farm-tools

Programs, library functions, tools working on top of deepset-ai's FARM

My own code for using the FARM library, opinionated, some parts may be out of date.

Contains modified modules from the FARM package to make some of the things I needed work.

License of this code is the same as for the FARM software.

Installation/Setup

See conda-create-env-sh

NOTE: make sure to either run the conda-create-env.sh code or perform the following steps as close as possible to get repeatable results!

create environment, tested with python 3.8
activate environment
Instead of directly installing FARM we need to slightly modify the installation process by changing the requirements file. This is done like this:
- from within the farm-tools root dir, clone the FARM repo: git clone https://github.com/deepset-ai/FARM.git
- copy our modified farm-requirements.txt into FARM/requirements.txt : cp farm-requirements.txt FARM/requirements.txt
- do a development install directly from the cloned repo:
- cd FARM
- pip install -r requirements.txt
- pip install -e .
- cd ..
if necessary because the wrong version of pytorch got installed for your system, uninstall pytorch installed as part of FARM and reinstall the version that you / that fits your configuration
Install the additional dependencies needed for farm-tools:
- pip install -r farm-tool-requirements.txt
Install the farm-tool package:
- pip install -e .
- if this is done the commands can be executed as e.g. farm-estimate instead of $PATH_TO_FARMTOOLS/farm_tools/farm_estimate.py
Install the jupyter kernel: python -m ipykernel install --user --name=farm-tools

Usage

All commands provide usage information with the parameter --help

Perfomance estimation: `farm-estimate`

usage: farm-estimate [-h] --runname RUNNAME --infile INFILE [--cfg CFG] [--seed SEED] [--n_gpu N_GPU] [--use_cuda USE_CUDA] [--use_amp USE_AMP]
                     [--do_lower_case DO_LOWER_CASE] [--text_column TEXT_COLUMN] [--batch_size BATCH_SIZE] [--max_seq MAX_SEQ]
                     [--deterministic DETERMINISTIC] [-d] [--label_column LABEL_COLUMN] [--dev_splt DEV_SPLT] [--grad_acc GRAD_ACC] [--lm_dir LM_DIR]
                     [--lm_name LM_NAME] [--evaluate_every EVALUATE_EVERY] [--max_epochs MAX_EPOCHS] [--dropout DROPOUT] [--lrate LRATE]
                     [--es_patience ES_PATIENCE] [--es_metric ES_METRIC] [--es_mode ES_MODE] [--es_min_evals ES_MIN_EVALS] [--es_hd ES_HD]
                     [--labels LABELS] [--dev_stratification DEV_STRATIFICATION] [--fts FTS] [--fts_cfg [FTS_CFG [FTS_CFG ...]]] [--fos FOS]
                     [--fos_cfg [FOS_CFG [FOS_CFG ...]]] [--hd_dim HD_DIM] [--hd0_cfg [HD0_CFG [HD0_CFG ...]]] [--hd1_cfg [HD1_CFG [HD1_CFG ...]]]
                     [--hd2_cfg [HD2_CFG [HD2_CFG ...]]] [--hd3_cfg [HD3_CFG [HD3_CFG ...]]] [--hd4_cfg [HD4_CFG [HD4_CFG ...]]]
                     [--losses_alpha LOSSES_ALPHA] [--eval_method EVAL_METHOD] [--xval_folds XVAL_FOLDS] [--holdout_repeats HOLDOUT_REPEATS]
                     [--holdout_train HOLDOUT_TRAIN] [--eval_stratification EVAL_STRATIFICATION]

optional arguments:
  -h, --help            show this help message and exit
  --runname RUNNAME     Experiment name. Files are stored in directory {runname}-{datetime}
  --infile INFILE       Path to input file
  --cfg CFG             Path to configuration file
  --seed SEED           Random seed (42)
  --n_gpu N_GPU         Number of GPUs, if GPU is to be used (1
  --use_cuda USE_CUDA   If GPUs should be used, if not specified, determined from setup
  --use_amp USE_AMP     Use AMP (False
  --do_lower_case DO_LOWER_CASE
                        Lower case tokens (False)
  --text_column TEXT_COLUMN
                        Name of in/out text column (text)
  --batch_size BATCH_SIZE
                        Batch size (32)
  --max_seq MAX_SEQ     Maximum sequence length (whatever the trainer used)
  --deterministic DETERMINISTIC
                        Use deterministic (slower) code (False)
  -d                    Enable debug mode
  --label_column LABEL_COLUMN
                        Name of label column (target)
  --dev_splt DEV_SPLT   Development set proportion (0.1)
  --grad_acc GRAD_ACC   Gradient accumulation steps (1)
  --lm_dir LM_DIR       Load LM from that directory instead of default
  --lm_name LM_NAME     Load LM from that known named model (will download and cache model!)
  --evaluate_every EVALUATE_EVERY
                        Evaluate every this many batches (10)
  --max_epochs MAX_EPOCHS
                        Maximum number of epochs (20)
  --dropout DROPOUT     Dropout rate (0.2)
  --lrate LRATE         Learning rate (5e-06)
  --es_patience ES_PATIENCE
                        Early stopping patience (10)
  --es_metric ES_METRIC
                        Early stopping metric (f1_micro)
  --es_mode ES_MODE     Early stopping mode (max)
  --es_min_evals ES_MIN_EVALS
                        Early stopping minimum evaluation steps (1)
  --es_hd ES_HD         Early stopping head number to use (0)
  --labels LABELS       Comma separated list of labels, if missing, assume '0' and '1'
  --dev_stratification DEV_STRATIFICATION
                        Use stratified dev set splits? (False)
  --fts FTS             FarmTasks class to use (FTSingleClassification)
  --fts_cfg [FTS_CFG [FTS_CFG ...]]
                        FarmTasks configuration settings of the form parm=value
  --fos FOS             FarmOptSched class to use (FOSDefault)
  --fos_cfg [FOS_CFG [FOS_CFG ...]]
                        Farm optimizer/scheduler configuration settings of the form parm=value
  --hd_dim HD_DIM       Dimension of the LM output, i.e. the head input (768)
  --hd0_cfg [HD0_CFG [HD0_CFG ...]]
                        Head 0 config parameters of the form parm=value
  --hd1_cfg [HD1_CFG [HD1_CFG ...]]
                        Head 1 config parameters of the form parm=value
  --hd2_cfg [HD2_CFG [HD2_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --hd3_cfg [HD3_CFG [HD3_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --hd4_cfg [HD4_CFG [HD4_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --losses_alpha LOSSES_ALPHA
                        Alpha for loss aggregation (weight of head 0, weight for head 1 is 1-alpha)
  --eval_method EVAL_METHOD
                        Evaluation method, one of xval, holdout (xval)
  --xval_folds XVAL_FOLDS
                        Number of folds for xval (10)
  --holdout_repeats HOLDOUT_REPEATS
                        Number of repetitions for holdout estimation (5)
  --holdout_train HOLDOUT_TRAIN
                        Portion used for training for holdout estimation (0.7)
  --eval_stratification EVAL_STRATIFICATION
                        Use stratified samples for the evaluation splits? (False)

Hyperparameter Search: `farm-hsearch`

usage: farm-hsearch [-h] --runname RUNNAME --infile INFILE [--cfg CFG] [--seed SEED] [--n_gpu N_GPU] [--use_cuda USE_CUDA] [--use_amp USE_AMP]
                    [--do_lower_case DO_LOWER_CASE] [--text_column TEXT_COLUMN] [--batch_size BATCH_SIZE] [--max_seq MAX_SEQ]
                    [--deterministic DETERMINISTIC] [-d] [--label_column LABEL_COLUMN] [--dev_splt DEV_SPLT] [--grad_acc GRAD_ACC] [--lm_dir LM_DIR]
                    [--lm_name LM_NAME] [--evaluate_every EVALUATE_EVERY] [--max_epochs MAX_EPOCHS] [--dropout DROPOUT] [--lrate LRATE]
                    [--es_patience ES_PATIENCE] [--es_metric ES_METRIC] [--es_mode ES_MODE] [--es_min_evals ES_MIN_EVALS] [--es_hd ES_HD]
                    [--labels LABELS] [--dev_stratification DEV_STRATIFICATION] [--fts FTS] [--fts_cfg [FTS_CFG [FTS_CFG ...]]] [--fos FOS]
                    [--fos_cfg [FOS_CFG [FOS_CFG ...]]] [--hd_dim HD_DIM] [--hd0_cfg [HD0_CFG [HD0_CFG ...]]] [--hd1_cfg [HD1_CFG [HD1_CFG ...]]]
                    [--hd2_cfg [HD2_CFG [HD2_CFG ...]]] [--hd3_cfg [HD3_CFG [HD3_CFG ...]]] [--hd4_cfg [HD4_CFG [HD4_CFG ...]]]
                    [--losses_alpha LOSSES_ALPHA] [--eval_method EVAL_METHOD] [--xval_folds XVAL_FOLDS] [--holdout_repeats HOLDOUT_REPEATS]
                    [--holdout_train HOLDOUT_TRAIN] [--eval_stratification EVAL_STRATIFICATION] --hcfg HCFG --outpref OUTPREF [--halg HALG]
                    [--halg_rand_n HALG_RAND_N] [--beamsize BEAMSIZE] [--est_var EST_VAR] [--est_cmp EST_CMP]

optional arguments:
  -h, --help            show this help message and exit
  --runname RUNNAME     Experiment name. Files are stored in directory {runname}-{datetime}
  --infile INFILE       Path to input file
  --cfg CFG             Path to configuration file
  --seed SEED           Random seed (42)
  --n_gpu N_GPU         Number of GPUs, if GPU is to be used (1
  --use_cuda USE_CUDA   If GPUs should be used, if not specified, determined from setup
  --use_amp USE_AMP     Use AMP (False
  --do_lower_case DO_LOWER_CASE
                        Lower case tokens (False)
  --text_column TEXT_COLUMN
                        Name of in/out text column (text)
  --batch_size BATCH_SIZE
                        Batch size (32)
  --max_seq MAX_SEQ     Maximum sequence length (whatever the trainer used)
  --deterministic DETERMINISTIC
                        Use deterministic (slower) code (False)
  -d                    Enable debug mode
  --label_column LABEL_COLUMN
                        Name of label column (target)
  --dev_splt DEV_SPLT   Development set proportion (0.1)
  --grad_acc GRAD_ACC   Gradient accumulation steps (1)
  --lm_dir LM_DIR       Load LM from that directory instead of default
  --lm_name LM_NAME     Load LM from that known named model (will download and cache model!)
  --evaluate_every EVALUATE_EVERY
                        Evaluate every this many batches (10)
  --max_epochs MAX_EPOCHS
                        Maximum number of epochs (20)
  --dropout DROPOUT     Dropout rate (0.2)
  --lrate LRATE         Learning rate (5e-06)
  --es_patience ES_PATIENCE
                        Early stopping patience (10)
  --es_metric ES_METRIC
                        Early stopping metric (f1_micro)
  --es_mode ES_MODE     Early stopping mode (max)
  --es_min_evals ES_MIN_EVALS
                        Early stopping minimum evaluation steps (1)
  --es_hd ES_HD         Early stopping head number to use (0)
  --labels LABELS       Comma separated list of labels, if missing, assume '0' and '1'
  --dev_stratification DEV_STRATIFICATION
                        Use stratified dev set splits? (False)
  --fts FTS             FarmTasks class to use (FTSingleClassification)
  --fts_cfg [FTS_CFG [FTS_CFG ...]]
                        FarmTasks configuration settings of the form parm=value
  --fos FOS             FarmOptSched class to use (FOSDefault)
  --fos_cfg [FOS_CFG [FOS_CFG ...]]
                        Farm optimizer/scheduler configuration settings of the form parm=value
  --hd_dim HD_DIM       Dimension of the LM output, i.e. the head input (768)
  --hd0_cfg [HD0_CFG [HD0_CFG ...]]
                        Head 0 config parameters of the form parm=value
  --hd1_cfg [HD1_CFG [HD1_CFG ...]]
                        Head 1 config parameters of the form parm=value
  --hd2_cfg [HD2_CFG [HD2_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --hd3_cfg [HD3_CFG [HD3_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --hd4_cfg [HD4_CFG [HD4_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --losses_alpha LOSSES_ALPHA
                        Alpha for loss aggregation (weight of head 0, weight for head 1 is 1-alpha)
  --eval_method EVAL_METHOD
                        Evaluation method, one of xval, holdout (xval)
  --xval_folds XVAL_FOLDS
                        Number of folds for xval (10)
  --holdout_repeats HOLDOUT_REPEATS
                        Number of repetitions for holdout estimation (5)
  --holdout_train HOLDOUT_TRAIN
                        Portion used for training for holdout estimation (0.7)
  --eval_stratification EVAL_STRATIFICATION
                        Use stratified samples for the evaluation splits? (False)
  --hcfg HCFG           TOML configuration file for the hyperparameter search (required)
  --outpref OUTPREF     Output prefix for the files written for the hsearch run
  --halg HALG           Search algorithm, one of grid, random, greedy, beam (grid)
  --halg_rand_n HALG_RAND_N
                        Number of random runs for halg=random (20)
  --beamsize BEAMSIZE   Size of beam for halg=beam (3)
  --est_var EST_VAR     Estimation variable to use for sorting/searching (head0_f1_macro_mean)
  --est_cmp EST_CMP     Comparison to use for optimizing est_var, min or max (max)

Train a model: `farm-train`

usage: farm-train [-h] --runname RUNNAME --infile INFILE [--cfg CFG] [--seed SEED] [--n_gpu N_GPU] [--use_cuda USE_CUDA] [--use_amp USE_AMP]
                  [--do_lower_case DO_LOWER_CASE] [--text_column TEXT_COLUMN] [--batch_size BATCH_SIZE] [--max_seq MAX_SEQ]
                  [--deterministic DETERMINISTIC] [-d] [--label_column LABEL_COLUMN] [--dev_splt DEV_SPLT] [--grad_acc GRAD_ACC] [--lm_dir LM_DIR]
                  [--lm_name LM_NAME] [--evaluate_every EVALUATE_EVERY] [--max_epochs MAX_EPOCHS] [--dropout DROPOUT] [--lrate LRATE]
                  [--es_patience ES_PATIENCE] [--es_metric ES_METRIC] [--es_mode ES_MODE] [--es_min_evals ES_MIN_EVALS] [--es_hd ES_HD]
                  [--labels LABELS] [--dev_stratification DEV_STRATIFICATION] [--fts FTS] [--fts_cfg [FTS_CFG [FTS_CFG ...]]] [--fos FOS]
                  [--fos_cfg [FOS_CFG [FOS_CFG ...]]] [--hd_dim HD_DIM] [--hd0_cfg [HD0_CFG [HD0_CFG ...]]] [--hd1_cfg [HD1_CFG [HD1_CFG ...]]]
                  [--hd2_cfg [HD2_CFG [HD2_CFG ...]]] [--hd3_cfg [HD3_CFG [HD3_CFG ...]]] [--hd4_cfg [HD4_CFG [HD4_CFG ...]]]
                  [--losses_alpha LOSSES_ALPHA]

optional arguments:
  -h, --help            show this help message and exit
  --runname RUNNAME     Experiment name. Files are stored in directory {runname}-{datetime}
  --infile INFILE       Path to input file
  --cfg CFG             Path to configuration file
  --seed SEED           Random seed (42)
  --n_gpu N_GPU         Number of GPUs, if GPU is to be used (1
  --use_cuda USE_CUDA   If GPUs should be used, if not specified, determined from setup
  --use_amp USE_AMP     Use AMP (False
  --do_lower_case DO_LOWER_CASE
                        Lower case tokens (False)
  --text_column TEXT_COLUMN
                        Name of in/out text column (text)
  --batch_size BATCH_SIZE
                        Batch size (32)
  --max_seq MAX_SEQ     Maximum sequence length (whatever the trainer used)
  --deterministic DETERMINISTIC
                        Use deterministic (slower) code (False)
  -d                    Enable debug mode
  --label_column LABEL_COLUMN
                        Name of label column (target)
  --dev_splt DEV_SPLT   Development set proportion (0.1)
  --grad_acc GRAD_ACC   Gradient accumulation steps (1)
  --lm_dir LM_DIR       Load LM from that directory instead of default
  --lm_name LM_NAME     Load LM from that known named model (will download and cache model!)
  --evaluate_every EVALUATE_EVERY
                        Evaluate every this many batches (10)
  --max_epochs MAX_EPOCHS
                        Maximum number of epochs (20)
  --dropout DROPOUT     Dropout rate (0.2)
  --lrate LRATE         Learning rate (5e-06)
  --es_patience ES_PATIENCE
                        Early stopping patience (10)
  --es_metric ES_METRIC
                        Early stopping metric (f1_micro)
  --es_mode ES_MODE     Early stopping mode (max)
  --es_min_evals ES_MIN_EVALS
                        Early stopping minimum evaluation steps (1)
  --es_hd ES_HD         Early stopping head number to use (0)
  --labels LABELS       Comma separated list of labels, if missing, assume '0' and '1'
  --dev_stratification DEV_STRATIFICATION
                        Use stratified dev set splits? (False)
  --fts FTS             FarmTasks class to use (FTSingleClassification)
  --fts_cfg [FTS_CFG [FTS_CFG ...]]
                        FarmTasks configuration settings of the form parm=value
  --fos FOS             FarmOptSched class to use (FOSDefault)
  --fos_cfg [FOS_CFG [FOS_CFG ...]]
                        Farm optimizer/scheduler configuration settings of the form parm=value
  --hd_dim HD_DIM       Dimension of the LM output, i.e. the head input (768)
  --hd0_cfg [HD0_CFG [HD0_CFG ...]]
                        Head 0 config parameters of the form parm=value
  --hd1_cfg [HD1_CFG [HD1_CFG ...]]
                        Head 1 config parameters of the form parm=value
  --hd2_cfg [HD2_CFG [HD2_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --hd3_cfg [HD3_CFG [HD3_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --hd4_cfg [HD4_CFG [HD4_CFG ...]]
                        Head 2 config parameters of the form parm=value
  --losses_alpha LOSSES_ALPHA
                        Alpha for loss aggregation (weight of head 0, weight for head 1 is 1-alpha)

Apply a trained model: `farm-apply`

usage: farm-apply [-h] --infile INFILE [--cfg CFG] [--seed SEED] [--n_gpu N_GPU] [--use_cuda USE_CUDA] [--use_amp USE_AMP]
                  [--do_lower_case DO_LOWER_CASE] [--text_column TEXT_COLUMN] [--batch_size BATCH_SIZE] [--max_seq MAX_SEQ]
                  [--deterministic DETERMINISTIC] [-d] --outfile OUTFILE --modeldir MODELDIR [--label_column LABEL_COLUMN]
                  [--prob_column PROB_COLUMN] [--num_processes NUM_PROCESSES]

optional arguments:
  -h, --help            show this help message and exit
  --infile INFILE       Path to input file
  --cfg CFG             Path to configuration file
  --seed SEED           Random seed (42)
  --n_gpu N_GPU         Number of GPUs, if GPU is to be used (1
  --use_cuda USE_CUDA   If GPUs should be used, if not specified, determined from setup
  --use_amp USE_AMP     Use AMP (False
  --do_lower_case DO_LOWER_CASE
                        Lower case tokens (False)
  --text_column TEXT_COLUMN
                        Name of in/out text column (text)
  --batch_size BATCH_SIZE
                        Batch size (32)
  --max_seq MAX_SEQ     Maximum sequence length (whatever the trainer used)
  --deterministic DETERMINISTIC
                        Use deterministic (slower) code (False)
  -d                    Enable debug mode
  --outfile OUTFILE     Path to output TSV file
  --modeldir MODELDIR   Path to directory where the model is stored
  --label_column LABEL_COLUMN
                        Name of added label column (prediction)
  --prob_column PROB_COLUMN
                        Name of added probability column (prob)
  --num_processes NUM_PROCESSES
                        Number of processes to use (1)

Name		Name	Last commit message	Last commit date
Latest commit History 27 Commits
farm_tools		farm_tools
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
conda-create-env.sh		conda-create-env.sh
farm-requirements.txt		farm-requirements.txt
farm-tool-requirements.txt		farm-tool-requirements.txt
farm-version.py		farm-version.py
setup.py		setup.py

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farm-tools

Installation/Setup

Usage

Perfomance estimation: `farm-estimate`

Hyperparameter Search: `farm-hsearch`

Train a model: `farm-train`

Apply a trained model: `farm-apply`

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farm-tools

Installation/Setup

Usage

Perfomance estimation: farm-estimate

Hyperparameter Search: farm-hsearch

Train a model: farm-train

Apply a trained model: farm-apply

About

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Perfomance estimation: `farm-estimate`

Hyperparameter Search: `farm-hsearch`

Train a model: `farm-train`

Apply a trained model: `farm-apply`

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