def gradient_descent2(f, df, x):
while True:
yield x
x = min(
(partial(gradient_step, df, -alpha)(x) for alpha in [100, 10, 1, 0.7, 0.01, 0.001, 0.0001, 0.00001]),
key=safe(f),
)
def gradient_descent3(f, df, x):
return accumulate(
lambda fx, _: min(
(partial(gradient_step, df, -alpha)(fx) for alpha in [100, 10, 1, 0.7, 0.01, 0.001, 0.0001, 0.00001]),
key=safe(f),
),
repeat(x),
)
def gradient_descent3(f, df, x):
return accumulate(
lambda fx, _: min(
(partial(gradient_step, df, -alpha)(fx)
for alpha in [100, 10, 1, 0.7, 0.01, 0.001, 0.0001, 0.00001]),
key=safe(f)), repeat(x))
def gradient_descent2(f, df, x):
while True:
yield x
x = min((partial(gradient_step, df, -alpha)(x)
for alpha in [100, 10, 1, 0.7, 0.01, 0.001, 0.0001, 0.00001]),
key=safe(f))