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new efef7b7 Temporarily disable 'test_row_sparse_pull' on GPU. (#8265)
efef7b7 is described below
commit efef7b7b4e24584e059a9c0ce995f02cc262cc08
Author: Indhu Bharathi <indhubhara...@gmail.com>
AuthorDate: Sat Oct 14 19:44:32 2017 -0700
Temporarily disable 'test_row_sparse_pull' on GPU. (#8265)
* Temporarily disable 'test_row_sparse_pull' on GPU. Can be enabled back
after https://github.com/apache/incubator-mxnet/issues/8262 is resolved.
* Disable test_row_sparse_pull for GPU (not CPU)
* Fix build
---
tests/python/gpu/test_kvstore_gpu.py | 2 +
tests/python/gpu/test_operator_gpu.py | 19 +++++-----
tests/python/unittest/test_kvstore.py | 1 +
tests/python/unittest/test_optimizer.py | 67 +++++++++++++++++----------------
4 files changed, 47 insertions(+), 42 deletions(-)
diff --git a/tests/python/gpu/test_kvstore_gpu.py
b/tests/python/gpu/test_kvstore_gpu.py
index ffc0cc1..517d2e7 100644
--- a/tests/python/gpu/test_kvstore_gpu.py
+++ b/tests/python/gpu/test_kvstore_gpu.py
@@ -18,6 +18,7 @@
# pylint: skip-file
import mxnet as mx
import numpy as np
+import unittest
from mxnet.test_utils import assert_almost_equal, default_context
shape = (4, 4)
@@ -35,6 +36,7 @@ def init_kv_with_str(stype='default'):
return kv
+@unittest.skip("Test fails intermittently. Temporarily disabled until fixed.
Tracked at https://github.com/apache/incubator-mxnet/issues/8262";)
def test_row_sparse_pull():
kv = init_kv_with_str('row_sparse')
kv.init('e', mx.nd.ones(shape).tostype('row_sparse'))
diff --git a/tests/python/gpu/test_operator_gpu.py
b/tests/python/gpu/test_operator_gpu.py
index 2f2c3a8..b1f43f3 100644
--- a/tests/python/gpu/test_operator_gpu.py
+++ b/tests/python/gpu/test_operator_gpu.py
@@ -21,6 +21,7 @@ import time
import unittest
import mxnet as mx
import numpy as np
+import unittest
from mxnet.test_utils import check_consistency, set_default_context,
assert_almost_equal
from numpy.testing import assert_allclose
@@ -1358,16 +1359,16 @@ def test_rnn_layer():
def test_sequence_reverse():
check_sequence_reverse(mx.gpu(0))
+@unittest.skip("Test fails intermittently. Temporarily disabled until fixed.
Tracked at https://github.com/apache/incubator-mxnet/issues/8211";)
+def test_autograd_save_memory():
+ x = mx.nd.zeros((128, 512, 512), ctx=mx.gpu(0))
+ x.attach_grad()
-#def test_autograd_save_memory():
-# x = mx.nd.zeros((128, 512, 512), ctx=mx.gpu(0))
-# x.attach_grad()
-#
-# with mx.autograd.record():
-# for i in range(200):
-# x = x + 1
-# x.wait_to_read()
-# x.backward()
+ with mx.autograd.record():
+ for i in range(200):
+ x = x + 1
+ x.wait_to_read()
+ x.backward()
def test_gluon_ctc_consistency():
loss = mx.gluon.loss.CTCLoss()
diff --git a/tests/python/unittest/test_kvstore.py
b/tests/python/unittest/test_kvstore.py
index 37d44e0..fc9e3be 100644
--- a/tests/python/unittest/test_kvstore.py
+++ b/tests/python/unittest/test_kvstore.py
@@ -18,6 +18,7 @@
# pylint: skip-file
import mxnet as mx
import numpy as np
+import unittest
from mxnet.test_utils import rand_ndarray, assert_almost_equal,
assert_exception
from mxnet.base import py_str, MXNetError
diff --git a/tests/python/unittest/test_optimizer.py
b/tests/python/unittest/test_optimizer.py
index 62a1d14..8666b9e 100644
--- a/tests/python/unittest/test_optimizer.py
+++ b/tests/python/unittest/test_optimizer.py
@@ -18,6 +18,7 @@
import numpy as np
import mxnet as mx
import mxnet.lr_scheduler as lr_scheduler
+import unittest
from nose.tools import raises
import math
from mxnet.test_utils import *
@@ -532,39 +533,39 @@ class PyRMSProp(mx.optimizer.Optimizer):
if self.clip_weights:
mx.ndarray.clip(weight, -self.clip_weights, self.clip_weights,
out=weight)
-#def test_rms():
-# mx.random.seed(0)
-# opt1 = PyRMSProp
-# opt2 = mx.optimizer.RMSProp
-# shape = (3, 4, 5)
-# cg_options = [{}, {'clip_gradient': 0.4}, {'clip_gradient': 0.5}]
-# cw_options = [{}, {'clip_weights': 0.01}]
-# center_options = [{}, {'centered': False}, {'centered': True}]
-# rg_options = [{}, {'rescale_grad': 0.14}, {'rescale_grad': 0.8}]
-# wd_options = [{}, {'wd': 0.03}, {'wd': 0.05}, {'wd': 0.07}]
-# mp_options = [{}, {'multi_precision': False}, {'multi_precision': True}]
-# for dtype in [np.float16, np.float32]:
-# for cw_option in cw_options:
-# for cg_option in cg_options:
-# for center_option in center_options:
-# for rg_option in rg_options:
-# for wd_option in wd_options:
-# for mp_option in mp_options:
-# kwarg = {}
-# kwarg.update(cw_option)
-# kwarg.update(cg_option)
-# kwarg.update(center_option)
-# kwarg.update(rg_option)
-# kwarg.update(wd_option)
-# kwarg.update(mp_option)
-# if (dtype == np.float16 and
-# ('multi_precision' not in kwarg or
-# not kwarg['multi_precision'])):
-# continue
-# compare_optimizer(opt1(**kwarg),
opt2(**kwarg), shape, dtype)
-# if (default_context() == mx.cpu()):
-# compare_optimizer(opt1(**kwarg),
opt2(**kwarg), shape, dtype, g_stype='row_sparse')
-#
+@unittest.skip("Test fails intermittently. Temporarily disabled until fixed.
Tracked at https://github.com/apache/incubator-mxnet/issues/8230";)
+def test_rms():
+ mx.random.seed(0)
+ opt1 = PyRMSProp
+ opt2 = mx.optimizer.RMSProp
+ shape = (3, 4, 5)
+ cg_options = [{}, {'clip_gradient': 0.4}, {'clip_gradient': 0.5}]
+ cw_options = [{}, {'clip_weights': 0.01}]
+ center_options = [{}, {'centered': False}, {'centered': True}]
+ rg_options = [{}, {'rescale_grad': 0.14}, {'rescale_grad': 0.8}]
+ wd_options = [{}, {'wd': 0.03}, {'wd': 0.05}, {'wd': 0.07}]
+ mp_options = [{}, {'multi_precision': False}, {'multi_precision': True}]
+ for dtype in [np.float16, np.float32]:
+ for cw_option in cw_options:
+ for cg_option in cg_options:
+ for center_option in center_options:
+ for rg_option in rg_options:
+ for wd_option in wd_options:
+ for mp_option in mp_options:
+ kwarg = {}
+ kwarg.update(cw_option)
+ kwarg.update(cg_option)
+ kwarg.update(center_option)
+ kwarg.update(rg_option)
+ kwarg.update(wd_option)
+ kwarg.update(mp_option)
+ if (dtype == np.float16 and
+ ('multi_precision' not in kwarg or
+ not kwarg['multi_precision'])):
+ continue
+ compare_optimizer(opt1(**kwarg),
opt2(**kwarg), shape, dtype)
+ if (default_context() == mx.cpu()):
+ compare_optimizer(opt1(**kwarg),
opt2(**kwarg), shape, dtype, g_stype='row_sparse')
class PyFtrl(mx.optimizer.Optimizer):
"""The Ftrl optimizer.
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