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import matplotlib.pyplot as plt
import time, sys, math
import numpy as np
def stream(string, variables) :
sys.stdout.write(f'\r{string}' % variables)
def num_params(model) :
parameters = filter(lambda p: p.requires_grad, model.parameters())
parameters = sum([np.prod(p.size()) for p in parameters]) / 1_000_000
print('Trainable Parameters: %.3f million' % parameters)
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 plot(array) :
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) :
M = np.flip(M, axis=0)
plt.figure(figsize=(18,4))
plt.imshow(M, interpolation='nearest', aspect='auto')
plt.show()
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