| /* |
| * 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 tensor.cc |
| */ |
| #include <tvm/ffi/function.h> |
| #include <tvm/ffi/reflection/registry.h> |
| #include <tvm/te/operation.h> |
| #include <tvm/te/tensor.h> |
| |
| namespace tvm { |
| namespace te { |
| |
| void TensorNode::RegisterReflection() { |
| namespace refl = tvm::ffi::reflection; |
| refl::ObjectDef<TensorNode>() |
| .def_ro("shape", &TensorNode::shape) |
| .def_ro("dtype", &TensorNode::dtype) |
| .def_ro("op", &TensorNode::op) |
| .def_ro("value_index", &TensorNode::value_index); |
| } |
| |
| TVM_FFI_STATIC_INIT_BLOCK() { TensorNode::RegisterReflection(); } |
| |
| IterVar thread_axis(Range dom, std::string tag) { |
| return IterVar(dom, Var(tag, dom.defined() ? dom->extent.dtype() : DataType::Int(32)), |
| kThreadIndex, tag); |
| } |
| |
| IterVar reduce_axis(Range dom, std::string name) { |
| return IterVar(dom, Var(name, dom->extent.dtype()), kCommReduce); |
| } |
| |
| Var var(std::string name_hint, DataType t) { return Var(name_hint, t); } |
| |
| // Tensor |
| inline PrimExpr Tensor::IndexTensor(ffi::Array<PrimExpr> indices, |
| bool support_negative_indices) const { |
| ffi::Array<PrimExpr> shape = (*this)->shape; |
| |
| if (shape.size() != 0) { |
| ICHECK_EQ(shape.size(), indices.size()) |
| << "Tensor dimension mismatch in read " |
| << "ndim = " << ndim() << ", indices.size=" << indices.size(); |
| } |
| |
| if (support_negative_indices) { |
| for (size_t i = 0; i < shape.size(); i++) { |
| PrimExpr new_index = |
| Select(indices[i] < make_const(indices[i]->dtype, 0), indices[i] + shape[i], indices[i]); |
| indices.Set(i, new_index); |
| } |
| } |
| return ProducerLoad((*this), indices); |
| } |
| |
| PrimExpr Tensor::operator()(ffi::Array<Var> indices) const { |
| ffi::Array<PrimExpr> arr(indices.begin(), indices.end()); |
| return operator()(arr); |
| } |
| |
| PrimExpr Tensor::operator()(ffi::Array<PrimExpr> indices) const { |
| return IndexTensor(indices, false); |
| } |
| |
| PrimExpr Tensor::IndexWithNegativeIndices(ffi::Array<Var> indices) const { |
| ffi::Array<PrimExpr> arr(indices.begin(), indices.end()); |
| return IndexWithNegativeIndices(arr); |
| } |
| |
| PrimExpr Tensor::IndexWithNegativeIndices(ffi::Array<PrimExpr> indices) const { |
| return IndexTensor(indices, true); |
| } |
| |
| ffi::String TensorNode::GetNameHint() const { |
| return op->num_outputs() == 1 ? op->name : (op->name + ".v" + std::to_string(value_index)); |
| } |
| |
| PrimExpr TensorNode::ToPrimExpr() const { return ffi::GetRef<Tensor>(this)(); } |
| |
| Tensor Operation::output(size_t i) const { |
| auto node = ffi::make_object<TensorNode>(); |
| node->op = *this; |
| node->value_index = i; |
| node->dtype = (*this)->output_dtype(i); |
| node->shape = (*this)->output_shape(i); |
| return Tensor(node); |
| } |
| |
| Tensor::Tensor(ffi::Array<PrimExpr> shape, DataType dtype, Operation op, int value_index) { |
| auto n = ffi::make_object<TensorNode>(); |
| n->shape = std::move(shape); |
| n->dtype = dtype; |
| n->op = op; |
| n->value_index = value_index; |
| data_ = std::move(n); |
| } |
| |
| TVM_FFI_STATIC_INIT_BLOCK() { |
| namespace refl = tvm::ffi::reflection; |
| refl::GlobalDef().def( |
| "te.Tensor", [](ffi::Array<PrimExpr> shape, DataType dtype, Operation op, int value_index) { |
| return Tensor(shape, dtype, op, value_index); |
| }); |
| } |
| |
| TVM_STATIC_IR_FUNCTOR(ReprPrinter, vtable) |
| .set_dispatch<TensorNode>([](const ObjectRef& node, ReprPrinter* p) { |
| auto* t = static_cast<const TensorNode*>(node.get()); |
| p->stream << "Tensor(shape=" << t->shape << ", op.name=" << t->op->name << ')'; |
| }); |
| |
| // Other tensor ops. |
| TVM_FFI_STATIC_INIT_BLOCK() { |
| namespace refl = tvm::ffi::reflection; |
| refl::GlobalDef() |
| .def_method("te.TensorEqual", &Tensor::operator==) |
| .def("te.TensorHash", |
| [](Tensor tensor) -> int64_t { |
| return static_cast<int64_t>(std::hash<Tensor>()(tensor)); |
| }) |
| .def("te.OpGetOutput", |
| [](Operation op, int64_t output) { return op.output(static_cast<size_t>(output)); }) |
| .def_method("te.OpNumOutputs", &OperationNode::num_outputs) |
| .def_method("te.OpInputTensors", &OperationNode::InputTensors); |
| } |
| |
| } // namespace te |
| } // namespace tvm |