SYMBOL INDEX (50 symbols across 16 files)

FILE: tutorial-contents/301_regression.py
  class Net (line 26) | class Net(torch.nn.Module):
    method __init__ (line 27) | def __init__(self, n_feature, n_hidden, n_output):
    method forward (line 32) | def forward(self, x):

FILE: tutorial-contents/302_classification.py
  class Net (line 31) | class Net(torch.nn.Module):
    method __init__ (line 32) | def __init__(self, n_feature, n_hidden, n_output):
    method forward (line 37) | def forward(self, x):

FILE: tutorial-contents/303_build_nn_quickly.py
  class Net (line 13) | class Net(torch.nn.Module):
    method __init__ (line 14) | def __init__(self, n_feature, n_hidden, n_output):
    method forward (line 19) | def forward(self, x):

FILE: tutorial-contents/304_save_reload.py
  function save (line 22) | def save():
  function restore_net (line 51) | def restore_net():
  function restore_params (line 63) | def restore_params():

FILE: tutorial-contents/305_batch_train.py
  function show_batch (line 28) | def show_batch():

FILE: tutorial-contents/306_optimizer.py
  class Net (line 34) | class Net(torch.nn.Module):
    method __init__ (line 35) | def __init__(self):
    method forward (line 40) | def forward(self, x):

FILE: tutorial-contents/401_CNN.py
  class CNN (line 59) | class CNN(nn.Module):
    method __init__ (line 60) | def __init__(self):
    method forward (line 80) | def forward(self, x):
  function plot_with_labels (line 98) | def plot_with_labels(lowDWeights, labels):

FILE: tutorial-contents/402_RNN_classifier.py
  class RNN (line 53) | class RNN(nn.Module):
    method __init__ (line 54) | def __init__(self):
    method forward (line 66) | def forward(self, x):

FILE: tutorial-contents/403_RNN_regressor.py
  class RNN (line 32) | class RNN(nn.Module):
    method __init__ (line 33) | def __init__(self):
    method forward (line 44) | def forward(self, x, h_state):

FILE: tutorial-contents/404_autoencoder.py
  class AutoEncoder (line 49) | class AutoEncoder(nn.Module):
    method __init__ (line 50) | def __init__(self):
    method forward (line 73) | def forward(self, x):

FILE: tutorial-contents/405_DQN_Reinforcement_learning.py
  class Net (line 31) | class Net(nn.Module):
    method __init__ (line 32) | def __init__(self, ):
    method forward (line 39) | def forward(self, x):
  class DQN (line 46) | class DQN(object):
    method __init__ (line 47) | def __init__(self):
    method choose_action (line 56) | def choose_action(self, x):
    method store_transition (line 68) | def store_transition(self, s, a, r, s_):
    method learn (line 75) | def learn(self):

FILE: tutorial-contents/406_GAN.py
  function artist_works (line 33) | def artist_works():     # painting from the famous artist (real target)

FILE: tutorial-contents/406_conditional_GAN.py
  function artist_works_with_labels (line 33) | def artist_works_with_labels():     # painting from the famous artist (r...

FILE: tutorial-contents/501_why_torch_dynamic_graph.py
  class RNN (line 22) | class RNN(nn.Module):
    method __init__ (line 23) | def __init__(self):
    method forward (line 34) | def forward(self, x, h_state):

FILE: tutorial-contents/502_GPU.py
  class CNN (line 31) | class CNN(nn.Module):
    method __init__ (line 32) | def __init__(self):
    method forward (line 39) | def forward(self, x):

FILE: tutorial-contents/504_batch_normalization.py
  class Net (line 51) | class Net(nn.Module):
    method __init__ (line 52) | def __init__(self, batch_normalization=False):
    method _set_init (line 73) | def _set_init(self, layer):
    method forward (line 77) | def forward(self, x):
  function plot_histogram (line 99) | def plot_histogram(l_in, l_in_bn, pre_ac, pre_ac_bn):