aravindsrinivas

import numpy as np


def madd_net(net='50', image_res=224, use_s1=False, is_bot=False, use_se=False, include_fc=True):
  num_blocks = {
      '50': [3, 4, 6, 3],
      '101': [3, 4, 23, 3],
      '152': [3, 8, 36, 3],
      '128': [3, 4, 23, 12],
      '77': [3, 4, 6, 12],

aravindsrinivas

import functools
import numpy as np
import tensorflow.compat.v1 as tf
from tensorflow.python.tpu import tpu_function


BATCH_NORM_DECAY = 0.9
BATCH_NORM_EPSILON = 1e-5

aravindsrinivas

import tensorflow as tf
import numpy as np
import gym
import sys
import os
from dqn_helper import HelperClass
from fourrooms import Fourrooms
from collections import deque
from tensorflow.python.tools.inspect_checkpoint import print_tensors_in_checkpoint_file
from copy import copy

aravindsrinivas

import os
import numpy as np
from matplotlib import pyplot as plt
from time import time

from foxhound import activations
from foxhound import updates
from foxhound import inits
from foxhound.theano_utils import floatX, sharedX

aravindsrinivas

import sys
sys.path.append('..')

import os
import json
from time import time
import numpy as np
from tqdm import tqdm
from matplotlib import pyplot as plt
from sklearn.externals import joblib

aravindsrinivas

# Alec Radford, Indico, Kyle Kastner
# License: MIT
"""
VAE in a single file.
Bringing in code from IndicoDataSolutions and Alec Radford (NewMu)
"""
import theano
import theano.tensor as T
from theano.compat.python2x import OrderedDict
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams

aravindsrinivas

import theano
import theano.tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
from theano.tensor.signal.downsample import max_pool_2d
from theano.tensor.extra_ops import repeat
from theano.sandbox.cuda.dnn import dnn_conv

from time import time
import numpy as np
from matplotlib import pyplot as plt