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torch-mlir/frontends/pytorch/test/ivalue_import/tuple.py

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Add Conv2D Torchscript Import Support (#167) Adds support for lowering a torch.nn.Conv2d module to the Torch Dialect through TorchScript import. Generated IR can be viewed here: https://gist.github.com/brycearden/6c0f790115c4577249372ef82768e6fd Required implementing support for tuple in the ivalue importer and list in the node importer.
2021-02-26 04:14:00 +08:00
# -*- Python -*-
# This file is licensed under a pytorch-style license
# See frontends/pytorch/LICENSE for license information.
import typing
import torch
import torch_mlir
# RUN: %PYTHON %s | npcomp-opt | FileCheck %s
mb = torch_mlir.ModuleBuilder()
class TestModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.t = (1, 2)
# CHECK: torch.class_type @[[CLASSTYPE:.*]] {
# TODO: Don't lose element type.
# CHECK: }
Add `!torch.int` type. This replaces the ad-hoc use of `i64` throughout the Torch layer, and helps to keep it crystal clear the distinction between `!torch.int` (which is modeling the Python `int` type) and the various types that serve as dtypes of tensors, which are a totally different type universe. Changes: - `!torch.int` type and C bindings. - Change `torch.constant.int` parser to not need the `: i64` at the end. - `m_TorchConstantInt` matcher to aid with matching constants. - BackendTypeConversion changes for `!torch.int` -> `i64` type conversion. - Refactor finalizing patterns in FinalizingBackendTypeConversionPass (they were getting very repetitive). - Mechanical rewriting of `!torch.int` to `i64` in all the tests, and `AnyTorchIntType` to `Torch_IntType` in the `.td` files.
2021-06-17 06:53:15 +08:00
# CHECK: %[[N1:.*]] = torch.constant.int 1
# CHECK: %[[N2:.*]] = torch.constant.int 2
# CHECK: %[[TUPLE:.*]] = torch.prim.TupleConstruct %[[N1]], %[[N2]] : !torch.int, !torch.int
Add Conv2D Torchscript Import Support (#167) Adds support for lowering a torch.nn.Conv2d module to the Torch Dialect through TorchScript import. Generated IR can be viewed here: https://gist.github.com/brycearden/6c0f790115c4577249372ef82768e6fd Required implementing support for tuple in the ivalue importer and list in the node importer.
2021-02-26 04:14:00 +08:00
# CHECK: torch.nn_module {
Add `!torch.int` type. This replaces the ad-hoc use of `i64` throughout the Torch layer, and helps to keep it crystal clear the distinction between `!torch.int` (which is modeling the Python `int` type) and the various types that serve as dtypes of tensors, which are a totally different type universe. Changes: - `!torch.int` type and C bindings. - Change `torch.constant.int` parser to not need the `: i64` at the end. - `m_TorchConstantInt` matcher to aid with matching constants. - BackendTypeConversion changes for `!torch.int` -> `i64` type conversion. - Refactor finalizing patterns in FinalizingBackendTypeConversionPass (they were getting very repetitive). - Mechanical rewriting of `!torch.int` to `i64` in all the tests, and `AnyTorchIntType` to `Torch_IntType` in the `.td` files.
2021-06-17 06:53:15 +08:00
# CHECK: torch.slot "t", %[[TUPLE]] : !torch.tuple<!torch.int, !torch.int>
Add Conv2D Torchscript Import Support (#167) Adds support for lowering a torch.nn.Conv2d module to the Torch Dialect through TorchScript import. Generated IR can be viewed here: https://gist.github.com/brycearden/6c0f790115c4577249372ef82768e6fd Required implementing support for tuple in the ivalue importer and list in the node importer.
2021-02-26 04:14:00 +08:00
# CHECK: } : !torch.nn.Module<"[[CLASSTYPE]]">
test_module = TestModule()
recursivescriptmodule = torch.jit.script(test_module)
# TODO: Automatically handle unpacking Python class RecursiveScriptModule into the underlying ScriptModule.
mb.import_module(recursivescriptmodule._c)
mb.module.operation.print()