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dynamic custom operator support (apache#15921)
* fixed example to use absolute path * added example for custom ops, added support for custom op registration * added fcompute registration for loaded operators moved library import order to after ndarray/symbol * changed dynamic ops to be contrib * added num in/out * removed contrib op registration re-registered ops from mx.nd.op to mx.nd * added support for infer shape, updated example to call operator * fixed whitespace * fixed whitespace * fixed whitespace * added temporary support for operator multi-registration * insanity checked * update docblocks * small format fix * fix unittest with correct library * implement InferType * initial support for resource manager, temp space * fixed formatting * changed decltype to typedef * fixed whitespace * Added windows declaration types, change APIs to return MXReturnValue instead of int * added library version number, API to get, and check to validate * Changed CMakeLists to build lib_ops instead of lib_api, updated lib_api example, fixed whitespace * add prototype of subgraph op * implement FMutateInput as optional attribute * fix sanity check * replace fcompute to fcomputeEx and implement simple finferstoragetype * changed fcompute to forward * initial commit with fgradient support * enabled gradient registration * fixed whitespace * fixed example to use absolute path * added example for custom ops, added support for custom op registration * added fcompute registration for loaded operators moved library import order to after ndarray/symbol * changed dynamic ops to be contrib * added num in/out * removed contrib op registration re-registered ops from mx.nd.op to mx.nd * added support for infer shape, updated example to call operator * fixed whitespace * fixed whitespace * fixed whitespace * added temporary support for operator multi-registration * insanity checked * update docblocks * small format fix * fix unittest with correct library * implement InferType * initial support for resource manager, temp space * fixed formatting * changed decltype to typedef * fixed whitespace * Added windows declaration types, change APIs to return MXReturnValue instead of int * added library version number, API to get, and check to validate * Changed CMakeLists to build lib_ops instead of lib_api, updated lib_api example, fixed whitespace * add prototype of subgraph op * implement FMutateInput as optional attribute * fix sanity check * replace fcompute to fcomputeEx and implement simple finferstoragetype * changed fcompute to forward * initial commit with fgradient support * enabled gradient registration * fixed whitespace * prototype of createopstate and fstatefulcompute * make custom state op interface work * subgraph forward * refactor stateful forward and add op resource * wip gemm backward * stateful backward and subgraph test * implement gemm and state gemm, refactor test files * add body to pure virtual destructor * subgraph passing from python to custom lib * rm lib_api c++11 dep, rm warpctc, add rm flag * fix conflict * subgraph json parsing utility * add data size and fix unsigned warnings * use c++ struct and fix cpplint * refactor op registry * fix line length and win array of ci; condense lines * add mxnet_extension dir * fixed extension to be dll for windows * updated examples to use the same format as the example in the top-level Makefile: "lib<name>.so" * removed destructor for CustomStatefulOp * fix error in gemm test and clear up subgraph test * lib path fix * add unittest for custom op * update Makefile revolve merge * fix test and rename folder * fix makefile rename * fix cmake rename * add explicit cpu context * wkcn feedback: change mxtensor func name. use c++11 flag * add operator keyward test and refine info print * using typedef in forward * small refine of docblock * change names * add separate stateful compute and pass state_op ptr * user example using opresource alloc * added DLTensor into MXTensor * fixed whitespace * added error check when DLTensor does not support MXNet data type * changed to throw runtime exception * changed include to stdexcept * retrigger CI * empty commit * empty commit * remove merge conflict * add setdltensor for easy use and add docs * CI * re-trigger CI * ci * ci
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| Original file line number | Diff line number | Diff line change |
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| # Licensed to the Apache Software Foundation (ASF) under one | ||
| # or more contributor license agreements. See the NOTICE file | ||
| # distributed with this work for additional information | ||
| # regarding copyright ownership. The ASF licenses this file | ||
| # to you 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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| all: subgraph_lib gemm_lib | ||
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| gemm_lib: | ||
| g++ -shared -fPIC -std=c++11 gemm_lib.cc -o libgemm_lib.so -I ../../../include/mxnet | ||
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| subgraph_lib: | ||
| g++ -shared -fPIC -std=c++11 subgraph_lib.cc -o libsubgraph_lib.so -I ../../../include/mxnet | ||
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| clean: | ||
| rm -rf libsubgraph_lib.so libgemm_lib.so |
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| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one | ||
| * or more contributor license agreements. See the NOTICE file | ||
| * distributed with this work for additional information | ||
| * regarding copyright ownership. The ASF licenses this file | ||
| * to you 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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| /*! | ||
| * Copyright (c) 2019 by Contributors | ||
| * \file gemm_lib.cc | ||
| * \brief Sample 2D gemm custom operator implementation library file | ||
| */ | ||
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| #include <iostream> | ||
| #include "lib_api.h" | ||
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| // main matrix multiplication routine | ||
| void gemm(const float* A, const float* B, float* C, | ||
| const unsigned n, const unsigned k, const unsigned m) { | ||
| unsigned i, j, kk; | ||
| for (i = 0; i < n; i++) { | ||
| for (j = 0; j < m; j++) { | ||
| C[i*m+j] = 0; | ||
| for (kk = 0; kk < k; kk++) { | ||
| C[i*m+j] += A[i*k+kk] * B[kk*m+j]; | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| void transpose(const float* A, float* At, const unsigned n, const unsigned m) { | ||
| unsigned i, j; | ||
| for (i = 0; i < n; i++) { | ||
| for (j = 0; j < m; j++) { | ||
| At[i*m+j] = A[j*n+i]; | ||
| } | ||
| } | ||
| } | ||
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| /* | ||
| * Executes C = A * B | ||
| * inputs[0] = A; inputs[1] = B; outputs[0] = C | ||
| */ | ||
| MXReturnValue forward(std::map<std::string, std::string> attrs, | ||
| std::vector<MXTensor> inputs, | ||
| std::vector<MXTensor> outputs, | ||
| OpResource res) { | ||
| // simple example of using runtime data type | ||
| if (inputs[0].dtype == kFloat32) { | ||
| typedef float DType; | ||
| // extract data pointers from tensors | ||
| // if using dltensor repr, below lines can be changed to something like | ||
| // DType* A = reinterpret_cast<DType*>(inputs[0].dltensor.data); | ||
| DType* A = inputs[0].data<DType>(); | ||
| DType* B = inputs[1].data<DType>(); | ||
| DType* C = outputs[0].data<DType>(); | ||
| // set tensor shapes | ||
| unsigned n = inputs[0].shape[0]; | ||
| unsigned k = inputs[0].shape[1]; | ||
| unsigned m = inputs[1].shape[1]; | ||
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| gemm(A, B, C, n, k, m); | ||
| } | ||
| return MX_SUCCESS; | ||
| } | ||
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| /* | ||
| * Executes dA = dC * B.T; Executes dB = A.T * dC | ||
| ***** gradient inputs | ||
| * inputs[0] = dC | ||
| ***** original inputs | ||
| * inputs[1] = A; inputs[2] = B | ||
| ***** original outputs | ||
| * inputs[3] = C | ||
| ***** gradient outputs | ||
| * outputs[0] = dA; outputs[1] = dB | ||
| */ | ||
| MXReturnValue backward(std::map<std::string, std::string> attrs, | ||
| std::vector<MXTensor> inputs, | ||
| std::vector<MXTensor> outputs, | ||
| OpResource res) { | ||
| // extract data pointers from tensors | ||
| float* dC = inputs[0].data<float>(); | ||
| float* A = inputs[1].data<float>(); | ||
| float* B = inputs[2].data<float>(); | ||
| float* dA = outputs[0].data<float>(); | ||
| float* dB = outputs[1].data<float>(); | ||
| // set tensor shapes | ||
| unsigned n = inputs[1].shape[0]; | ||
| unsigned k = inputs[1].shape[1]; | ||
| unsigned m = inputs[2].shape[1]; | ||
| // allocate temporary workspace memory through resource manager | ||
| // for multiple arrays better to request a big memory pool | ||
| void *workspace = res.alloc((k*n + m*k) * sizeof(float)); | ||
| float *At = static_cast<float*>(workspace); | ||
| float *Bt = static_cast<float*>(workspace) + (k*n); | ||
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| transpose(A, At, k, n); | ||
| transpose(B, Bt, m, k); | ||
| gemm(dC, Bt, dA, n, m, k); | ||
| gemm(At, dC, dB, k, n, m); | ||
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| return MX_SUCCESS; | ||
| } | ||
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| MXReturnValue parseAttrs(std::map<std::string, std::string> attrs, int* num_in, int* num_out) { | ||
| *num_in = 2; | ||
| *num_out = 1; | ||
| return MX_SUCCESS; | ||
| } | ||
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| MXReturnValue inferType(std::map<std::string, std::string> attrs, | ||
| std::vector<int> &intypes, | ||
| std::vector<int> &outtypes) { | ||
| // validate inputs | ||
| if (intypes.size() != 2) { | ||
| std::cout << "Expected 2 inputs to inferType" << std::endl; | ||
| return MX_FAIL; | ||
| } | ||
| for (unsigned i = 0; i < intypes.size(); i++) { | ||
| if (intypes[i] != kFloat32) { | ||
| std::cout << "Expected input " << i << " to have float32 type" << std::endl; | ||
| return MX_FAIL; | ||
| } | ||
| } | ||
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| outtypes[0] = intypes[0]; | ||
| return MX_SUCCESS; | ||
| } | ||
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| MXReturnValue inferShape(std::map<std::string, std::string> attrs, | ||
| std::vector<std::vector<unsigned int>> &inshapes, | ||
| std::vector<std::vector<unsigned int>> &outshapes) { | ||
| // validate inputs | ||
| if (inshapes.size() != 2) { | ||
| std::cout << "Expected 2 inputs to inferShape" << std::endl; | ||
| return MX_FAIL; | ||
| } | ||
| if (inshapes[0].size() != 2 || inshapes[1].size() != 2) { | ||
| std::cout << "Expected 2D matrices for both inputs to inferShape" << std::endl; | ||
| return MX_FAIL; | ||
| } | ||
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| unsigned n = inshapes[0][0]; | ||
| unsigned k = inshapes[0][1]; | ||
| unsigned kk = inshapes[1][0]; | ||
| unsigned m = inshapes[1][1]; | ||
| if (k != kk) { | ||
| std::cout << "Exected first input axis 1 equals to second input axis 0" << std::endl; | ||
| return MX_FAIL; | ||
| } | ||
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| outshapes[0] = {n, m}; | ||
| return MX_SUCCESS; | ||
| } | ||
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| REGISTER_OP(my_gemm) | ||
| .setForward(forward) | ||
| .setBackward(backward) | ||
| .setParseAttrs(parseAttrs) | ||
| .setInferType(inferType) | ||
| .setInferShape(inferShape); | ||
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| /* ------------------------------------------------------------------------- */ | ||
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| class MyStatefulGemm : public CustomStatefulOp { | ||
| public: | ||
| explicit MyStatefulGemm(int count) : count(count) {} | ||
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| MXReturnValue Forward(std::vector<MXTensor> inputs, | ||
| std::vector<MXTensor> outputs, | ||
| OpResource op_res) { | ||
| ++count; | ||
| std::cout << "Info: keyword + number of forward: " << count << std::endl; | ||
| std::map<std::string, std::string> attrs; | ||
| return forward(attrs, inputs, outputs, op_res); | ||
| } | ||
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| MXReturnValue Backward(std::vector<MXTensor> inputs, | ||
| std::vector<MXTensor> outputs, | ||
| OpResource op_res) { | ||
| std::map<std::string, std::string> attrs; | ||
| return backward(attrs, inputs, outputs, op_res); | ||
| } | ||
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| ~MyStatefulGemm() {} | ||
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| private: | ||
| int count; | ||
| }; | ||
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| MXReturnValue createOpState(std::map<std::string, std::string> attrs, | ||
| CustomStatefulOp** op_inst) { | ||
| int count = 0; | ||
| if (attrs.count("test_kw") > 0) | ||
| count = std::stoi(attrs["test_kw"]); | ||
| *op_inst = new MyStatefulGemm(count); | ||
| std::cout << "Info: stateful operator created" << std::endl; | ||
| return MX_SUCCESS; | ||
| } | ||
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| MXReturnValue mutateInputs(std::map<std::string, std::string> attrs, | ||
| std::vector<int> &input_indices) { | ||
| // input_indices.push_back(1); // mark mutate input | ||
| return MX_SUCCESS; | ||
| } | ||
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| REGISTER_OP(state_gemm) | ||
| .setParseAttrs(parseAttrs) | ||
| .setInferType(inferType) | ||
| .setInferShape(inferShape) | ||
| .setMutateInputs(mutateInputs) | ||
| .setCreateOpState(createOpState); | ||
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| MXReturnValue initialize(int version) { | ||
| if (version >= 10400) { | ||
| std::cout << "MXNet version " << version << " supported" << std::endl; | ||
| return MX_SUCCESS; | ||
| } else { | ||
| std::cout << "MXNet version " << version << " not supported" << std::endl; | ||
| return MX_FAIL; | ||
| } | ||
| } |
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