Python chainer.gradient_check.check_backward() Examples
The following are 30
code examples of chainer.gradient_check.check_backward().
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Example #1
| Source File: test_swish.py From chainer with MIT License | 5 votes |
|
def test_backward_cpu(self):
self.check_backward(self.x, self.gy)
Example #2
| Source File: test_link_n_step_gru.py From chainer with MIT License | 5 votes |
|
def test_backward_cpu(self):
self.check_backward(self.h, self.xs, self.gh, self.gys)
Example #3
| Source File: test_link_tree_lstm.py From chainer with MIT License | 5 votes |
|
def test_full_backward_cpu(self):
self.check_backward(self.gc, self.gh, *self.inputs)
Example #4
| Source File: test_link_n_step_gru.py From chainer with MIT License | 5 votes |
|
def test_backward_cpu(self):
self.check_backward(
self.h, self.xs, self.gh, self.gys)
Example #5
| Source File: test_link_n_step_gru.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.rnn.to_gpu()
with chainer.using_config('use_cudnn', 'auto'):
self.check_backward(
cuda.to_gpu(self.h),
[cuda.to_gpu(x) for x in self.xs],
cuda.to_gpu(self.gh),
[cuda.to_gpu(gy) for gy in self.gys])
Example #6
| Source File: test_link_n_step_gru.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.rnn.to_gpu()
with chainer.using_config('use_cudnn', 'auto'):
self.check_backward(
cuda.to_gpu(self.h),
[cuda.to_gpu(x) for x in self.xs],
cuda.to_gpu(self.gh),
[cuda.to_gpu(gy) for gy in self.gys])
Example #7
| Source File: test_link_tree_lstm.py From chainer with MIT License | 5 votes |
|
def test_no_gh_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
self.check_backward(cuda.to_gpu(self.gc), None,
*[cuda.to_gpu(v) for v in self.inputs])
Example #8
| Source File: test_link_tree_lstm.py From chainer with MIT License | 5 votes |
|
def test_no_gc_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
self.check_backward(None, cuda.to_gpu(self.gh),
*[cuda.to_gpu(v) for v in self.inputs])
Example #9
| Source File: test_link_tree_lstm.py From chainer with MIT License | 5 votes |
|
def test_no_gh_backward_cpu(self):
self.check_backward(self.gc, None, *self.inputs)
Example #10
| Source File: test_link_tree_lstm.py From chainer with MIT License | 5 votes |
|
def test_no_gc_backward_cpu(self):
self.check_backward(None, self.gh, *self.inputs)
Example #11
| Source File: test_link_n_step_gru.py From chainer with MIT License | 5 votes |
|
def check_backward(
self, h_data, xs_data, gh_data, gys_data):
def fun(*args):
if self.hidden_none:
h = None
xs = args
else:
h, = args[:1]
xs = args[1:]
hy, ys = self.rnn(h, xs)
return tuple([hy, ] + list(ys))
params = []
for layer in self.rnn:
for p in layer.params():
params.append(p)
if self.hidden_none:
in_data = xs_data
else:
in_data = [h_data] + xs_data
gradient_check.check_backward(
fun, tuple(in_data),
tuple([gh_data] + gys_data),
tuple(params), eps=1e-2, rtol=1e-3, atol=1e-3)
Example #12
| Source File: test_link_n_step_lstm.py From chainer with MIT License | 5 votes |
|
def check_backward(
self, h_data, c_data, xs_data, gh_data, gc_data, gys_data):
def fun(*args):
if self.hidden_none:
h = c = None
xs = args
else:
h, c = args[:2]
xs = args[2:]
hy, cy, ys = self.rnn(h, c, xs)
return tuple([hy, cy] + list(ys))
params = []
for layer in self.rnn:
for p in layer.params():
params.append(p)
if self.hidden_none:
in_data = xs_data
else:
in_data = [h_data, c_data] + xs_data
gradient_check.check_backward(
fun, tuple(in_data),
tuple([gh_data, gc_data] + gys_data),
tuple(params), eps=1e-2, rtol=1e-3, atol=1e-3)
Example #13
| Source File: test_prelu.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy))
Example #14
| Source File: test_prelu.py From chainer with MIT License | 5 votes |
|
def check_backward(self, x_data, y_grad):
gradient_check.check_backward(
self.link, x_data, y_grad, self.link.W, atol=1e-4)
Example #15
| Source File: test_swish.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy))
Example #16
| Source File: test_link_n_step_lstm.py From chainer with MIT License | 5 votes |
|
def test_backward_cpu(self):
self.check_backward(
self.h, self.c, self.xs, self.gh, self.gc, self.gys)
Example #17
| Source File: test_swish.py From chainer with MIT License | 5 votes |
|
def check_backward(self, x_data, gy_data):
gradient_check.check_backward(
self.link, x_data, gy_data, self.link.beta, atol=1e-4)
Example #18
| Source File: test_simplified_dropconnect.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy),
cuda.to_gpu(self.mask))
Example #19
| Source File: test_simplified_dropconnect.py From chainer with MIT License | 5 votes |
|
def check_backward(self, x_data, y_grad, mask):
gradient_check.check_backward(
self.link_wrapper, (x_data, mask), y_grad,
(self.link.W, self.link.b), dtype='d',
atol=1e-4, rtol=1e-3)
Example #20
| Source File: test_simplified_dropconnect.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy),
cuda.to_gpu(self.mask))
Example #21
| Source File: test_simplified_dropconnect.py From chainer with MIT License | 5 votes |
|
def test_backward_cpu(self):
self.check_backward(self.x, self.gy, self.mask)
Example #22
| Source File: test_simplified_dropconnect.py From chainer with MIT License | 5 votes |
|
def check_backward(self, x_data, y_grad, mask):
gradient_check.check_backward(
self.link_wrapper, (x_data, mask), y_grad,
(self.link.W, self.link.b),
dtype='d', **self.check_backward_options)
Example #23
| Source File: test_maxout.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy))
Example #24
| Source File: test_maxout.py From chainer with MIT License | 5 votes |
|
def check_backward(self, x_data, y_grad):
params = [self.link.linear.W]
if self.initial_bias is not None:
params.append(self.link.linear.b)
gradient_check.check_backward(
self.link, x_data, y_grad, params, atol=1e-2)
Example #25
| Source File: test_highway.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
self.check_backward(cuda.to_gpu(self.x), cuda.to_gpu(self.gy))
Example #26
| Source File: test_highway.py From chainer with MIT License | 5 votes |
|
def test_backward_cpu(self):
self.check_backward(self.x, self.gy)
Example #27
| Source File: test_highway.py From chainer with MIT License | 5 votes |
|
def check_backward(self, x_data, y_grad):
gradient_check.check_backward(
self.link, x_data, y_grad,
(self.link.plain.W, self.link.plain.b,
self.link.transform.W, self.link.transform.b),
eps=1e-2, atol=3.2e-3, rtol=1e-2)
Example #28
| Source File: test_scale.py From chainer with MIT License | 5 votes |
|
def test_backward_gpu(self):
with testing.assert_warns(DeprecationWarning):
self.link.to_gpu()
x = cuda.to_gpu(self.x)
if self.learn_W:
W = None
else:
W = cuda.to_gpu(self.W)
gy = cuda.to_gpu(self.gy)
self.check_backward(x, W, gy)
Example #29
| Source File: test_scale.py From chainer with MIT License | 5 votes |
|
def check_backward(self, x_data, W_data, y_grad):
if W_data is None:
params = [self.link.W]
gradient_check.check_backward(
self.link, x_data, y_grad, params, atol=1e-2)
else:
gradient_check.check_backward(
self.link, (x_data, W_data), y_grad, atol=1e-2)
Example #30
| Source File: test_bilinear.py From chainer with MIT License | 5 votes |
|
def _check_backward(e1, e2, y_grad, link, bias):
params = [link.W]
if bias:
params.append(link.b)
gradient_check.check_backward(
link, (e1, e2), y_grad, params, eps=1e-2, rtol=1e-3)
