Python RandomState.randint Examples

Example #1

File: experiment.py Project: CloudHerods/maxwells-daemon

 def indexed_loss_fun(w, i_iter):
     rs = RandomState((seed, i, i_iter))
     idxs = rs.randint(N_train, size=batch_size)
     return nllfun(w, train_images[idxs], train_labels[idxs])

Example #2

File: experiment.py Project: CloudHerods/maxwells-daemon

 def indexed_loss_fun(w, i_iter):
     rs = RandomState((seed, i, i_iter))
     idxs = rs.randint(N_train, size=batch_size)
     nll = nllfun(w, train_images[idxs], train_labels[idxs]) * N_train
     nlp = neg_log_prior(w)
     return nll + nlp

Example #3

File: experiment.py Project: ml-lab/maxwells-daemon

 def indexed_loss_fun(w, i_iter):
     rs = RandomState((seed, i_iter))
     idxs = rs.randint(N_train, size=batch_size)
     nll = nllfun(w, train_images[idxs], train_labels[idxs]) * N_train
     #nlp = neg_log_prior(w)
     return nll  # + nlp

Example #4

File: experiment.py Project: ml-lab/maxwells-daemon

 def indexed_loss_fun(w, i_iter):
     rs = RandomState((seed, i, i_iter))
     idxs = rs.randint(N_train, size=batch_size)
     nll = nllfun(w, train_inputs[idxs], train_targets[idxs]) * N_train
     nlp = neg_log_prior(w)
     return nll + nlp

Example #5

File: experiment.py Project: CloudHerods/maxwells-daemon

 def indexed_loss_fun(w, i_iter):
     rs = RandomState((seed, i, i_iter))
     idxs = rs.randint(N_train, size=batch_size)
     nll = nllfun(w, train_inputs[idxs], train_targets[idxs]) * N_train
     return nll

Example #6

 def indexed_loss_fun(w, i_iter):
     rs = RandomState((seed, i, i_iter))
     idxs = rs.randint(N_train, size=batch_size)
     return nllfun(w, train_images[idxs], train_labels[idxs]) * N_train