From 38c332223e73201dc6fcc8da59d5856e629f7dc7 Mon Sep 17 00:00:00 2001
From: jinchen62 <jinchenye62@gmail.com>
Date: Thu, 29 Aug 2024 05:39:29 -0700
Subject: [PATCH] Fix onnx.Gather lowering with dynamic shapes

---
 .../TorchOnnxToTorch/DefaultDomainGtoP.cpp          | 13 ++++++++++---
 .../TorchOnnxToTorch/simple_ops_g_to_p.mlir         |  3 ++-
 2 files changed, 12 insertions(+), 4 deletions(-)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
index ef50c3bcaf9..9f9a5f89422 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
@@ -1941,7 +1941,6 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
             indicesCt = Torch::kUnknownSize;
             break;
           }
-
           indicesCt *= sz;
         }
 
@@ -1976,8 +1975,16 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
           return success();
         }
 
-        rewriter.replaceOpWithNewOp<Torch::AtenSqueezeOp>(binder.op, resultType,
-                                                          gather);
+        // 0 indicesRank will always squeeze the axis dim
+        // Use PrimsSqueezeOp for the case of result with dynamic shape
+        SmallVector<Value> dimList({index});
+        Value dimValueList = rewriter.create<Torch::PrimListConstructOp>(
+            loc,
+            rewriter.getType<Torch::ListType>(
+                rewriter.getType<Torch::IntType>()),
+            dimList);
+        rewriter.replaceOpWithNewOp<Torch::PrimsSqueezeOp>(
+            binder.op, resultType, gather, dimValueList);
         return success();
       });
   patterns.onOp(
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
index 2e7b5908888..64096fd23b7 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir
@@ -78,7 +78,8 @@ func.func @test_gather_scalar(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.
   // CHECK: %[[SEL:.+]] = torch.aten.where.self %[[LT]], %[[ADD]], %arg1
   // CHECK: %[[FLAT:.+]] = torch.aten.unsqueeze %[[SEL]], %[[ZERO]] : !torch.vtensor<[],si64>, !torch.int -> !torch.vtensor<[1],si64>
   // CHECK: %[[ISEL:.+]] = torch.aten.index_select %arg0, %[[AXIS]], %[[FLAT]]
-  // CHECK: %[[RES:.+]] = torch.aten.squeeze %[[ISEL]] : !torch.vtensor<[1,4,5],f32> -> !torch.vtensor<[4,5],f32>
+  // CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[AXIS]] : (!torch.int) -> !torch.list<int>
+  // CHECK: %[[RES:.+]] = torch.prims.squeeze %[[ISEL]], %[[DIMS]] : !torch.vtensor<[1,4,5],f32>, !torch.list<int> -> !torch.vtensor<[4,5],f32>
   // CHECK: return %[[RES]]
   %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[], si64>) -> !torch.vtensor<[4,5],f32>
   return %0 : !torch.vtensor<[4,5],f32>