t-vi commented on a change in pull request #7401: URL: https://github.com/apache/tvm/pull/7401#discussion_r822544365
########## File path: src/relay/backend/contrib/libtorch/libtorch_codegen.cc ########## @@ -0,0 +1,147 @@ +/* + * 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. + */ + +/*! + * \file src/relay/backend/contrib/libtorch/codegen.cc + * \brief Implementation of libtorch codegen. + */ + +#include <ATen/DLConvertor.h> +#include <dlpack/dlpack.h> +#include <torch/csrc/jit/api/compilation_unit.h> +#include <torch/csrc/jit/serialization/import.h> +#include <torch/torch.h> +#include <tvm/relay/attrs/nn.h> +#include <tvm/relay/expr_functor.h> +#include <tvm/relay/op.h> +#include <tvm/relay/transform.h> +#include <tvm/relay/type.h> +#include <tvm/runtime/module.h> +#include <tvm/runtime/registry.h> +#include <tvm/tir/op.h> + +#include <fstream> +#include <numeric> +#include <sstream> + +#include "../../utils.h" + +namespace tvm { +namespace relay { +namespace contrib { + +using namespace backend; + +/*! \brief Attributes of a TorchFunction node */ +struct TorchFunctionAttrs : public tvm::AttrsNode<TorchFunctionAttrs> { + std::string serialized_function; + int64_t len; + + TVM_DECLARE_ATTRS(TorchFunctionAttrs, "relay.attrs.TorchFunctionAttrs") { + TVM_ATTR_FIELD(serialized_function).set_default("").describe("Function from fn.save(...)"); + TVM_ATTR_FIELD(len).set_default(-1).describe("Function from fn.save(...)"); + } +}; + +TVM_REGISTER_NODE_TYPE(TorchFunctionAttrs); + +bool TorchOpRel(const Array<Type>& types, int num_inputs, const Attrs& attrs, + const TypeReporter& reporter) { + const auto* sfattrs = attrs.as<TorchFunctionAttrs>(); + std::stringstream str(sfattrs->serialized_function); + torch::jit::Module mod = torch::jit::load(str); + + std::vector<torch::jit::IValue> inputs; + for (int i = 0; i < num_inputs; i++) { + auto* ty = types[i].as<TensorTypeNode>(); + ICHECK(ty) << "only accept tensors as inputs"; + std::vector<int64_t> shape; + for (const auto& s : ty->shape) { + auto* si = s.as<IntImmNode>(); + if (!si) { + return false; + } + shape.push_back(si->value); + } + auto torchScalarType = at::toScalarType(ty->dtype); + + inputs.emplace_back(torch::zeros(shape, at::TensorOptions().dtype(torchScalarType))); + } + auto res = mod.forward(inputs); + auto res_t = res.toTensor(); + ICHECK((int)types.size() == num_inputs + 1) << "only single output supported"; + Array<PrimExpr> res_sizes; + for (int d = 0; d < res_t.dim(); d++) { + res_sizes.push_back(IntImm(DataType::Int(32), res_t.size(d))); + } + reporter->Assign(types[num_inputs], TensorType(res_sizes, DataType(at::getDLDataType(res_t)))); + return true; +} + +RELAY_REGISTER_OP("torch_op") + .set_support_level(99) + .add_type_rel("TorchOpRel", TorchOpRel) + .set_attrs_type<TorchFunctionAttrs>(); + +Expr MakeTorchOp(Array<Expr> args, const std::string& serialized_function) { + static const Op& op = Op::Get("torch_op"); + auto attrs = make_object<TorchFunctionAttrs>(); + attrs->serialized_function = serialized_function; + attrs->len = serialized_function.size(); + return Call(op, args, Attrs(attrs), {}); +} + +TVM_REGISTER_GLOBAL("relay.op._make.torchop").set_body_typed(MakeTorchOp); + +/*! + * \brief The external compiler/codegen tool. It takes a Relay expression/module and + * compile it into a runtime module. + */ +runtime::Module TorchCompiler(const ObjectRef& ref) { + ICHECK(ref->IsInstance<FunctionNode>()) << "The input ref is expected to be a Relay function."; + Function func = Downcast<Function>(ref); + std::string func_name = backend::GetExtSymbol(func); + + ICHECK(func.defined()) << "Input error: expect a Relay function."; + const auto* call = func->body.as<CallNode>(); + ICHECK(call) << "Expected call node\n"; + const auto* op_node = call->op.as<OpNode>(); + ICHECK(op_node) << "Expect OpNode, but got " << call->op->GetTypeKey(); + const auto op_name = GetRef<Op>(op_node)->name; + ICHECK(op_name == "torch_op") << "Unsupported op: " << AsText(call->op, false) << "\n"; + + const auto* attrs = call->attrs.as<TorchFunctionAttrs>(); + + // TensorRTJSONSerializer serializer(func_name, func); + // serializer.serialize(); + // std::string graph_json = serializer.GetJSON(); + + const auto* pf = runtime::Registry::Get("runtime.torch_runtime_create"); + ICHECK(pf != nullptr) << "Cannot find Torch runtime module create function."; Review comment: Thank you! I was unsure whether runtime and codegen cross-links should go through the registry, I'll fix that. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
