#!/usr/bin/python3
# coding: utf-8
if '__file__' in globals():
import os, sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import numpy as np
from dezero import Variable
from dezero.utils import plot_dot_graph
def goldstein(x, y):
z = (1 + (x + y + 1)**2 * (19 - 14*x + 3*x**2 - 14*y + 6*x*y + 3*y**2)) * \
(30 + (2*x - 3*y)**2 * (18 - 32*x + 12*x**2 + 48*y - 36*x*y + 27*y**2))
return z
x = Variable(np.array(1.0))
y = Variable(np.array(1.0))
z = goldstein(x, y)
z.backward()
x.name = 'x'
y.name = 'y'
z.name = 'z'
plot_dot_graph(z, verbose=False, to_file='goldstein.png')
import numpy as np
from dezero import Variable
from dezero.utils import plot_dot_graph
import dezero.functions as f
iterss = 0
if __name__ == '__main__':
x = Variable(np.array(1))
y = f.tanh(x)
x.name = 'x'
y.name = 'y'
y.backward(create_graph=True)
for iters in [0, 1, 2, 3, 4, 5, 6]:
for i in range(iters):
gx: Variable = x.grad
x.clear_grad()
gx.backward(create_graph=True)
gx: Variable = x.grad
gx.name = f'gx{iters + 1}'
plot_dot_graph(gx, verbose=False, to_file=f'tanh_diff_{iters + 1}.png')
def plot(self, *inputs, to_file='model.png'):
ys = self.__call__(*inputs)
return utils.plot_dot_graph(ys, verbose=True, to_file=to_file)
x = Variable(np.array(np.pi / 4))
y = sin(x)
y.backward()
print('--- original sin ---')
print(y.data)
print(x.grad)
def my_sin(x, threshold=0.0001):
y = 0
for i in range(100000):
c = (-1)**i / math.factorial(2 * i + 1)
t = c * x**(2 * i + 1)
y = y + t
if abs(t.data) < threshold:
break
return y
x = Variable(np.array(np.pi / 4))
y = my_sin(x) # , threshold=1e-150)
y.backward()
print('--- approximate sin ---')
print(y.data)
print(x.grad)
x.name = 'x'
y.name = 'y'
plot_dot_graph(y, verbose=False, to_file='my_sin.png')
def plot(self, *inputs, to_file='model.png'):
y = self.forward(*inputs)
return utils.plot_dot_graph(y, verbose=True, to_file=to_file)
import numpy as np
from dezero.core import Variable
import dezero.functions as F
from dezero.utils import plot_dot_graph
def network():
x = Variable(np.array(1.0), name="x")
y = F.exp(x)
y.name = "y"
y.backward(create_graph=True)
gx = x.grad
gx.name = "gx"
gx.backward(create_graph=True)
return gx
if __name__ == "__main__":
plot_dot_graph(network())
if '__file__' in globals():
import os, sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import numpy as np
import matplotlib.pyplot as plt
from dezero import Variable
from dezero.utils import plot_dot_graph
import dezero.functions as F
x = Variable(np.array(1.0))
y = F.tanh(x)
x.name = 'x'
y.name = 'y'
y.backward(create_graph=True)
iters = 6
for i in range(iters):
gx = x.grad
x.cleargrad()
gx.backward(create_graph=True)
gx = x.grad
gx.name = 'gx' + str(iters + 1)
plot_dot_graph(gx, verbose=False, to_file='tanh6.png')
def plot(self, *inputs, to_file="model.png"):
y = self.forward(*inputs)
return utils.plot_dot_graph(y, verbose=False, to_file=to_file)
if "__file__" in globals():
import os, sys
sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
import numpy as np
from dezero import Variable
from dezero.utils import plot_dot_graph
import dezero.functions as F
x = Variable(np.array(1.0))
y = F.tanh(x)
x.name = "x"
y.name = "y"
y.backward(create_graph=True)
iters = 0
for i in range(iters):
gx = x.grad
x.cleargrad()
gx.backward(create_graph=True)
# 계산 그래프 그리기
gx = x.grad
gx.name = "gx" + str(iters + 1)
plot_dot_graph(gx, verbose=False, to_file="tanh.png")
y = 0
for i in range(100000):
c = (-1)**i / math.factorial(2 * i + 1)
t = c * x**(2 * i + 1)
y = y + t
if abs(t.data) < threshold:
break
return y
x = Variable(np.array(np.pi / 4))
y = my_sin(x)
y.backward()
print(y.data)
print(x.grad)
x.name = 'x'
y.name = 'y'
plot_dot_graph(y, verbose=False, to_file='my_sin_thres_1e-4.png')
x = Variable(np.array(np.pi / 4))
y = my_sin(x, threshold=1e-150)
y.backward()
print(y.data)
print(x.grad)
x.name = 'x'
y.name = 'y'
plot_dot_graph(y, verbose=False, to_file='my_sin_thres_1e-150.png')
import numpy as np
from dezero import Variable
from dezero.utils import plot_dot_graph
import dezero.functions as F
x = Variable(np.array(1.0))
y = F.tanh(x)
x.name = 'x'
y.name = 'y'
y.backward(create_graph=True)
iters = 1
for i in range(iters):
gx = x.grad
x.cleargrad()
gx.backward(create_graph=True)
gx = x.grad
gx.name = 'gx' + str(iters + 1)
plot_dot_graph(gx, to_file='tanh.png')
'''
Need the dot binary from the graphviz package (www.graphviz.org).
'''
import numpy as np
from dezero import Variable
from dezero.utils import plot_dot_graph
def goldstein(x0, x1):
y = (1 + (x0 + x1 + 1)**2 * (19 - 14*x0 + 3*x0**2 - 14*x1 + 6*x0*x1 + 3*x1**2)) *\
(30 + (2*x0 - 3*x1)**2 * (18 - 32*x0 + 12*x0**2 + 48*x1 - 36*x0*x1 + 27*x1**2))
return y
x0 = Variable(np.array(1.0))
x1 = Variable(np.array(1.0))
y = goldstein(x0, x1)
y.backward()
x0.name = 'x0'
x1.name = 'x1'
y.name = 'y'
plot_dot_graph(y)
x = Variable(np.array(np.pi / 4))
y = sin(x)
y.backward()
print('--- original sin ---')
print(y.data)
print(x.grad)
def my_sin(x, threshold=0.0001):
y = 0
for i in range(100000):
c = (-1) ** i / math.factorial(2 * i + 1)
t = c * x ** (2 * i + 1)
y = y + t
if abs(t.data) < threshold:
break
return y
x = Variable(np.array(np.pi / 4))
y = my_sin(x) # , threshold=1e-150)
y.backward()
print('--- approximate sin ---')
print(y.data)
print(x.grad)
x.name = 'x'
y.name = 'y'
plot_dot_graph(y, to_file='my_sin.png')
if '__file__' in globals():
import os
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import numpy as np
import matplotlib.pyplot as plt
from dezero import Variable
from dezero import setup_variable
from dezero.utils import plot_dot_graph
import dezero.functions as F
setup_variable()
if __name__ == '__main__':
x = Variable(np.array(1.0))
y = F.tanh(x)
x.name = 'x'
y.name = 'y'
y.backward(create_graph=True)
iters = 8
for i in range(iters):
gx = x.grad
x.cleargrad()
gx.backward(create_graph=True)
# draw graph
gx.name = 'gx' + str(i + 1)
plot_dot_graph(gx, verbose=False, to_file='tanh{}.png'.format(str(i)))
'''
Need the dot binary from the graphviz package (www.graphviz.org).
'''
import numpy as np
from dezero import Variable
from dezero.utils import plot_dot_graph
def goldstein(x0, x1):
y = (1 + (x0 + x1 + 1)**2 * (19 - 14*x0 + 3*x0**2 - 14*x1 + 6*x0*x1 + 3*x1**2)) *\
(30 + (2*x0 - 3*x1)**2 * (18 - 32*x0 + 12*x0**2 + 48*x1 - 36*x0*x1 + 27*x1**2))
return y
x0 = Variable(np.array(1.0))
x1 = Variable(np.array(1.0))
y = goldstein(x0, x1)
y.backward()
x0.name = 'x0'
x1.name = 'x1'
y.name = 'y'
plot_dot_graph(y, verbose=False)
def __init__(self, hidden_size, out_size):
super().__init__()
self.rnn = L.RNN(hidden_size)
self.fc = L.Linear(out_size)
def reset_state(self):
self.rnn.reset_state()
def forward(self, x):
h = self.rnn(x)
y = self.fc(h)
return y
seq_data = [np.random.randn(1, 1) for _ in range(10)] # ダミーの時系列データ
xs = seq_data[0:-1]
ts = seq_data[1:] # xsより1ステップ先のデータ
model = SimpleRNN(10, 1)
loss, cnt = 0, 0
for x, t in zip(xs, ts):
y = model(x)
loss += F.mean_squared_error(y, t)
cnt += 1
if cnt == 1:
model.cleargrads()
loss.backward()
break
plot_dot_graph(loss, verbose=False, to_file='SimpleRNN.png')
if '__file__' in globals():
import os
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import numpy as np
from dezero.utils import plot_dot_graph
from dezero import Variable
import dezero.functions as F
x = Variable(np.array(np.array(1.0)))
y = F.tanh(x)
x.name = 'x'
y.name = 'y'
y.backward(create_graph=True)
iters = 5
for i in range(iters):
gx = x.grad
x.cleargrad()
gx.backward(create_graph=True)
gx = x.grad
gx.name = 'gx' + str(iters + 1)
plot_dot_graph(gx, verbose=False, to_file='../save/tanh.png')
import numpy as np
from dezero import Variable
from dezero.math_functions import sin
from dezero.utils import plot_dot_graph
if __name__ == '__main__':
x = Variable(np.array(np.pi / 4))
y = sin(x)
y.backward()
x.name = 'x'
y.name = 'y'
plot_dot_graph(y, verbose=False, to_file='sin.png')
y = sin(x, threshold=1e-150)
y.backward()
plot_dot_graph(y, verbose=False, to_file='sin_1e-150.png')