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torch-mlir/include/npcomp/Dialect/ATen/Transforms/ATenToStd.td

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Add ATen Dialect (#16) This patch adds a dialect intended to be used as a frontend dialect to facilitate lowering from "A Tensor Library" in torch/pytorch. This patch includes several passes that are useful in conjuction with the dialect: --aten-layer-name: Generates layer names for each operation, which are not present in the original pytorch. --aten-to-std: Lower the ATen dialect into standard dialect function calls. --return-elimination-pass: convert functions (primarily the toplevel function) to pass return values by reference. This simplifies pytorch integration. --aten-op-report: generate a textual report about the model --liveness-report Future patches will implement actual integration with the pytorch jit to intercept and generates MLIR in this dialect, then lower the resulting MLIR into function calls through aten-layer-name -> aten-to-std -> return-elimination -> std-to-llvm. The result would then jitted using the LLVM jit, linked against a runtime library which makes calls back into pytorch to implement all the layers. Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com> Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com>
2020-08-13 10:28:04 +08:00
//===- ATenToStd.td ----------------------------------------*- tablegen -*-===//
//
// This file is licensed under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
NFC: Re-organize ATen directory structure and fix warnings. * Still some more work to do on the Transforms tree to bring it in line with the others (will do that as I add things).
2020-10-23 05:13:26 +08:00
#ifndef MLIR_ATEN_TO_STD_TD
Add ATen Dialect (#16) This patch adds a dialect intended to be used as a frontend dialect to facilitate lowering from "A Tensor Library" in torch/pytorch. This patch includes several passes that are useful in conjuction with the dialect: --aten-layer-name: Generates layer names for each operation, which are not present in the original pytorch. --aten-to-std: Lower the ATen dialect into standard dialect function calls. --return-elimination-pass: convert functions (primarily the toplevel function) to pass return values by reference. This simplifies pytorch integration. --aten-op-report: generate a textual report about the model --liveness-report Future patches will implement actual integration with the pytorch jit to intercept and generates MLIR in this dialect, then lower the resulting MLIR into function calls through aten-layer-name -> aten-to-std -> return-elimination -> std-to-llvm. The result would then jitted using the LLVM jit, linked against a runtime library which makes calls back into pytorch to implement all the layers. Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com> Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com>
2020-08-13 10:28:04 +08:00
#define MLIR_ATEN_TO_STD_TD
include "mlir/Dialect/StandardOps/IR/Ops.td"
NFC: Re-organize ATen directory structure and fix warnings. * Still some more work to do on the Transforms tree to bring it in line with the others (will do that as I add things).
2020-10-23 05:13:26 +08:00
include "npcomp/Dialect/ATen/IR/ATenOps.td"
Add ATen Dialect (#16) This patch adds a dialect intended to be used as a frontend dialect to facilitate lowering from "A Tensor Library" in torch/pytorch. This patch includes several passes that are useful in conjuction with the dialect: --aten-layer-name: Generates layer names for each operation, which are not present in the original pytorch. --aten-to-std: Lower the ATen dialect into standard dialect function calls. --return-elimination-pass: convert functions (primarily the toplevel function) to pass return values by reference. This simplifies pytorch integration. --aten-op-report: generate a textual report about the model --liveness-report Future patches will implement actual integration with the pytorch jit to intercept and generates MLIR in this dialect, then lower the resulting MLIR into function calls through aten-layer-name -> aten-to-std -> return-elimination -> std-to-llvm. The result would then jitted using the LLVM jit, linked against a runtime library which makes calls back into pytorch to implement all the layers. Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com> Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com>
2020-08-13 10:28:04 +08:00
#endif