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Merged
merged 5 commits into from
Aug 21, 2018
Merged

Enable legacy_nn unit tests. #132

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a6f983b
skipped tests on rocm
lcskrishna Aug 17, 2018
fb13d61
enabled legacy_nn tests
lcskrishna Aug 17, 2018
ac774a0
Merge branch 'master' of https://github.com/ROCmSoftwarePlatform/pyto…
lcskrishna Aug 17, 2018
2209d9f
merge from master
lcskrishna Aug 20, 2018
c304e87
skipped tests that fail on CI
lcskrishna Aug 21, 2018
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22 changes: 21 additions & 1 deletion test/common_nn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
import torch
import torch.cuda
from torch.nn.functional import _Reduction
from common import TestCase, to_gpu, freeze_rng_state, is_iterable
from common import TestCase, to_gpu, freeze_rng_state, is_iterable, TEST_WITH_ROCM
from common_cuda import TEST_CUDA
from torch.autograd.gradcheck import get_numerical_jacobian, iter_tensors
import torch.backends.cudnn
Expand Down Expand Up @@ -102,11 +102,13 @@ def get_weight(m):
constructor_args=(1,),
input_size=(10, 20),
reference_fn=lambda i, _: torch.exp(i).div(torch.exp(i).sum(1, True).expand(10, 20)),
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='Softmax2d',
input_size=(1, 3, 10, 20),
reference_fn=lambda i, _: torch.exp(i).div(torch.exp(i).sum(1, False)),
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='LogSoftmax',
Expand All @@ -120,6 +122,7 @@ def get_weight(m):
input_size=(1, 3, 10, 20),
reference_fn=lambda i, _: torch.exp(i).div_(torch.exp(i).sum(1, False)).log_(),
desc='multiparam',
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='ELU',
Expand Down Expand Up @@ -198,48 +201,56 @@ def get_weight(m):
input_size=(2, 3, 4),
desc='1d_multiparam',
reference_fn=lambda i, p: torch.clamp(i, min=0) + torch.clamp(i, max=0) * p[0][0],
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='PReLU',
input_size=(2, 3, 4, 5),
desc='2d',
reference_fn=lambda i, p: torch.clamp(i, min=0) + torch.clamp(i, max=0) * p[0][0],
#test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='PReLU',
constructor_args=(3,),
input_size=(2, 3, 4, 5),
desc='2d_multiparam',
reference_fn=lambda i, p: torch.clamp(i, min=0) + torch.clamp(i, max=0) * p[0][0],
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='PReLU',
input_size=(2, 3, 4, 5, 6),
reference_fn=lambda i, p: torch.clamp(i, min=0) + torch.clamp(i, max=0) * p[0][0],
desc='3d',
#test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='PReLU',
constructor_args=(3,),
input_size=(2, 3, 4, 5, 6),
desc='3d_multiparam',
reference_fn=lambda i, p: torch.clamp(i, min=0) + torch.clamp(i, max=0) * p[0][0],
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='Softsign',
input_size=(3, 2, 5),
reference_fn=lambda i, _: i.div(1 + torch.abs(i)),
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='Softmin',
constructor_args=(1,),
input_size=(10, 20),
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='Softmin',
constructor_args=(1,),
input_size=(2, 3, 5, 10),
desc='multidim',
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='Tanhshrink',
Expand Down Expand Up @@ -576,6 +587,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
reference_fn=lambda i, t, m: -(t * i.log() + (1 - t) * (1 - i).log()).sum() /
(i.numel() if get_reduction(m) else 1),
check_gradgrad=False,
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='BCELoss',
Expand All @@ -586,6 +598,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
(i.numel() if get_reduction(m) else 1),
desc='weights',
check_gradgrad=False,
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='CrossEntropyLoss',
Expand All @@ -606,6 +619,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
reference_fn=lambda i, t, m:
hingeembeddingloss_reference(i, t, reduction=get_reduction(m)),
check_sum_reduction=True,
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='HingeEmbeddingLoss',
Expand All @@ -616,6 +630,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
hingeembeddingloss_reference(i, t, margin=0.5, reduction=get_reduction(m)),
desc='margin',
check_sum_reduction=True,
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='MultiLabelMarginLoss',
Expand All @@ -642,6 +657,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
target_fn=lambda: torch.rand(5, 10).mul(2).floor(),
reference_fn=lambda i, t, m: -(t * i.sigmoid().log() + (1 - t) * (-i).sigmoid().log()).sum() / i.numel(),
check_gradgrad=False,
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='MultiMarginLoss',
Expand Down Expand Up @@ -720,6 +736,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
reference_fn=lambda i, t, m:
cosineembeddingloss_reference(i[0], i[1], t, reduction=get_reduction(m)),
check_sum_reduction=True,
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='CosineEmbeddingLoss',
Expand All @@ -730,6 +747,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
cosineembeddingloss_reference(i[0], i[1], t, margin=0.7, reduction=get_reduction(m)),
desc='margin',
check_sum_reduction=True,
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='MarginRankingLoss',
Expand All @@ -738,6 +756,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
reference_fn=lambda i, t, m:
marginrankingloss_reference(i[0], i[1], t, reduction=get_reduction(m)),
check_sum_reduction=True,
test_cuda = (not TEST_WITH_ROCM)
),
dict(
module_name='MarginRankingLoss',
Expand All @@ -748,6 +767,7 @@ def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0
marginrankingloss_reference(i[0], i[1], t, margin=0.5, reduction=get_reduction(m)),
desc='margin',
check_sum_reduction=True,
test_cuda = (not TEST_WITH_ROCM)
),
]

Expand Down
1 change: 0 additions & 1 deletion test/run_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,6 @@
'cuda',
'distributed',
'distributions',
'legacy_nn',
'multiprocessing',
'nccl',
'nn',
Expand Down
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