File size: 2,806 Bytes
be903e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2021 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 {
class F_conv1d : public GraphRewriterPass
{
public:
const char* match_pattern_graph() const
{
return R"PNNXIR(7767517
16 15
pnnx.Input input_0 0 1 input
pnnx.Input input_1 0 1 weight
pnnx.Input input_2 0 1 bias
pnnx.Input input_3 0 1 stride
pnnx.Input input_4 0 1 padding
pnnx.Input input_5 0 1 dilation
pnnx.Input input_6 0 1 groups
prim::Constant op_0 0 1 transposed value=False
prim::Constant op_1 0 1 output_padding_w value=0
prim::ListConstruct op_2 1 1 output_padding_w output_padding
prim::Constant op_3 0 1 benchmark value=*
prim::Constant op_4 0 1 deterministic value=*
prim::Constant op_5 0 1 cudnn_enabled value=*
prim::Constant op_6 0 1 allow_tf32 value=*
aten::_convolution op_7 13 1 input weight bias stride padding dilation transposed output_padding groups benchmark deterministic cudnn_enabled allow_tf32 out
pnnx.Output output 1 0 out
)PNNXIR";
}
const char* type_str() const
{
return "F.conv1d";
}
};
REGISTER_GLOBAL_PNNX_GRAPH_REWRITER_PASS(F_conv1d, 10)
class F_convmode : public GraphRewriterPass
{
public:
const char* match_pattern_graph() const
{
return R"PNNXIR(7767517
9 8
pnnx.Input input_0 0 1 input
pnnx.Input input_1 0 1 weight
pnnx.Input input_2 0 1 bias
pnnx.Input input_3 0 1 stride
pnnx.Input input_4 0 1 padding
pnnx.Input input_5 0 1 dilation
pnnx.Input input_6 0 1 groups
aten::_convolution_mode op_0 7 1 input weight bias stride padding dilation groups out
pnnx.Output output 1 0 out
)PNNXIR";
}
const char* type_str() const
{
return "F.convmode";
}
};
REGISTER_GLOBAL_PNNX_GRAPH_REWRITER_PASS(F_convmode, 10)
} // namespace pnnx
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