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pnnx convert torch bitwise left_shift right_shift (#4349)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,41 @@ | ||
| // Tencent is pleased to support the open source community by making ncnn available. | ||
| // | ||
| // Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved. | ||
| // | ||
| // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | ||
| // in compliance with the License. You may obtain a copy of the License at | ||
| // | ||
| // https://opensource.org/licenses/BSD-3-Clause | ||
| // | ||
| // 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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| #include "pass_level2.h" | ||
|
|
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| namespace pnnx { | ||
|
|
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| class torch_bitwise_left_shift : public GraphRewriterPass | ||
| { | ||
| public: | ||
| const char* match_pattern_graph() const | ||
| { | ||
| return R"PNNXIR(7767517 | ||
| 4 3 | ||
| pnnx.Input input_0 0 1 input | ||
| pnnx.Input input_1 0 1 other | ||
| aten::bitwise_left_shift op_0 2 1 input other out | ||
| pnnx.Output output 1 0 out | ||
| )PNNXIR"; | ||
| } | ||
|
|
||
| const char* type_str() const | ||
| { | ||
| return "torch.bitwise_left_shift"; | ||
| } | ||
| }; | ||
|
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| REGISTER_GLOBAL_PNNX_GRAPH_REWRITER_PASS(torch_bitwise_left_shift, 20) | ||
|
|
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| } // namespace pnnx |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,41 @@ | ||
| // Tencent is pleased to support the open source community by making ncnn available. | ||
| // | ||
| // Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved. | ||
| // | ||
| // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | ||
| // in compliance with the License. You may obtain a copy of the License at | ||
| // | ||
| // https://opensource.org/licenses/BSD-3-Clause | ||
| // | ||
| // 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. | ||
|
|
||
| #include "pass_level2.h" | ||
|
|
||
| namespace pnnx { | ||
|
|
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| class torch_bitwise_right_shift : public GraphRewriterPass | ||
| { | ||
| public: | ||
| const char* match_pattern_graph() const | ||
| { | ||
| return R"PNNXIR(7767517 | ||
| 4 3 | ||
| pnnx.Input input_0 0 1 input | ||
| pnnx.Input input_1 0 1 other | ||
| aten::bitwise_right_shift op_0 2 1 input other out | ||
| pnnx.Output output 1 0 out | ||
| )PNNXIR"; | ||
| } | ||
|
|
||
| const char* type_str() const | ||
| { | ||
| return "torch.bitwise_right_shift"; | ||
| } | ||
| }; | ||
|
|
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| REGISTER_GLOBAL_PNNX_GRAPH_REWRITER_PASS(torch_bitwise_right_shift, 20) | ||
|
|
||
| } // namespace pnnx |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,55 @@ | ||
| # Tencent is pleased to support the open source community by making ncnn available. | ||
| # | ||
| # Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved. | ||
| # | ||
| # Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | ||
| # in compliance with the License. You may obtain a copy of the License at | ||
| # | ||
| # https://opensource.org/licenses/BSD-3-Clause | ||
| # | ||
| # 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 torch | ||
| import torch.nn as nn | ||
| import torch.nn.functional as F | ||
|
|
||
| class Model(nn.Module): | ||
| def __init__(self): | ||
| super(Model, self).__init__() | ||
|
|
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| def forward(self, x, y): | ||
| out = torch.bitwise_left_shift(x, y) | ||
| return out | ||
|
|
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| def test(): | ||
| net = Model() | ||
| net.eval() | ||
|
|
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| torch.manual_seed(0) | ||
| x = torch.randint(10, (3, 16), dtype=torch.int) | ||
| y = torch.randint(10, (3, 16), dtype=torch.int) | ||
|
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| a = net(x, y) | ||
|
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| # export torchscript | ||
| mod = torch.jit.trace(net, (x, y)) | ||
| mod.save("test_torch_bitwise_left_shift.pt") | ||
|
|
||
| # torchscript to pnnx | ||
| import os | ||
| os.system("../src/pnnx test_torch_bitwise_left_shift.pt inputshape=[3,16]i32,[3,16]i32") | ||
|
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| # pnnx inference | ||
| import test_torch_bitwise_left_shift_pnnx | ||
| b = test_torch_bitwise_left_shift_pnnx.test_inference() | ||
|
|
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| return torch.equal(a, b) | ||
|
|
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| if __name__ == "__main__": | ||
| if test(): | ||
| exit(0) | ||
| else: | ||
| exit(1) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,55 @@ | ||
| # Tencent is pleased to support the open source community by making ncnn available. | ||
| # | ||
| # Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved. | ||
| # | ||
| # Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | ||
| # in compliance with the License. You may obtain a copy of the License at | ||
| # | ||
| # https://opensource.org/licenses/BSD-3-Clause | ||
| # | ||
| # 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 torch | ||
| import torch.nn as nn | ||
| import torch.nn.functional as F | ||
|
|
||
| class Model(nn.Module): | ||
| def __init__(self): | ||
| super(Model, self).__init__() | ||
|
|
||
| def forward(self, x, y): | ||
| out = torch.bitwise_right_shift(x, y) | ||
| return out | ||
|
|
||
| def test(): | ||
| net = Model() | ||
| net.eval() | ||
|
|
||
| torch.manual_seed(0) | ||
| x = torch.randint(10, (3, 16), dtype=torch.int) | ||
| y = torch.randint(10, (3, 16), dtype=torch.int) | ||
|
|
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| a = net(x, y) | ||
|
|
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| # export torchscript | ||
| mod = torch.jit.trace(net, (x, y)) | ||
| mod.save("test_torch_bitwise_right_shift.pt") | ||
|
|
||
| # torchscript to pnnx | ||
| import os | ||
| os.system("../src/pnnx test_torch_bitwise_right_shift.pt inputshape=[3,16]i32,[3,16]i32") | ||
|
|
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| # pnnx inference | ||
| import test_torch_bitwise_right_shift_pnnx | ||
| b = test_torch_bitwise_right_shift_pnnx.test_inference() | ||
|
|
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| return torch.equal(a, b) | ||
|
|
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| if __name__ == "__main__": | ||
| if test(): | ||
| exit(0) | ||
| else: | ||
| exit(1) |