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[2025-02-27 11:56:01,016] INFO: [0;35mWill use single-gpu: NVIDIA A100-SXM4-80GB[0m |
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[2025-02-27 11:56:01,016] INFO: configured dtype=torch.float32 for autocast |
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[2025-02-27 11:56:01,016] INFO: configured dtype=torch.float32 for autocast |
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[2025-02-27 11:56:01,088] INFO: model_kwargs: {'input_dim': 17, 'num_classes': 6, 'input_encoding': 'split', 'pt_mode': 'direct-elemtype-split', 'eta_mode': 'linear', 'sin_phi_mode': 'linear', 'cos_phi_mode': 'linear', 'energy_mode': 'direct-elemtype-split', 'elemtypes_nonzero': [1, 2], 'learned_representation_mode': 'last', 'conv_type': 'attention', 'num_convs': 3, 'dropout_ff': 0.0, 'dropout_conv_id_mha': 0.0, 'dropout_conv_id_ff': 0.0, 'dropout_conv_reg_mha': 0.0, 'dropout_conv_reg_ff': 0.0, 'activation': 'relu', 'head_dim': 32, 'num_heads': 32, 'attention_type': 'math', 'use_pre_layernorm': True} |
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[2025-02-27 11:56:01,088] INFO: model_kwargs: {'input_dim': 17, 'num_classes': 6, 'input_encoding': 'split', 'pt_mode': 'direct-elemtype-split', 'eta_mode': 'linear', 'sin_phi_mode': 'linear', 'cos_phi_mode': 'linear', 'energy_mode': 'direct-elemtype-split', 'elemtypes_nonzero': [1, 2], 'learned_representation_mode': 'last', 'conv_type': 'attention', 'num_convs': 3, 'dropout_ff': 0.0, 'dropout_conv_id_mha': 0.0, 'dropout_conv_id_ff': 0.0, 'dropout_conv_reg_mha': 0.0, 'dropout_conv_reg_ff': 0.0, 'activation': 'relu', 'head_dim': 32, 'num_heads': 32, 'attention_type': 'math', 'use_pre_layernorm': True} |
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[2025-02-27 11:56:01,396] INFO: layer conv_id_0 using attention_type=math |
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[2025-02-27 11:56:01,396] INFO: layer conv_id_0 using attention_type=math |
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[2025-02-27 11:56:01,513] INFO: layer conv_reg_0 using attention_type=math |
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[2025-02-27 11:56:01,513] INFO: layer conv_reg_0 using attention_type=math |
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[2025-02-27 11:56:01,617] INFO: layer conv_id_1 using attention_type=math |
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[2025-02-27 11:56:01,617] INFO: layer conv_id_1 using attention_type=math |
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[2025-02-27 11:56:01,738] INFO: layer conv_reg_1 using attention_type=math |
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[2025-02-27 11:56:01,738] INFO: layer conv_reg_1 using attention_type=math |
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[2025-02-27 11:56:01,850] INFO: layer conv_id_2 using attention_type=math |
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[2025-02-27 11:56:01,850] INFO: layer conv_id_2 using attention_type=math |
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[2025-02-27 11:56:01,962] INFO: layer conv_reg_2 using attention_type=math |
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[2025-02-27 11:56:01,962] INFO: layer conv_reg_2 using attention_type=math |
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[2025-02-27 11:56:23,228] WARNING: [0;31mThe following parameters are missing in the checkpoint file ['nn_pu.0.weight', 'nn_pu.0.bias', 'nn_pu.2.weight', 'nn_pu.2.bias', 'nn_pu.4.weight', 'nn_pu.4.bias'][0m |
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[2025-02-27 11:56:23,228] WARNING: [0;31mThe following parameters are missing in the checkpoint file ['nn_pu.0.weight', 'nn_pu.0.bias', 'nn_pu.2.weight', 'nn_pu.2.bias', 'nn_pu.4.weight', 'nn_pu.4.bias'][0m |
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[2025-02-27 11:56:23,287] WARNING: [1mOptimizer checkpoint will not be loaded[0m |
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[2025-02-27 11:56:23,287] WARNING: [1mOptimizer checkpoint will not be loaded[0m |
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[2025-02-27 11:56:23,288] INFO: [1mLoaded model weights from /pfvolcentral/experiments/scratch_4M_1/checkpoints/best_weights.pth[0m |
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[2025-02-27 11:56:23,288] INFO: [1mLoaded model weights from /pfvolcentral/experiments/scratch_4M_1/checkpoints/best_weights.pth[0m |
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[2025-02-27 11:56:23,367] INFO: MLPF( |
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|
(nn0_id): ModuleList( |
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|
(0-1): 2 x Sequential( |
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|
(0): Linear(in_features=17, out_features=1024, bias=True) |
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(1): ReLU() |
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(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
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(3): Dropout(p=0.0, inplace=False) |
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(4): Linear(in_features=1024, out_features=1024, bias=True) |
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) |
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) |
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|
(nn0_reg): ModuleList( |
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|
(0-1): 2 x Sequential( |
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|
(0): Linear(in_features=17, out_features=1024, bias=True) |
|
|
(1): ReLU() |
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|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
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(3): Dropout(p=0.0, inplace=False) |
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|
(4): Linear(in_features=1024, out_features=1024, bias=True) |
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) |
|
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) |
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|
(conv_id): ModuleList( |
|
|
(0-2): 3 x PreLnSelfAttentionLayer( |
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|
(mha): MultiheadAttention( |
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|
(out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) |
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) |
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|
(norm0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
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(norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
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|
(seq): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
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(2): Linear(in_features=1024, out_features=1024, bias=True) |
|
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(3): ReLU() |
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) |
|
|
(dropout): Dropout(p=0.0, inplace=False) |
|
|
) |
|
|
) |
|
|
(conv_reg): ModuleList( |
|
|
(0-2): 3 x PreLnSelfAttentionLayer( |
|
|
(mha): MultiheadAttention( |
|
|
(out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) |
|
|
) |
|
|
(norm0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(seq): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(3): ReLU() |
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|
) |
|
|
(dropout): Dropout(p=0.0, inplace=False) |
|
|
) |
|
|
) |
|
|
(nn_binary_particle): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=2, bias=True) |
|
|
) |
|
|
(nn_pid): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=6, bias=True) |
|
|
) |
|
|
(nn_pu): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=1, bias=True) |
|
|
) |
|
|
(nn_pt): RegressionOutput( |
|
|
(nn): ModuleList( |
|
|
(0-1): 2 x Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=1, bias=True) |
|
|
) |
|
|
) |
|
|
) |
|
|
(nn_eta): RegressionOutput( |
|
|
(nn): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=2, bias=True) |
|
|
) |
|
|
) |
|
|
(nn_sin_phi): RegressionOutput( |
|
|
(nn): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=2, bias=True) |
|
|
) |
|
|
) |
|
|
(nn_cos_phi): RegressionOutput( |
|
|
(nn): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=2, bias=True) |
|
|
) |
|
|
) |
|
|
(nn_energy): RegressionOutput( |
|
|
(nn): ModuleList( |
|
|
(0-1): 2 x Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=1, bias=True) |
|
|
) |
|
|
) |
|
|
) |
|
|
(final_norm_id): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(final_norm_reg): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
) |
|
|
[2025-02-27 11:56:23,367] INFO: MLPF( |
|
|
(nn0_id): ModuleList( |
|
|
(0-1): 2 x Sequential( |
|
|
(0): Linear(in_features=17, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
) |
|
|
) |
|
|
(nn0_reg): ModuleList( |
|
|
(0-1): 2 x Sequential( |
|
|
(0): Linear(in_features=17, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
) |
|
|
) |
|
|
(conv_id): ModuleList( |
|
|
(0-2): 3 x PreLnSelfAttentionLayer( |
|
|
(mha): MultiheadAttention( |
|
|
(out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) |
|
|
) |
|
|
(norm0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(seq): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(3): ReLU() |
|
|
) |
|
|
(dropout): Dropout(p=0.0, inplace=False) |
|
|
) |
|
|
) |
|
|
(conv_reg): ModuleList( |
|
|
(0-2): 3 x PreLnSelfAttentionLayer( |
|
|
(mha): MultiheadAttention( |
|
|
(out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) |
|
|
) |
|
|
(norm0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(seq): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(3): ReLU() |
|
|
) |
|
|
(dropout): Dropout(p=0.0, inplace=False) |
|
|
) |
|
|
) |
|
|
(nn_binary_particle): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=2, bias=True) |
|
|
) |
|
|
(nn_pid): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=6, bias=True) |
|
|
) |
|
|
(nn_pu): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=1, bias=True) |
|
|
) |
|
|
(nn_pt): RegressionOutput( |
|
|
(nn): ModuleList( |
|
|
(0-1): 2 x Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=1, bias=True) |
|
|
) |
|
|
) |
|
|
) |
|
|
(nn_eta): RegressionOutput( |
|
|
(nn): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=2, bias=True) |
|
|
) |
|
|
) |
|
|
(nn_sin_phi): RegressionOutput( |
|
|
(nn): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=2, bias=True) |
|
|
) |
|
|
) |
|
|
(nn_cos_phi): RegressionOutput( |
|
|
(nn): Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=2, bias=True) |
|
|
) |
|
|
) |
|
|
(nn_energy): RegressionOutput( |
|
|
(nn): ModuleList( |
|
|
(0-1): 2 x Sequential( |
|
|
(0): Linear(in_features=1024, out_features=1024, bias=True) |
|
|
(1): ReLU() |
|
|
(2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(3): Dropout(p=0.0, inplace=False) |
|
|
(4): Linear(in_features=1024, out_features=1, bias=True) |
|
|
) |
|
|
) |
|
|
) |
|
|
(final_norm_id): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
(final_norm_reg): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
|
|
) |
|
|
[2025-02-27 11:56:23,369] INFO: Trainable parameters: 52630547 |
|
|
[2025-02-27 11:56:23,369] INFO: Trainable parameters: 52630547 |
|
|
[2025-02-27 11:56:23,369] INFO: Non-trainable parameters: 0 |
|
|
[2025-02-27 11:56:23,369] INFO: Non-trainable parameters: 0 |
|
|
[2025-02-27 11:56:23,369] INFO: Total parameters: 52630547 |
|
|
[2025-02-27 11:56:23,369] INFO: Total parameters: 52630547 |
|
|
[2025-02-27 11:56:23,372] INFO: Modules Trainable parameters Non-trainable parameters |
|
|
nn0_id.0.0.weight 17408 0 |
|
|
nn0_id.0.0.bias 1024 0 |
|
|
nn0_id.0.2.weight 1024 0 |
|
|
nn0_id.0.2.bias 1024 0 |
|
|
nn0_id.0.4.weight 1048576 0 |
|
|
nn0_id.0.4.bias 1024 0 |
|
|
nn0_id.1.0.weight 17408 0 |
|
|
nn0_id.1.0.bias 1024 0 |
|
|
nn0_id.1.2.weight 1024 0 |
|
|
nn0_id.1.2.bias 1024 0 |
|
|
nn0_id.1.4.weight 1048576 0 |
|
|
nn0_id.1.4.bias 1024 0 |
|
|
nn0_reg.0.0.weight 17408 0 |
|
|
nn0_reg.0.0.bias 1024 0 |
|
|
nn0_reg.0.2.weight 1024 0 |
|
|
nn0_reg.0.2.bias 1024 0 |
|
|
nn0_reg.0.4.weight 1048576 0 |
|
|
nn0_reg.0.4.bias 1024 0 |
|
|
nn0_reg.1.0.weight 17408 0 |
|
|
nn0_reg.1.0.bias 1024 0 |
|
|
nn0_reg.1.2.weight 1024 0 |
|
|
nn0_reg.1.2.bias 1024 0 |
|
|
nn0_reg.1.4.weight 1048576 0 |
|
|
nn0_reg.1.4.bias 1024 0 |
|
|
conv_id.0.mha.in_proj_weight 3145728 0 |
|
|
conv_id.0.mha.in_proj_bias 3072 0 |
|
|
conv_id.0.mha.out_proj.weight 1048576 0 |
|
|
conv_id.0.mha.out_proj.bias 1024 0 |
|
|
conv_id.0.norm0.weight 1024 0 |
|
|
conv_id.0.norm0.bias 1024 0 |
|
|
conv_id.0.norm1.weight 1024 0 |
|
|
conv_id.0.norm1.bias 1024 0 |
|
|
conv_id.0.seq.0.weight 1048576 0 |
|
|
conv_id.0.seq.0.bias 1024 0 |
|
|
conv_id.0.seq.2.weight 1048576 0 |
|
|
conv_id.0.seq.2.bias 1024 0 |
|
|
conv_id.1.mha.in_proj_weight 3145728 0 |
|
|
conv_id.1.mha.in_proj_bias 3072 0 |
|
|
conv_id.1.mha.out_proj.weight 1048576 0 |
|
|
conv_id.1.mha.out_proj.bias 1024 0 |
|
|
conv_id.1.norm0.weight 1024 0 |
|
|
conv_id.1.norm0.bias 1024 0 |
|
|
conv_id.1.norm1.weight 1024 0 |
|
|
conv_id.1.norm1.bias 1024 0 |
|
|
conv_id.1.seq.0.weight 1048576 0 |
|
|
conv_id.1.seq.0.bias 1024 0 |
|
|
conv_id.1.seq.2.weight 1048576 0 |
|
|
conv_id.1.seq.2.bias 1024 0 |
|
|
conv_id.2.mha.in_proj_weight 3145728 0 |
|
|
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[2025-02-27 11:56:23,372] INFO: split_configs=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] |
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[2025-02-27 11:56:23,372] INFO: split_configs=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] |
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[2025-02-27 11:56:23,540] INFO: [0;34mtest_dataset: cld_edm_ttbar_pf, 5000[0m |
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[2025-02-27 11:56:23,540] INFO: [0;34mtest_dataset: cld_edm_ttbar_pf, 5000[0m |
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[2025-02-27 11:56:23,575] INFO: Running predictions on cld_edm_ttbar_pf |
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[2025-02-27 11:56:23,575] INFO: Running predictions on cld_edm_ttbar_pf |
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[2025-02-27 11:56:31,214] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_0.parquet |
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[2025-02-27 11:56:31,214] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_0.parquet |
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[2025-02-27 11:56:31,987] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_1.parquet |
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[2025-02-27 11:56:31,987] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_1.parquet |
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[2025-02-27 11:56:32,598] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_2.parquet |
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[2025-02-27 11:56:32,598] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_2.parquet |
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[2025-02-27 11:56:33,205] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_3.parquet |
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[2025-02-27 11:56:33,205] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_3.parquet |
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[2025-02-27 11:56:33,892] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_4.parquet |
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[2025-02-27 11:56:33,892] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_4.parquet |
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[2025-02-27 11:56:34,473] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_5.parquet |
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[2025-02-27 11:56:34,473] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_5.parquet |
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[2025-02-27 11:56:35,143] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_6.parquet |
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[2025-02-27 11:56:35,143] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_6.parquet |
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[2025-02-27 11:56:35,799] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_7.parquet |
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[2025-02-27 11:56:35,799] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_7.parquet |
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[2025-02-27 11:56:36,496] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_8.parquet |
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[2025-02-27 11:56:36,496] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_8.parquet |
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[2025-02-27 11:56:37,164] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_9.parquet |
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[2025-02-27 11:56:37,164] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_9.parquet |
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[2025-02-27 11:56:37,854] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_10.parquet |
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[2025-02-27 11:56:37,854] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_10.parquet |
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[2025-02-27 11:56:38,478] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_11.parquet |
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[2025-02-27 11:56:38,478] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_11.parquet |
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[2025-02-27 11:56:39,195] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_12.parquet |
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[2025-02-27 11:56:39,195] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_12.parquet |
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[2025-02-27 11:56:39,857] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_13.parquet |
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[2025-02-27 11:56:39,857] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_13.parquet |
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[2025-02-27 11:56:40,446] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_14.parquet |
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[2025-02-27 11:56:40,446] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_14.parquet |
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[2025-02-27 11:56:41,053] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_15.parquet |
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[2025-02-27 11:56:41,053] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_15.parquet |
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[2025-02-27 11:56:41,691] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_16.parquet |
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[2025-02-27 11:56:41,691] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_16.parquet |
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[2025-02-27 11:56:42,296] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_17.parquet |
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[2025-02-27 11:56:42,296] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_17.parquet |
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[2025-02-27 11:56:42,886] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_18.parquet |
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[2025-02-27 11:56:42,886] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_18.parquet |
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[2025-02-27 11:56:43,599] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_19.parquet |
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[2025-02-27 11:56:43,599] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_19.parquet |
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[2025-02-27 11:56:44,265] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_20.parquet |
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[2025-02-27 11:56:44,265] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_20.parquet |
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[2025-02-27 11:56:44,890] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_21.parquet |
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[2025-02-27 11:56:44,890] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_21.parquet |
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[2025-02-27 11:56:45,506] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_22.parquet |
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[2025-02-27 11:56:45,506] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_22.parquet |
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[2025-02-27 11:56:46,133] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_23.parquet |
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[2025-02-27 11:56:46,133] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_23.parquet |
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[2025-02-27 11:56:46,831] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_24.parquet |
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[2025-02-27 11:56:46,831] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_24.parquet |
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[2025-02-27 11:56:47,514] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_25.parquet |
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[2025-02-27 11:56:47,514] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_25.parquet |
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[2025-02-27 11:56:48,169] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_26.parquet |
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[2025-02-27 11:56:48,169] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_26.parquet |
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[2025-02-27 11:56:48,748] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_27.parquet |
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[2025-02-27 11:56:48,748] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_27.parquet |
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[2025-02-27 11:56:49,403] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_28.parquet |
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[2025-02-27 11:56:50,026] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_29.parquet |
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[2025-02-27 11:56:50,026] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_29.parquet |
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[2025-02-27 11:56:50,649] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_30.parquet |
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[2025-02-27 11:56:50,649] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_30.parquet |
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[2025-02-27 11:56:51,279] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_31.parquet |
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[2025-02-27 11:56:51,279] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_31.parquet |
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[2025-02-27 11:56:51,947] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_32.parquet |
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[2025-02-27 11:56:51,947] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_32.parquet |
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[2025-02-27 11:56:52,571] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_33.parquet |
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[2025-02-27 11:56:52,571] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_33.parquet |
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[2025-02-27 11:56:53,182] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_34.parquet |
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[2025-02-27 11:56:53,182] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_34.parquet |
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[2025-02-27 11:56:53,862] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_35.parquet |
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[2025-02-27 11:56:53,862] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_35.parquet |
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[2025-02-27 11:56:54,539] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_36.parquet |
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[2025-02-27 11:56:54,539] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_36.parquet |
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[2025-02-27 11:56:55,188] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_37.parquet |
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[2025-02-27 11:56:55,188] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_37.parquet |
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[2025-02-27 11:56:55,799] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_38.parquet |
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[2025-02-27 11:56:55,799] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_38.parquet |
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[2025-02-27 11:56:56,070] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_39.parquet |
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[2025-02-27 11:56:56,070] INFO: Saved predictions at /pfvolcentral/experiments/scratch_4M_1/preds_best_weights/cld_edm_ttbar_pf/pred_0_39.parquet |
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[2025-02-27 11:56:56,372] INFO: Time taken to make predictions on device 0 is: 0.54 min |
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[2025-02-27 11:56:56,372] INFO: Time taken to make predictions on device 0 is: 0.54 min |
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[2025-02-27 11:56:56,375] INFO: Plotting distributions for cld_edm_ttbar_pf |
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[2025-02-27 11:56:56,375] INFO: Plotting distributions for cld_edm_ttbar_pf |
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