lhutton1 commented on a change in pull request #5915: URL: https://github.com/apache/incubator-tvm/pull/5915#discussion_r456310867
########## File path: src/relay/backend/contrib/arm_compute_lib/codegen.cc ########## @@ -0,0 +1,186 @@ +/* + * 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/arm_compute_lib/codegen_acl.cc + * \brief Implementation of the Relay -> ACL JSON serializer. + */ +#include <tvm/ir/module.h> +#include <tvm/relay/attrs/nn.h> +#include <tvm/relay/type.h> + +#include "../../utils.h" +#include "codegen_acl.h" + +namespace tvm { +namespace relay { +namespace contrib { +namespace arm_compute_lib { + +using JSONGraphNode = tvm::runtime::json::JSONGraphNode; +using JSONGraphNodeEntry = tvm::runtime::json::JSONGraphNodeEntry; + +std::vector<JSONGraphNodeEntry> ACLJSONSerializer::VisitExpr_(const CallNode* cn) { + Expr expr = GetRef<Expr>(cn); + std::string name; + std::shared_ptr<JSONGraphNode> json_node; + + if (cn->op.as<OpNode>()) { + json_node = CreateOpJSONNode(cn); + } else if (const auto* fn = cn->op.as<FunctionNode>()) { + auto comp = fn->GetAttr<String>(attr::kComposite); + CHECK(comp.defined()) << "Arm Compute Library JSON runtime only supports composite functions."; + name = comp.value(); + if (name == "arm_compute_lib.conv2d") { + json_node = CreateCompositeConvJSONNode(cn); + } else { + LOG(FATAL) << "Unrecognized Arm Compute Library pattern: " << name; + } + } else { + LOG(FATAL) << "Arm Compute Library JSON runtime does not support calls to " + << cn->op->GetTypeKey(); + } + + return AddNode(json_node, GetRef<Expr>(cn)); +} + +std::shared_ptr<JSONGraphNode> ACLJSONSerializer::CreateOpJSONNode(const CallNode* cn) { + const auto* op = cn->op.as<OpNode>(); + CHECK(op); + const std::string name = op->name; + // Collect inputs + std::vector<JSONGraphNodeEntry> inputs; + for (const auto& arg : cn->args) { + auto res = VisitExpr(arg); + inputs.insert(inputs.end(), res.begin(), res.end()); + } + // Create JSON op + auto json_node = std::make_shared<JSONGraphNode>(name, "kernel", inputs, 1); + SetCallNodeAttribute(json_node, cn); + return json_node; +} + +std::shared_ptr<JSONGraphNode> ACLJSONSerializer::CreateCompositeConvJSONNode(const CallNode* cn) { + const std::string name = "arm_compute_lib.conv2d"; + const CallNode* pad = nullptr; + const CallNode* conv; + const CallNode* bias = nullptr; + bool has_activation = false; + + // Unpack composite function + const auto* fn = cn->op.as<FunctionNode>(); + CHECK(fn); + const auto* current_call = fn->body.as<CallNode>(); + if (backend::IsOp(current_call, "nn.relu")) { + has_activation = true; + current_call = current_call->args[0].as<CallNode>(); + } + if (backend::IsOp(current_call, "nn.bias_add")) { + bias = current_call; + current_call = current_call->args[0].as<CallNode>(); + } + CHECK(backend::IsOp(current_call, "nn.conv2d")); + conv = current_call; + if (!current_call->args.empty() && current_call->args[0]->IsInstance<CallNode>()) { + current_call = current_call->args[0].as<CallNode>(); + if (backend::IsOp(current_call, "nn.pad")) { + pad = current_call; + } + } + + const auto* conv_attr = conv->attrs.as<Conv2DAttrs>(); + CHECK(conv_attr); + CHECK(conv_attr->kernel_layout == "OHWI") + << "Kernel layout must be OHWI, has the module been pre-processed correctly?"; + + std::vector<JSONGraphNodeEntry> inputs; + inputs.push_back(VisitExpr(cn->args[0])[0]); + inputs.push_back(VisitExpr(conv->args[1])[0]); + if (bias) { + inputs.push_back(VisitExpr(bias->args[1])[0]); + } + + auto json_node = std::make_shared<JSONGraphNode>(name, "kernel", inputs, 1); + SetCallNodeAttribute(json_node, conv); + + // Override attributes + if (pad) { + const auto* pad_attr = pad->attrs.as<PadAttrs>(); + CHECK(pad_attr); + auto p = pad_attr->pad_width; + // Convert to TVM layout for now, conversion to ACL layout takes place in runtime. + // Standard convolution pad layout for TVM: top, left, bottom, right. + std::vector<std::string> padding = {std::to_string(p[1][0].as<IntImmNode>()->value), + std::to_string(p[2][0].as<IntImmNode>()->value), + std::to_string(p[1][1].as<IntImmNode>()->value), + std::to_string(p[2][1].as<IntImmNode>()->value)}; + std::vector<dmlc::any> padding_attr; + padding_attr.emplace_back(padding); + json_node->SetAttr("padding", padding_attr); + } + if (has_activation) { + std::vector<std::string> activation_type = {"relu"}; + std::vector<dmlc::any> act_attr; + act_attr.emplace_back(activation_type); + json_node->SetAttr("activation_type", act_attr); + } + return json_node; +} + +IRModule PreProcessModule(const IRModule& mod) { + IRModule preprocessed_module; + tvm::Map<String, Array<String>> desired_layouts = {{"nn.conv2d", {"NHWC", "OHWI"}}}; + preprocessed_module = transform::ConvertLayout(desired_layouts)(mod); + preprocessed_module = transform::FoldConstant()(preprocessed_module); + return preprocessed_module; +} Review comment: Just the ACL partitions ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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