seqgra attribution¶
seqgra attribution: Obtain feature attribution/evidence for selected examples across multiple grammars, models, evaluators
usage: seqgraa [-h] [-v] -a ANALYSIS_ID -d GRAMMAR_IDS [GRAMMAR_IDS ...] -m MODEL_DEF_FILES [MODEL_DEF_FILES ...] -o
OUTPUT_DIR -i EXAMPLES_FILE -j ANNOTATIONS_FILE [-e EVALUATORS [EVALUATORS ...]] [-t TARGET]
[--eval-sis-predict-threshold EVAL_SIS_PREDICT_THRESHOLD]
[--eval-grad-importance-threshold EVAL_GRAD_IMPORTANCE_THRESHOLD] [--eval-suppress-plots] [-g GPU]
Named Arguments¶
- -v, --version
show program’s version number and exit
- -a, --analysis-id
analysis ID (used for script file name and comparator folders)
- -d, --grammar-ids
list of grammar IDs or data folders (inside output-dir/input)
- -m, --model-def-files
list of paths to the seqgra XML model definition files
- -o, --output-dir
output directory of previous seqgra calls with subdirectories input (simulated and experimental data) and models (trained models); subdirectories are created for attribution analysis
- -i, --examples-file
path to file containing examples for feature importance evaluators
- -j, --annotations-file
path to file containing annotations of examples for feature importance evaluators
- -e, --evaluators
feature importance evaluator ID or IDs: contrastive-excitation-backprop, deconv, deep-lift, excitation-backprop, feedback, grad-cam, gradient, gradient-x-input, guided-backprop, integrated-gradients, nonlinear-integrated-gradients, saliency, sis, smooth-grad
Default: frozenset({‘gradient-x-input’, ‘deconv’, ‘deep-lift’, ‘guided-backprop’, ‘saliency’, ‘gradient’, ‘integrated-gradients’})
- -t, --target
target label for which evidence/attribution should be generated, either ‘y’ for ground truth label or ‘y-hat’ for predicted label, defaults to ‘y’
Default: “y”
- --eval-sis-predict-threshold
prediction threshold for Sufficient Input Subsets; this evaluator argument is only visible to the SIS evaluator
Default: 0.5
- --eval-grad-importance-threshold
feature importance threshold for gradient-based feature importance evaluators; this parameter only affects thresholded grammar agreement plots, not the feature importance measures themselves; this evaluator argument is only visible to gradient-based feature importance evaluators (defaults to 0.01)
Default: 0.01
- --eval-suppress-plots
if this flag is set, plots are suppressed globally; this evaluator argument will be passed to all evaluators
Default: False
- -g, --gpu
ID of GPU used by TensorFlow and PyTorch (defaults to GPU ID 0); CPU is used if no GPU is available or GPU ID is set to -1
Default: 0