.next_frame_sv2p() hparams.latent_loss_multiplier = 1e-4 hparams.learning_rate_constant = 1e-4 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 = 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" hparams.upsample_method = "bilinear_upsample_conv" return hparams
def next_frame_savp(): """SAVP model hparams.""" hparams = 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.modality = { "inputs": modalities.VideoModalityL1Raw, "targets": modalities.VideoModalityL1Raw, } hparams.latent_loss_multiplier_schedule = "linear" hparams.upsample_method = "bilinear_upsample_conv" hparams.internal_loss = False hparams.reward_prediction = False hparams.anneal_end = 100000 hparams.num_iterations_1st_stage = 0 hparams.num_iterations_2nd_stage = 50000 return hparams
def testSv2pTwoFrames(self): self.TestOnVariousInputOutputSizes(sv2p_params.next_frame_sv2p(), sv2p.NextFrameSv2pTwoFrames, 1, False)
def testSv2pWithActions(self): self.TestWithActions(sv2p_params.next_frame_sv2p(), sv2p.NextFrameSv2p, 1, False)
def testSv2pWithActionsAndRewards(self): self.TestWithActionAndRewards( sv2p_params.next_frame_sv2p(), sv2p.NextFrameSv2p, 1)
def testSv2pTwoFrames(self): self.TestOnVariousInputOutputSizes( sv2p_params.next_frame_sv2p(), sv2p.NextFrameSv2pTwoFrames, 1, False)
def testSv2pWithActions(self): self.TestWithActions( sv2p_params.next_frame_sv2p(), sv2p.NextFrameSv2p, 1, False)