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---
ops: [evaluate]
model: {
path: /absolute/path/to/model/architecture.py,
class: ModelArchitectureClassName,
class_args: {
arg1: val1,
arg2: val2
},
non_strand_specific: mean
}
sampler: !obj:selene_sdk.samplers.file_samplers.BedFileSampler {
filepath: /path/to/file.bed, # generated from selene_sdk training (`test_data.bed`)
reference_sequence: !obj:selene_sdk.sequences.Genome {
input_path: /path/to/genome/hg.fa
},
n_samples: n_samples_in_file, # wc -l file.bed
targets_avail: True,
sequence_length: 1000,
n_features: 2
}
evaluate_model: !obj:selene_sdk.EvaluateModel {
features: !obj:selene_sdk.utils.load_features_list {
input_path: /path/to/distinct_features.txt
},
trained_model_path: /path/to/trained_model.pth.tar,
batch_size: 64,
report_gt_feature_n_positives: 50,
use_cuda: True,
output_dir: /path/to/output_dir
}
random_seed: 1337
...
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