comparison simple_model_fit.py @ 17:a01fa4e8fe4f draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb

16:d0352e8b4c10

import argparse
import json
import pickle

import pandas as pd
from galaxy_ml.utils import load_model, read_columns
from scipy.io import mmread
from sklearn.pipeline import Pipeline

N_JOBS = int(__import__("os").environ.get("GALAXY_SLOTS", 1))

    """
    with open(inputs, "r") as param_handler:
        params = json.load(param_handler)

    # load model
    with open(infile_estimator, "rb") as est_handler:
        estimator = load_model(est_handler)
    estimator = clean_params(estimator, n_jobs=N_JOBS)

    X_train, y_train = _get_X_y(params, infile1, infile2)

    estimator.fit(X_train, y_train)

        if getattr(main_est, "validation_data", None):
            del main_est.validation_data
        if getattr(main_est, "data_generator_", None):
            del main_est.data_generator_

    with open(out_object, "wb") as output_handler:
        pickle.dump(estimator, output_handler, pickle.HIGHEST_PROTOCOL)


if __name__ == "__main__":
    aparser = argparse.ArgumentParser()
    aparser.add_argument("-i", "--inputs", dest="inputs", required=True)

17:a01fa4e8fe4f

import argparse
import json

import pandas as pd
from galaxy_ml.model_persist import dump_model_to_h5, load_model_from_h5
from galaxy_ml.utils import read_columns
from scipy.io import mmread
from sklearn.pipeline import Pipeline

N_JOBS = int(__import__("os").environ.get("GALAXY_SLOTS", 1))

    """
    with open(inputs, "r") as param_handler:
        params = json.load(param_handler)

    # load model
    estimator = load_model_from_h5(infile_estimator)

    estimator = clean_params(estimator)

    X_train, y_train = _get_X_y(params, infile1, infile2)

    estimator.fit(X_train, y_train)

        if getattr(main_est, "validation_data", None):
            del main_est.validation_data
        if getattr(main_est, "data_generator_", None):
            del main_est.data_generator_

    dump_model_to_h5(estimator, out_object)


if __name__ == "__main__":
    aparser = argparse.ArgumentParser()
    aparser.add_argument("-i", "--inputs", dest="inputs", required=True)