Add GridSearch API and Implementation, User defined Configs only

[faizanahemad]

Proposed Features

• Add gridsearch function.
• store results of grid-search in text results file.
• run multiple configurations passed by user.
• read configurations passed in text config file.
• display best configuration.
• display loss and acc curve for each run.
• enable Multiple runs per config for stable results.

How the API looks like?

def gridsearch_manual(run_fn,configs,results_file,runs=3,
                          plot_acc_curves=False,verbose=0):
    """
    run_fn: this function takes config as input, reads data, runs model and gives out 
    train_acc,val_acc,training_time,train_acc_list,val_acc_list
    configs: is a list of user defined configs, it is either a filename or a list of dict. In case it is file 
    it should be csv, 1st row as header names, and each row is treated as a single config, and 1 
    row is read as key-value pair.
    runs: is the number of times each config is tried, to ensure stable results
    """

    return best_config

Intended Usage This will be called from a script file or notebook, and provide best hyper-params

Limitations

• Each Config has to be defined by user. Later another function which can generate these configs will be made. Something like Scikit's GridSearchCV
• Only flat hierarchy configs are supported. So each config in configs list is a dict like param_name->value, no nested dicts.

Online References/Documentation was referred while making this API

• https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html
• http://hyperopt.github.io/hyperopt/

Branch Name (The github branch in which you are working on this).

• Use Git Branches instead of forking
• Make a separate branch for your feature and once it's reviewed we will merge it into master.

Note: Before raising a PR make sure that you have made an issue like this with tag: enhancement, ensure your code is tested and documented.