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Add view weight norm where zeropad2d global test (#7886)
* fix_unfold_tensor_sbp_and_add_global_test * refine * add_var_upsample_global_test * add_view_weight_norm_where_zeropad2d_global_test * del code not in this branch * fix where infer shape and sbp bug * del CheckBroadcastable * Update test_consistent_view.py * fix where test error Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>
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| Original file line number | Diff line number | Diff line change |
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| """ | ||
| Copyright 2020 The OneFlow Authors. All rights reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. | ||
| """ | ||
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| import unittest | ||
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| from oneflow.test_utils.automated_test_util import * | ||
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| import oneflow as flow | ||
| import oneflow.unittest | ||
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| @autotest(n=1, check_graph=False) | ||
| def _test_global_view(test_case, placement, sbp): | ||
| x = random_tensor(ndim=2, dim0=8, dim1=32).to_global(placement, sbp) | ||
| y = x.view(8, 8, 2, -1) | ||
| return y | ||
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| @autotest(n=1, check_graph=False) | ||
| def _test_global_view_size(test_case, placement, sbp): | ||
| x = random_tensor(ndim=2, dim0=8, dim1=32).to_global(placement, sbp) | ||
| shape = torch.Size([8, 8, 2, -1]) | ||
| y = x.view(shape) | ||
| return y | ||
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| class TestGlobalView(flow.unittest.TestCase): | ||
| @globaltest | ||
| def test_global_view(test_case): | ||
| for placement in all_placement(): | ||
| for sbp in all_sbp(placement, max_dim=2): | ||
| _test_global_view(test_case, placement, sbp) | ||
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| @globaltest | ||
| def test_global_view_size(test_case): | ||
| for placement in all_placement(): | ||
| for sbp in all_sbp(placement, max_dim=2): | ||
| _test_global_view_size(test_case, placement, sbp) | ||
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| if __name__ == "__main__": | ||
| unittest.main() |
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python/oneflow/test/modules/test_consistent_weight_norm.py
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| """ | ||
| Copyright 2020 The OneFlow Authors. All rights reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. | ||
| """ | ||
| import unittest | ||
| from collections import OrderedDict | ||
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| from oneflow.test_utils.test_util import GenArgList | ||
| from oneflow.test_utils.automated_test_util import * | ||
| import oneflow as flow | ||
| import oneflow.unittest | ||
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| @autotest(n=1, check_graph=False) | ||
| def _test_global_weight_norm_with_random_data(test_case, placement, sbp): | ||
| dim = random(-2, 2).to(int).value() | ||
| liner_model_torch = torch.nn.Linear(8, 16).to_global(placement, sbp) | ||
| m = torch.nn.utils.weight_norm(liner_model_torch, name="weight", dim=dim) | ||
| return m.weight_g, m.weight_v | ||
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| class TestGlobalWeightNorm(flow.unittest.TestCase): | ||
| @globaltest | ||
| def test_global_weight_norm_with_random_data(test_case): | ||
| for placement in all_placement(): | ||
| for sbp in all_sbp(placement, max_dim=1): | ||
| _test_global_weight_norm_with_random_data(test_case, placement, sbp) | ||
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| if __name__ == "__main__": | ||
| unittest.main() |
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