| /* |
| * 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. |
| */ |
| |
| #include "utils.h" |
| |
| #include <tvm/relax/analysis.h> |
| |
| namespace tvm { |
| namespace relax { |
| |
| bool IsScalarTensor(const StructInfo& sinfo) { |
| if (!sinfo->IsInstance<TensorStructInfoNode>()) { |
| return false; |
| } |
| TensorStructInfo tensor_sinfo = Downcast<TensorStructInfo>(sinfo); |
| if (!tensor_sinfo->shape.defined() || !tensor_sinfo->shape->IsInstance<ShapeExprNode>()) { |
| return false; |
| } |
| return tensor_sinfo->shape.as<ShapeExprNode>()->values.size() == 0; |
| } |
| |
| bool IsScalarTensor(const Expr& expr) { return IsScalarTensor(GetStructInfo(expr)); } |
| |
| bool IsNestedTensor(const StructInfo& sinfo) { |
| return IsNestedTensorConditioned(sinfo, [](const TensorStructInfo& sinfo) { return true; }); |
| } |
| |
| bool IsNestedTensor(const Expr& expr) { return IsNestedTensor(GetStructInfo(expr)); } |
| |
| Function ComposeFunctions(Function func_a, Function func_b) { |
| Array<Binding> bindings; |
| |
| Var func_a_output("func_a_output", func_a->ret_struct_info); |
| |
| bindings.push_back(VarBinding(func_a_output, func_a->body)); |
| |
| auto func_a_outputs = [&]() -> Array<Expr> { |
| if (auto func_a_output_tuple = func_a->ret_struct_info.as<TupleStructInfoNode>()) { |
| Array<Expr> outputs; |
| for (size_t i = 0; i < func_a_output_tuple->fields.size(); i++) { |
| outputs.push_back(TupleGetItem(func_a_output, i)); |
| } |
| return outputs; |
| } else { |
| return {func_a_output}; |
| } |
| }(); |
| |
| if (func_b->params.size() == 1 && func_b->params[0]->struct_info_.as<TupleStructInfoNode>()) { |
| // Special case where the output of the first function is a tuple |
| // that should be provided as-is to the second function, and |
| // should not be unpacked into individual elements. |
| auto param = func_b->params[0]; |
| bindings.push_back(MatchCast(param, func_a_output, GetStructInfo(param))); |
| } else { |
| CHECK_EQ(func_a_outputs.size(), func_b->params.size()) |
| << "ValueError: " |
| << "Cannot compose functions together. " |
| << "First function produces " << func_a_outputs.size() << " values, " |
| << "but second function expects " << func_b->params.size() << " parameters as input"; |
| for (size_t i = 0; i < func_a_outputs.size(); i++) { |
| auto param = func_b->params[i]; |
| bindings.push_back(MatchCast(param, func_a_outputs[i], GetStructInfo(param))); |
| } |
| } |
| |
| auto new_body = SeqExpr({BindingBlock(bindings)}, func_b->body); |
| |
| auto new_function = Function(func_a->params, new_body, func_b->ret_struct_info, |
| func_a->is_pure && func_b->is_pure, func_a->attrs); |
| |
| new_function = CopyWithNewVars(new_function); |
| new_function = Downcast<Function>(CanonicalizeBindings(new_function)); |
| new_function = Downcast<Function>(RemoveAllUnused(new_function)); |
| |
| return new_function; |
| } |
| |
| } // namespace relax |
| } // namespace tvm |