From: James Reed <jamesreed@fb.com>
Date: Fri, 8 Feb 2019 01:22:00 +0000 (-0800)
Subject: aten::_convolution now participates in shape analysis (#16837)
X-Git-Tag: accepted/tizen/6.5/unified/20211028.231830~1412
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=c35f3ae89fc2756ef1a7078b200689ade4f118e7;p=platform%2Fupstream%2Fpytorch.git

aten::_convolution now participates in shape analysis (#16837)

Summary:
During tracing, we record `aten::_convolution` rather than `aten::convolution`. The schema for the former was not present in the shape analysis pass, and resulted in some missing shape information.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16837

Differential Revision: D13993831

Pulled By: jamesr66a

fbshipit-source-id: ebb63bf628d81613258caf773a3af5930303ce5a
---

diff --git a/torch/csrc/jit/passes/shape_analysis.cpp b/torch/csrc/jit/passes/shape_analysis.cpp
index 8087812..41bbd18 100644
--- a/torch/csrc/jit/passes/shape_analysis.cpp
+++ b/torch/csrc/jit/passes/shape_analysis.cpp
@@ -786,6 +786,7 @@ class ShapePropagator {
             "aten::conv_transpose2d(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] output_padding, int groups, int[] dilation) -> Tensor",
             "aten::conv_transpose3d(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] output_padding, int groups, int[] dilation) -> Tensor",
             "aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor",
+            "aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled) -> Tensor",
             "aten::adaptive_avg_pool1d(Tensor self, int[] output_size) -> Tensor",
             "aten::adaptive_avg_pool2d(Tensor self, int[] output_size) -> Tensor",
             "aten::adaptive_avg_pool3d(Tensor self, int[] output_size) -> Tensor",