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NNGraph input/output valid by register tensors (#6240)
* NNGraph input/output valid by register tensors * LazyJobInstrutionType skip send Push/PullCB by NNGraph io valid * Add test script * Fix bug of static vec empty * fix bug of clang Co-authored-by: oneflow-ci-bot <69100618+oneflow-ci-bot@users.noreply.github.com>
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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 os | ||
| import time | ||
| import unittest | ||
| import numpy as np | ||
|
|
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| import oneflow as flow | ||
| import oneflow.unittest | ||
|
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| def _test_graph_buffer_limit(test_case): | ||
| class StageLayerModule(flow.nn.Module): | ||
| def __init__(self): | ||
| super().__init__() | ||
| self.linear1 = flow.nn.Linear(10, 8, False) | ||
| self.linear2 = flow.nn.Linear(8, 10, False) | ||
| flow.nn.init.constant_(self.linear1.weight, 0.023) | ||
| flow.nn.init.constant_(self.linear2.weight, 1.23) | ||
|
|
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| def forward(self, x): | ||
| out0 = self.linear1(x) | ||
| out0 = out0 + 1.0 | ||
| out0 = out0 * 2.0 | ||
| out1 = self.linear2(out0) | ||
| return out1 | ||
|
|
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| P0 = flow.placement("cuda", {0: [0]}) | ||
| P1 = flow.placement("cuda", {0: [1]}) | ||
| PT = flow.placement("cuda", {0: [0, 1]}) | ||
| B = flow.sbp.broadcast | ||
|
|
||
| class PipelineModule(flow.nn.Module): | ||
| def __init__(self): | ||
| super().__init__() | ||
| self.layer_0 = StageLayerModule() | ||
| self.layer_1 = StageLayerModule() | ||
| self.layer_0.to_consistent(P0, B) | ||
| self.layer_1.to_consistent(P1, B) | ||
|
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| def forward(self, x): | ||
| # stage 0 | ||
| in0 = x.to_consistent(P0, B) | ||
| out0 = self.layer_0(in0) | ||
| # stage 1 | ||
| in1 = out0.to_consistent(P1, B) | ||
| out1 = self.layer_1(in1) | ||
| return out1 | ||
|
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| pp_m = PipelineModule() | ||
| pp_m.eval() | ||
|
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| class PipelineGraph(flow.nn.Graph): | ||
| def __init__(self): | ||
| super().__init__() | ||
| self.pp_m = pp_m | ||
|
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| def build(self, x): | ||
| return self.pp_m(x) | ||
|
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| pp_g = PipelineGraph() | ||
|
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| for i in range(500): | ||
| x = flow.randn(16, 10) | ||
| x = x.to_consistent(P0, B) | ||
| out = pp_g(x) | ||
| # print(out.to_local().mean()) | ||
|
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|
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| @unittest.skipIf(os.getenv("ONEFLOW_TEST_CPU_ONLY"), "only test cpu cases") | ||
| @flow.unittest.skip_unless_1n2d() | ||
| class TestGraphPipelineBufferLimit(oneflow.unittest.TestCase): | ||
| def test_graph_buffer_limit(test_case): | ||
| _test_graph_buffer_limit(test_case) | ||
|
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| if __name__ == "__main__": | ||
| unittest.main() |