From fb51634417389f7ca53c4aa6447f6e5c8b4ea75a Mon Sep 17 00:00:00 2001 From: Dominik Roth Date: Sun, 26 May 2024 00:28:33 +0200 Subject: [PATCH] somewhat working --- config.yaml | 117 ++++++++++++++++++++++++++++++++++++++-------------- 1 file changed, 85 insertions(+), 32 deletions(-) diff --git a/config.yaml b/config.yaml index 985eaea..414a9ad 100644 --- a/config.yaml +++ b/config.yaml @@ -1,5 +1,5 @@ name: DEFAULT -project: Spikey +project: Spikey_1 slurm: name: 'Spikey_{config[name]}' @@ -22,7 +22,7 @@ runner: spikey scheduler: reps_per_version: 1 - agents_per_job: 1 + agents_per_job: 100 reps_per_agent: 1 wandb: @@ -37,35 +37,6 @@ wandb: monitor_gym: False save_code: False ---- -name: Test -import: $ - -latent_projector: - type: rnn # Options: 'fc', 'rnn' - input_size: 195 # =0.01s 19531 # =1s Input size for the Latent Projector (length of snippets). - latent_size: 4 # Size of the latent representation before message passing. - #layer_shapes: [256, 32] # List of layer sizes for the latent projector (if type is 'fc'). - #activations: ['ReLU', 'ReLU'] # Activation functions for the latent projector layers (if type is 'fc'). - rnn_hidden_size: 4 # Hidden size for the RNN projector (if type is 'rnn'). - rnn_num_layers: 1 # Number of layers for the RNN projector (if type is 'rnn'). - -middle_out: - output_size: 4 # Size of the latent representation after message passing. - num_peers: 3 # Number of most correlated peers to consider. - -predictor: - layer_shapes: [4] # List of layer sizes for the predictor. - activations: ['ELU'] # Activation functions for the predictor layers. - -training: - epochs: 1024 # Number of training epochs. - batch_size: 16 # 64 # Batch size for training. - num_batches: 4 # Batches per epoch - learning_rate: 0.05 # Learning rate for the optimizer. - eval_freq: -1 # 8 # Frequency of evaluation during training (in epochs). - save_path: models # Directory to save the best model and encoder. - evaluation: full_compression: false # Perform full compression during evaluation @@ -79,4 +50,86 @@ data: cut_length: null # Optional length to cut sequences to. profiler: - enable: false \ No newline at end of file + enable: false + +training: + eval_freq: -1 # 8 # Frequency of evaluation during training (in epochs). + save_path: models # Directory to save the best model and encoder. +--- +name: FC +import: $ + +latent_projector: + type: fc # Options: 'fc', 'rnn' + input_size: 1953 # =0.1s 19531 # =1s Input size for the Latent Projector (length of snippets). + latent_size: 4 # Size of the latent representation before message passing. + layer_shapes: [32, 8] # List of layer sizes for the latent projector (if type is 'fc'). + activations: ['ReLU', 'ReLU'] # Activation functions for the latent projector layers (if type is 'fc'). + #rnn_hidden_size: 4 # Hidden size for the RNN projector (if type is 'rnn'). + #rnn_num_layers: 1 # Number of layers for the RNN projector (if type is 'rnn'). + +middle_out: + output_size: 4 # Size of the latent representation after message passing. + num_peers: 3 # Number of most correlated peers to consider. + +predictor: + layer_shapes: [3] # List of layer sizes for the predictor. + activations: ['ReLU'] # Activation functions for the predictor layers. + +training: + epochs: 1024 # Number of training epochs. + batch_size: 32 # Batch size for training. + num_batches: 1 # Batches per epoch + learning_rate: 0.01 # Learning rate for the optimizer. +--- +name: FC6 +import: $ + +latent_projector: + type: fc # Options: 'fc', 'rnn' + input_size: 195 # =0.1s 19531 # =1s Input size for the Latent Projector (length of snippets). + latent_size: 4 # Size of the latent representation before message passing. + layer_shapes: [16] # List of layer sizes for the latent projector (if type is 'fc'). + activations: ['ReLU'] # Activation functions for the latent projector layers (if type is 'fc'). + #rnn_hidden_size: 4 # Hidden size for the RNN projector (if type is 'rnn'). + #rnn_num_layers: 1 # Number of layers for the RNN projector (if type is 'rnn'). + +middle_out: + output_size: 8 # Size of the latent representation after message passing. + num_peers: 3 # Number of most correlated peers to consider. + +predictor: + layer_shapes: [3] # List of layer sizes for the predictor. + activations: ['ReLU'] # Activation functions for the predictor layers. + +training: + epochs: 1024 # Number of training epochs. + batch_size: 16 # Batch size for training. + num_batches: 1 # Batches per epoch + learning_rate: 0.01 # Learning rate for the optimizer. +--- +name: RNN +import: $ + +latent_projector: + type: rnn # Options: 'fc', 'rnn' + input_size: 1953 # =0.1s 19531 # =1s Input size for the Latent Projector (length of snippets). + latent_size: 4 # Size of the latent representation before message passing. + #layer_shapes: [32, 8] # List of layer sizes for the latent projector (if type is 'fc'). + #activations: ['ReLU', 'ReLU'] # Activation functions for the latent projector layers (if type is 'fc'). + rnn_hidden_size: 3 # Hidden size for the RNN projector (if type is 'rnn'). + rnn_num_layers: 2 # Number of layers for the RNN projector (if type is 'rnn'). + +middle_out: + output_size: 4 # Size of the latent representation after message passing. + num_peers: 3 # Number of most correlated peers to consider. + +predictor: + layer_shapes: [3] # List of layer sizes for the predictor. + activations: ['ReLU'] # Activation functions for the predictor layers. + +training: + epochs: 1024 # Number of training epochs. + batch_size: 64 # Batch size for training. + num_batches: 2 # Batches per epoch + learning_rate: 0.01 # Learning rate for the optimizer. \ No newline at end of file