| /* |
| * 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 relax/src/ir/emit_te.cc |
| */ |
| #include "./emit_te.h" |
| |
| #include <tvm/relax/struct_info.h> |
| #include <tvm/tir/stmt_functor.h> |
| |
| namespace tvm { |
| namespace relax { |
| |
| // RXPlaceholderOpNode |
| TVM_STATIC_IR_FUNCTOR(ReprPrinter, vtable) |
| .set_dispatch<RXPlaceholderOpNode>([](const ObjectRef& node, ReprPrinter* p) { |
| auto* op = static_cast<const RXPlaceholderOpNode*>(node.get()); |
| p->stream << "rxplaceholder(" << op->name << ", " << op << ")"; |
| }); |
| |
| TVM_REGISTER_NODE_TYPE(RXPlaceholderOpNode); |
| |
| te::Tensor TETensor(Expr value, Map<tir::Var, PrimExpr> tir_var_map, std::string name) { |
| auto n = make_object<RXPlaceholderOpNode>(); |
| n->name = name; |
| n->value = value; |
| |
| // If the value is a constant, it might come as an argument of EmitTE and thus its shape and |
| // checked-type might not be properly set. In this case we set the shape and dtype of the returned |
| // TE tensor. |
| if (const auto* constant = value.as<ConstantNode>()) { |
| n->dtype = DataType(constant->data->dtype); |
| |
| int ndim = constant->data->ndim; |
| ShapeTuple shape_tuple = constant->data.Shape(); |
| Array<PrimExpr> shape; |
| shape.reserve(ndim); |
| for (int i = 0; i < ndim; ++i) { |
| shape.push_back(IntImm(DataType::Int(64), shape_tuple[i])); |
| } |
| n->shape = std::move(shape); |
| return te::PlaceholderOp(n).output(0); |
| } |
| ICHECK(value->struct_info_.defined()) << "value must be normalized and contain StructInfo"; |
| auto* tensor_sinfo = GetStructInfoAs<TensorStructInfoNode>(value); |
| ICHECK(tensor_sinfo) << "Value must be a tensor"; |
| auto* shape_expr = tensor_sinfo->shape.as<ShapeExprNode>(); |
| CHECK(shape_expr) |
| << "ValueError: Expression does not have an known symbolic shape, please consider use " |
| "match_cast " |
| << "to constrain the shape before passing into te_tensor"; |
| n->shape = shape_expr->values.Map( |
| [&tir_var_map](const PrimExpr& e) { return tir::Substitute(e, tir_var_map); }); |
| n->dtype = tensor_sinfo->dtype; |
| return te::PlaceholderOp(n).output(0); |
| } |
| |
| TVM_REGISTER_GLOBAL("relax.TETensor").set_body_typed(TETensor); |
| |
| } // namespace relax |
| } // namespace tvm |