Batu's group workspace
Group: JumpMLP_Observations
Name
21 visualized
State
Notes
User
Tags
Created
Runtime
Sweep
activation
activation_first_layer
add_node_id
aggregation_method
architecture
batch_size
dropout
dropout_percentage
edge_type
env_name
h_feats
hidden_dim
input_dim
k
l2_regularization
learning_rate
linear_input
linear_output
loss
max_epochs
model_type
node_id
num_layers
obs
observation
residual
scale_by_10
seed
self_loop
sweep
observation_specification.agent_pos.slice_start
observation_specification.agent_pos.slice_stop
observation_specification.goal_pos.slice_start
observation_specification.goal_pos.slice_stop
observation_specification.velocity.slice_start
observation_specification.velocity.slice_stop
node_observation_specification
observation_specification.full.slice_start
observation_specification.full.slice_stop
observation_specification.vector.slice_start
observation_specification.vector.slice_stop
goal_connection_type
id_one_hot
typeID_one_hot
Finished
batu
2m 48s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=19, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=19, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
19
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
2106
-
InputSweep
-
-
-
-
-
-
-
-
-
0
19
-
-
-
Finished
batu
2m 57s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=505, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=505, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
505
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
1720
-
InputSweep
-
-
-
-
-
-
-
0
505
-
-
-
-
-
Finished
batu
2m 50s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=6, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=6, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
6
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
1031
-
InputSweep
13
16
16
19
-
-
-
-
-
-
-
-
-
-
Finished
batu
2m 49s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=9, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=9, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
9
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
7847
-
InputSweep
13
16
16
19
9
12
-
-
-
-
-
-
-
-
Finished
batu
2m 57s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=6, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=6, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
6
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
1862
-
InputSweep
13
16
16
19
-
-
-
-
-
-
-
-
-
-
Finished
batu
2m 58s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=505, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=505, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
505
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
841
-
InputSweep
-
-
-
-
-
-
-
0
505
-
-
-
-
-
Finished
batu
2m 51s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=9, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=9, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
9
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
1089
-
InputSweep
13
16
16
19
9
12
-
-
-
-
-
-
-
-
Finished
batu
2m 55s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=19, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=19, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
19
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
2405
-
InputSweep
-
-
-
-
-
-
-
-
-
0
19
-
-
-
Finished
batu
3m 4s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=6, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=6, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
6
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
101
-
InputSweep
13
16
16
19
-
-
-
-
-
-
-
-
-
-
Finished
batu
3m 14s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=9, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=9, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
9
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
104
-
InputSweep
13
16
16
19
9
12
-
-
-
-
-
-
-
-
Finished
batu
3m 7s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=19, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=19, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
19
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
9290
-
InputSweep
-
-
-
-
-
-
-
-
-
0
19
-
-
-
Finished
batu
3m 10s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=505, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=505, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
505
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
2195
-
InputSweep
-
-
-
-
-
-
-
0
505
-
-
-
-
-
Finished
batu
3m 9s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=6, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=6, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
6
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
1188
-
InputSweep
13
16
16
19
-
-
-
-
-
-
-
-
-
-
Finished
batu
3m 10s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=19, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=19, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
19
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
2095
-
InputSweep
-
-
-
-
-
-
-
-
-
0
19
-
-
-
Finished
batu
3m 5s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=9, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=9, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
9
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
9488
-
InputSweep
13
16
16
19
9
12
-
-
-
-
-
-
-
-
Finished
batu
3m
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=505, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=505, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
505
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
2832
-
InputSweep
-
-
-
-
-
-
-
0
505
-
-
-
-
-
Finished
batu
2m 59s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=19, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=19, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
19
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
9542
-
InputSweep
-
-
-
-
-
-
-
-
-
0
19
-
-
-
Finished
batu
2m 54s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=9, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=9, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
9
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
407
-
InputSweep
13
16
16
19
9
12
-
-
-
-
-
-
-
-
Finished
batu
2m 58s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=6, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=6, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
6
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
185
-
InputSweep
13
16
16
19
-
-
-
-
-
-
-
-
-
-
Finished
batu
3m 5s
-
torch.nn.functional.relu
-
-
-
BaselineNoGraph(
(dropout): Dropout(p=0, inplace=False)
(layers): ModuleList(
(0): Linear(in_features=505, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=3, bias=True)
)
(input_layer): Linear(in_features=505, out_features=512, bias=True)
(hidden_layers): ModuleList(
(0): Linear(in_features=512, out_features=512, bias=True)
)
(output_layer): Linear(in_features=512, out_features=3, bias=True)
)
128
-
0
-
Jump
512
-
505
-
0
0.001
-
-
torch.nn.functional.mse_loss
50
-
-
3
-
pos
-
-
2510
-
InputSweep
-
-
-
-
-
-
-
0
505
-
-
-
-
-
1-20
of 21