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,
