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| import time | |
| import numpy as np | |
| import sys | |
| def progbar(i, n, size=16): | |
| done = (i * size) // n | |
| bar = '' | |
| for i in range(size): | |
| bar += '█' if i <= done else '░' | |
| return bar | |
| def stream(message) : | |
| try: | |
| sys.stdout.write("\r{%s}" % message) | |
| except: | |
| #Remove non-ASCII characters from message | |
| message = ''.join(i for i in message if ord(i)<128) | |
| sys.stdout.write("\r{%s}" % message) | |
| def simple_table(item_tuples) : | |
| border_pattern = '+---------------------------------------' | |
| whitespace = ' ' | |
| headings, cells, = [], [] | |
| for item in item_tuples : | |
| heading, cell = str(item[0]), str(item[1]) | |
| pad_head = True if len(heading) < len(cell) else False | |
| pad = abs(len(heading) - len(cell)) | |
| pad = whitespace[:pad] | |
| pad_left = pad[:len(pad)//2] | |
| pad_right = pad[len(pad)//2:] | |
| if pad_head : | |
| heading = pad_left + heading + pad_right | |
| else : | |
| cell = pad_left + cell + pad_right | |
| headings += [heading] | |
| cells += [cell] | |
| border, head, body = '', '', '' | |
| for i in range(len(item_tuples)) : | |
| temp_head = f'| {headings[i]} ' | |
| temp_body = f'| {cells[i]} ' | |
| border += border_pattern[:len(temp_head)] | |
| head += temp_head | |
| body += temp_body | |
| if i == len(item_tuples) - 1 : | |
| head += '|' | |
| body += '|' | |
| border += '+' | |
| print(border) | |
| print(head) | |
| print(border) | |
| print(body) | |
| print(border) | |
| print(' ') | |
| def time_since(started) : | |
| elapsed = time.time() - started | |
| m = int(elapsed // 60) | |
| s = int(elapsed % 60) | |
| if m >= 60 : | |
| h = int(m // 60) | |
| m = m % 60 | |
| return f'{h}h {m}m {s}s' | |
| else : | |
| return f'{m}m {s}s' | |
| def save_attention(attn, path): | |
| import matplotlib.pyplot as plt | |
| fig = plt.figure(figsize=(12, 6)) | |
| plt.imshow(attn.T, interpolation='nearest', aspect='auto') | |
| fig.savefig(f'{path}.png', bbox_inches='tight') | |
| plt.close(fig) | |
| def save_spectrogram(M, path, length=None): | |
| import matplotlib.pyplot as plt | |
| M = np.flip(M, axis=0) | |
| if length : M = M[:, :length] | |
| fig = plt.figure(figsize=(12, 6)) | |
| plt.imshow(M, interpolation='nearest', aspect='auto') | |
| fig.savefig(f'{path}.png', bbox_inches='tight') | |
| plt.close(fig) | |
| def plot(array): | |
| import matplotlib.pyplot as plt | |
| fig = plt.figure(figsize=(30, 5)) | |
| ax = fig.add_subplot(111) | |
| ax.xaxis.label.set_color('grey') | |
| ax.yaxis.label.set_color('grey') | |
| ax.xaxis.label.set_fontsize(23) | |
| ax.yaxis.label.set_fontsize(23) | |
| ax.tick_params(axis='x', colors='grey', labelsize=23) | |
| ax.tick_params(axis='y', colors='grey', labelsize=23) | |
| plt.plot(array) | |
| def plot_spec(M): | |
| import matplotlib.pyplot as plt | |
| M = np.flip(M, axis=0) | |
| plt.figure(figsize=(18,4)) | |
| plt.imshow(M, interpolation='nearest', aspect='auto') | |
| plt.show() | |