(we_file='glove_model_50.npz', w2i_file='glove_word2idx_50.json')

()

()

(we_file, w2i_file, use_brown=True, n_files=50)

()

()

()

()

()

()

()

()

()

()

()

()

()

()

()

()

()

()

(loadfile=None, savefile=None)

()

()

()

()

()

()

()

()

()

()

()

()

()

()

()

()

(x, c, m, a, B)

()

(s)

(s)

(s)

(s)

(T, Y)

(T, Y)

(self)

(phi_hat)

(X, Y, C, mu, a, b, e, f, a0, b0, e0, f0)

(B=12, learning_rate=10e-5, epochs=200)

(B=12, learning_rate=10e-4, epochs=3000)

(B=12, learning_rate=10e-4, epochs=1000)

(B=12, learning_rate=10e-5, epochs=200)

(self, input_, target, eligibility, lr=1e-2)

(self, X, Y)

(self, x, y, e, lr=1e-4)

(self)

(self)

(grid, policy)

(grid, policy)

(grid, policy)

(env, T, params)

( env, total_t, experience_replay_buffer, model, target_model, gamma, batch_size, epsilon, e

( env, total_t, experience_replay_buffer, model, target_model, gamma, batch_size, epsilon, e

( env, total_t, experience_replay_buffer, model, target_model, gamma, batch_size, epsilon, e

(model, eps, gamma, n=5)

(env, pmodel, gamma)

(model, eps, gamma)

(model, eps, gamma, lambda_)

(env, pmodel, gamma)

(env, model, eps, gamma)

(model, eps, gamma)

(env, model, tmodel, eps, gamma, copy_period)

(env, model, tmodel, eps, gamma, copy_period)

(model, eps, gamma, lambda_)

(env, params)

(env, pmodel, vmodel, gamma)

(env, pmodel, vmodel, gamma)

(bandits, trial)

(a, b, trial, ctr)

(pca)

(X, K, index_word_map, max_iter=20, beta=1.0, show_plots=True)

(X, K, max_iter=20, beta=1.0)

(X, Y, sample=20, max_deg=20)

(self)

(p_y)

(X, W1, b1, W2, b2)

(self, X)

(self, X)

(self, X)

(self, X)

(self, X)

(self, prev_words)

(self, X)

(self, X)

(self, X)

(self, X)

(self, X)

(self, X)