feat(subgraph): add graph builder

GitOrigin-RevId: f32cfc39e071da45068b4abf9aa585e6d1474150

imperative/src/include/megbrain/imperative/graph_builder.h

+/**
+ * \file imperative/src/include/megbrain/imperative/graph_builder.h
+ * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
+ *
+ * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or
+ * implied.
+ */
+
+#pragma once
+
+#include "megbrain/imperative/subgraph.h"
+
+namespace mgb {
+namespace imperative {
+
+template <typename TDesc>
+class Subgraph::Builder {
+    using graph_t = Subgraph;
+    using var_t = graph_t::var_t;
+    using vars_t = graph_t::vars_t;
+    using op_t = graph_t::op_t;
+    using expr_t = graph_t::expr_t;
+    using exprs_t = std::list<expr_t>;
+    using expr_iter_t = std::list<expr_t>::iterator;
+    using desc_t = TDesc;
+    using descs_t = SmallVector<TDesc>;
+    using infer_fn_t = std::function<descs_t(op_t, descs_t, size_t)>;
+    using encoded_graph_t = EncodedSubraph;
+    using var_map_t = std::unordered_map<var_t, var_t>;
+    vars_t m_inputs;
+    SmallVector<std::pair<var_t, TensorPtr>> m_constants;
+    vars_t m_outputs;
+    exprs_t m_exprs;
+    var_t m_last_var = 0;
+    std::unordered_map<var_t, TDesc> m_var2desc;
+    infer_fn_t m_infer_fn;
+    var_map_t m_var_replace_map;
+
+private:
+    var_t next_var() { return ++m_last_var; }
+
+public:
+    explicit Builder(std::function<descs_t(op_t, descs_t, size_t)> infer_function)
+            : m_infer_fn{infer_function} {}
+    vars_t write_expr(op_t op, vars_t inputs, size_t nr_outputs) {
+        return write_expr_before(m_exprs.end(), std::move(op),
+                                 std::move(inputs), std::move(nr_outputs));
+    }
+    vars_t write_expr_before(expr_iter_t iter, op_t op, vars_t inputs,
+                             size_t nr_outputs) {
+        vars_t outputs;
+        for (size_t i = 0; i < nr_outputs; ++i) {
+            outputs.push_back(next_var());
+        }
+        m_exprs.insert(iter, {op, inputs, outputs});
+        descs_t input_descs = get_descs(inputs);
+        descs_t output_descs = m_infer_fn(op, input_descs, nr_outputs);
+        mgb_assert(output_descs.size() == nr_outputs,
+                   "bad infer_function: output descs size mismatch");
+        for (size_t i = 0; i < nr_outputs; ++i) {
+            m_var2desc[outputs[i]] = output_descs[i];
+        }
+        return outputs;
+    }
+    var_t write_constant(TensorPtr constant, desc_t desc) {
+        var_t constant_var = next_var();
+        m_constants.emplace_back(constant_var, constant);
+        m_var2desc[constant_var] = std::move(desc);
+        return constant_var;
+    }
+    var_t write_input(desc_t input_desc) {
+        var_t input = next_var();
+        m_var2desc[input] = input_desc;
+        m_inputs.push_back(input);
+        return input;
+    }
+    vars_t write_inputs(descs_t input_descs) {
+        vars_t inputs;
+        for (auto&& input_desc: input_descs) {
+            inputs.push_back(write_input(input_desc));
+        }
+        return inputs;
+    }
+    void add_output(var_t var) { m_outputs.push_back(var); }
+    void add_outputs(vars_t vars) {
+        m_outputs.insert(m_outputs.begin(), vars.begin(), vars.end());
+    }
+    desc_t get_desc(var_t var) { return m_var2desc.at(var); }
+    descs_t get_descs(vars_t vars) {
+        descs_t descs;
+        for (auto&& var : vars) {
+            descs.push_back(get_desc(var));
+        }
+        return descs;
+    }
+    encoded_graph_t encode() const {
+        graph_t graph{m_inputs,
+                      m_constants,
+                      m_outputs,
+                      {m_exprs.begin(), m_exprs.end()}};
+        graph.replace_vars(m_var_replace_map);
+        graph.remove_unused_exprs();
+        return encoded_graph_t::make(std::move(graph));
+    }
+    void replace_var(var_t old_var, var_t new_var) {
+        mgb_assert(!m_var_replace_map.count(old_var),
+                   "var cannot be replaced twice");
+        m_var_replace_map[old_var] = new_var;
+    }
+    template <typename TFunctor>
+    void iterate(TFunctor&& functor) {
+        for (expr_iter_t iter = m_exprs.begin(); iter != m_exprs.end();
+             ++iter) {
+            functor(iter);
+        }
+    }
+    template <typename TFunctor>
+    void reverse_iterate(TFunctor&& functor) {
+        for (expr_iter_t iter = --m_exprs.end();; --iter) {
+            functor(iter);
+            if (iter == m_exprs.begin()) {
+                break;
+            }
+        }
+    }
+    expr_iter_t begin() { return m_exprs.begin(); }
+    expr_iter_t end() { return m_exprs.end(); }
+};
+}  // namespace imperative
+}  // namespace mgb
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