2020-08-13 10:28:04 +08:00
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//===- ATen.td ---------------------------------------------*- tablegen -*-===//
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//
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// This file is licensed under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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2020-10-23 05:13:26 +08:00
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#ifndef NPCOMP_DIALECT_ATEN_IR_ATEN_OPS
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#define NPCOMP_DIALECT_ATEN_IR_ATEN_OPS
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2020-08-13 10:28:04 +08:00
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2020-10-23 05:13:26 +08:00
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include "npcomp/Dialect/ATen/IR/ATenDialect.td"
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include "npcomp/Dialect/ATen/IR/ATenOpInterface.td"
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2020-10-23 14:31:34 +08:00
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include "npcomp/Dialect/Torch/IR/OpInterfaces.td"
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2021-01-28 08:35:44 +08:00
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include "npcomp/Dialect/Torch/IR/TorchTypes.td"
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2020-08-13 10:28:04 +08:00
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include "mlir/Interfaces/SideEffectInterfaces.td"
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2020-08-28 06:09:10 +08:00
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2020-08-13 10:28:04 +08:00
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// TODO: convert to "let results =" style
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2020-08-28 06:09:10 +08:00
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// TODO: Rename prefix from "aten" to "ATen" for consistency.
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2020-08-13 10:28:04 +08:00
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class aten_Op<string mnemonic, list<OpTrait> traits = [StatisticsOpInterface]> :
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2020-08-28 06:09:10 +08:00
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Op<ATen_Dialect, mnemonic, traits>;
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2020-08-13 10:28:04 +08:00
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// Most ops are automatically generated from pytorch specs.
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2020-10-23 05:13:26 +08:00
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include "npcomp/Dialect/ATen/IR/GeneratedATenOps.td"
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2020-10-28 09:13:23 +08:00
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include "npcomp/Dialect/ATen/IR/LegacyGeneratedATenOps.td"
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2020-08-13 10:28:04 +08:00
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def aten_BatchNormOp: aten_Op<"batch_norm", [NoSideEffect, StatisticsOpInterface]>,
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Results<(outs AnyTensor:$output, AnyTensor:$save_mean, AnyTensor:$save_invstd)> {
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let arguments = (
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ins AnyType:$arg0,
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AnyType:$arg1,
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AnyType:$arg2,
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AnyType:$arg3,
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AnyType:$arg4,
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AnyType:$arg5,
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AnyType:$arg6,
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AnyType:$arg7,
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AnyType:$arg8
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);
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let summary = "BatchNorm operator";
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let description = [{
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BatchNorm operator
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}];
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let extraClassDeclaration = [{
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std::map<std::string, uint64_t> getStatistics();
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}];
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}
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// We have list constants, which come out of pytorch. Represent them using
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// our own constant-like type, which gets lowered to std_ConstantOp later.
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def aten_ConstantOp: aten_Op<"constant", [NoSideEffect]>,
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Results<(outs AnyType)> {
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let summary = "Constant operator";
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let description = [{
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Constant operator
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}];
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}
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def aten_FlattenOp: aten_Op<"flatten", [NoSideEffect, StatisticsOpInterface]>,
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Results<(outs AnyTensor)> {
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let arguments = (
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ins AnyType:$arg0,
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AnyType:$arg1,
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AnyType:$arg2
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);
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let summary = "Flatten operator";
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let description = [{
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Flatten operator
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}];
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let extraClassDeclaration = [{
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std::map<std::string, uint64_t> getStatistics();
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}];
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}
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def aten_MaxPool2dOp: aten_Op<"max_pool2d", [NoSideEffect, StatisticsOpInterface]>,
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Results<(outs AnyTensor)> {
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let arguments = (
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ins AnyType:$arg0,
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AnyType:$arg1,
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AnyType:$arg2,
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AnyType:$arg3,
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AnyType:$arg4,
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AnyType:$arg5
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);
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let summary = "MaxPool2d operator";
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let description = [{
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MaxPool2d operator
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}];
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let extraClassDeclaration = [{
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std::map<std::string, uint64_t> getStatistics();
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}];
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}
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def aten_TypeCastOp : aten_Op<"type_cast", [NoSideEffect]>,
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Results<(outs AnyType)> {
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let summary = "TypeCast operator";
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let arguments = (
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ins AnyType:$x
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);
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}
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2020-10-23 05:13:26 +08:00
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#endif // NPCOMP_DIALECT_ATEN_IR_ATEN_OPS
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