import random import string import os import pandas as pd import pickle from keras import backend as K from keras.utils.generic_utils import get_custom_objects def swish(x): return (K.sigmoid(x) * x) if __name__ == "__main__": swish_act = Activation(swish) swish_act.__name__ = "swish" get_custom_objects().update({'swish': swish_act}) X = np.genfromtxt('data/X_train.txt', delimiter=None) Y = np.genfromtxt('data/Y_train.txt', delimiter=None)[:, np.newaxis] raw_data = np.concatenate((X, Y), axis=1) trn_p = 96 dev_p = 4 regularization = 0 runs = 1 hidden_layers = 3 nodes_per_hidden = 2048 activation = ["relu", "sigmoid", "tanh", "swish"] # activation = ["swish"] df = pd.DataFrame() for r in range(runs):
import cv2 import os import numpy as np import argparse from keras.models import load_model from keras.backend import sigmoid def swish(x, beta = 1): return (x * sigmoid(beta * x)) from keras.utils.generic_utils import get_custom_objects from keras.layers import Activation swish = Activation(swish) swish.__name__ = 'swish' get_custom_objects().update({'swish': swish}) def construct_row(roof_id, probs): row = [] row.append(roof_id) for i in range(5): row.append("{:.8f}".format(probs[0][i])) return ','.join(row) + '\n' def main(): parser = argparse.ArgumentParser() parser.add_argument("--model", type=str, help="Model path") args = parser.parse_args() model_path = args.model
cur_opt_name = 'SGD' cur_model_name = "VGG16" acfObj = 'relu' pred_acfObj = 'softmax' else: if opt == 'SGD': cur_opt = lambda: SGD_fix( lr=lr, fixW=W_fix_W, fixI=W_fix_I, autoscale=sa) cur_opt_name = f"SGD_{wl}_{sa}" #cur_model_name = "VGGsmallfix" cur_model_name = "VGG16fix" acf = gen_reluFix(X_fix_W, X_fix_I) acfObj = Activation(acf, name='relufix') acfObj.__name__ = 'relufix' get_custom_objects().update({'relufix': acfObj}) pred_acf = gen_softmaxFix(X_fix_W, X_fix_I) pred_acfObj = Activation(pred_acf, name='softmaxfix') pred_acfObj.__name__ = 'softmaxfix' get_custom_objects().update({'softmaxfix': pred_acfObj}) magic( lrs=("reduce_lr_loss", reduce_lr), #lrs=("static",static_lr), opt=(cur_opt_name, cur_opt), #model_from_file=True, #model_json="VGG16_flowers___OPT_fixSGD_Wfix_16W_fix_I_2X_fix_W_16X_fix_I_2___LRS_reduce_lr_fix.json", #model_w_file="dl_weights/VGG16_flowers___OPT_fixSGD_Wfix_16W_fix_I_2X_fix_W_16X_fix_I_2___LRS_reduce_lr-epoch190-acc0.2201-loss3.1715-valacc0.1464-valloss3.4019.hdf5", model_name=cur_model_name, fc_layers=fc_layers,