neerajshukla1911

int doubler(int x) {
  return 2 * x;
}

neerajshukla1911

int doubler(int x) {
  return 2 * x;
}

neerajshukla1911

# Count files directorywise
-a | cut -d/ -f2 | sort | uniq -c | sort -nr

neerajshukla1911

# coding: utf-8

# In[10]:

import os
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
#from keras import backend as K
from keras.layers.core import K
K.set_learning_phase(0)

neerajshukla1911

import tensorflow as tf
import keras

# Flags for defining the tf.train.ClusterSpec
tf.app.flags.DEFINE_string("ps_hosts", "",
                           "Comma-separated list of hostname:port pairs")
tf.app.flags.DEFINE_string("worker_hosts", "",
                           "Comma-separated list of hostname:port pairs")

# Flags for defining the tf.train.Server

neerajshukla1911

import tensorflow as tf
import keras

# Flags for defining the tf.train.ClusterSpec
tf.app.flags.DEFINE_string("ps_hosts", "",
                           "Comma-separated list of hostname:port pairs")
tf.app.flags.DEFINE_string("worker_hosts", "",
                           "Comma-separated list of hostname:port pairs")

# Flags for defining the tf.train.Server

neerajshukla1911

# coding: utf-8

# In[10]:

import os
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
#from keras import backend as K
from keras.layers.core import K
K.set_learning_phase(0)

neerajshukla1911

from sklearn.metrics import confusion_matrix
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sn
from sklearn.metrics import accuracy_score
import json

predicted_csv_filepath = '/home/neeraj/keras_jobs/sleeve_length_men_final_weights_prediction.csv'
class_indices_filepath = "/home/neeraj/keras_jobs/sleeve_length_men4/inception_v3.cls"

neerajshukla1911

import os
os.environ["CUDA_VISIBLE_DEVICES"] = "5"
from keras.models import model_from_json
from keras.preprocessing.image import array_to_img, img_to_array, load_img
import numpy as np
import json
from os import path
from keras.applications.inception_v3 import preprocess_input
import csv 

neerajshukla1911

import os

os.environ["CUDA_VISIBLE_DEVICES"] = "0"
from keras import applications
from keras.preprocessing.image import ImageDataGenerator
from keras import optimizers
from keras.models import Sequential, load_model
from keras.layers import Dropout, Flatten, Dense, Input, GlobalAveragePooling2D
from keras.engine.training import Model
import tensorflow as tf