diff --git a/lib/Conversion/TorchToLinalg/IndirectDataMovement.cpp b/lib/Conversion/TorchToLinalg/IndirectDataMovement.cpp
index fbc5004c9..07e4b23a1 100644
--- a/lib/Conversion/TorchToLinalg/IndirectDataMovement.cpp
+++ b/lib/Conversion/TorchToLinalg/IndirectDataMovement.cpp
@@ -222,23 +222,9 @@ public:
     Value weight = adaptor.getWeight();
     Value indices = adaptor.getIndices();
     Value offsets = adaptor.getOffsets();
-    Value scaleGradByFreq = op.getScaleGradByFreq();
     Value mode = op.getMode();
-    Value sparse = op.getSparse();
     Value includeLastOffset = op.getIncludeLastOffset();
 
-    bool scaleGradByFreqBool;
-    if (!matchPattern(scaleGradByFreq,
-                      m_TorchConstantBool(&scaleGradByFreqBool))) {
-      return rewriter.notifyMatchFailure(
-          op, "scale_grad_by_freq is expected to be a constant boolean value.");
-    }
-
-    if (scaleGradByFreqBool) {
-      return rewriter.notifyMatchFailure(
-          op, "Unimplemented: scale_grad_by_freq=True.");
-    }
-
     int64_t modeInt;
     if (!matchPattern(mode, m_TorchConstantInt(&modeInt))) {
       return rewriter.notifyMatchFailure(
@@ -251,18 +237,6 @@ public:
                                          "not supported yet for EmbeddingBag.");
     }
 
-    bool isSparse;
-    if (!matchPattern(sparse, m_TorchConstantBool(&isSparse))) {
-      return rewriter.notifyMatchFailure(
-          op, "sparse is expected to be a constant boolean value.");
-    }
-
-    if (isSparse) {
-      return rewriter.notifyMatchFailure(
-          op,
-          "Unimplemented: Sparse mode is not supported yet for EmbeddingBag.");
-    }
-
     bool discardLastOffset;
     if (!matchPattern(includeLastOffset,
                       m_TorchConstantBool(&discardLastOffset))) {
diff --git a/test/Conversion/TorchToLinalg/embeddingBag.mlir b/test/Conversion/TorchToLinalg/embeddingBag.mlir
new file mode 100644
index 000000000..05aa57fc7
--- /dev/null
+++ b/test/Conversion/TorchToLinalg/embeddingBag.mlir
@@ -0,0 +1,52 @@
+// RUN: torch-mlir-opt <%s -convert-torch-to-linalg -split-input-file -verify-diagnostics | FileCheck %s
+
+// CHECK: #[[$ATTR_0:.+]] = affine_map<(d0, d1, d2) -> (d1)>
+// CHECK: #[[$ATTR_1:.+]] = affine_map<(d0, d1, d2) -> (d0)>
+// CHECK: #[[$ATTR_2:.+]] = affine_map<(d0, d1, d2) -> (d0, d2)>
+// CHECK-LABEL:   func.func @torchAtenEmbeddingBagPaddingIdx
+// CHECK:         %[[VAL_0:.*]]: !torch.vtensor<[1000000,64],f32>
+// CHECK:         %[[VAL_1:.*]]: !torch.vtensor<[204790],si64>
+// CHECK:         %[[VAL_2:.*]]: !torch.vtensor<[2048],si64>
+// CHECK:         %[[VAL_3:.*]] = torch_c.to_builtin_tensor %[[VAL_2]] : !torch.vtensor<[2048],si64> -> tensor<2048xi64>
+// CHECK:         %[[VAL_4:.*]] = torch_c.to_builtin_tensor %[[VAL_1]] : !torch.vtensor<[204790],si64> -> tensor<204790xi64>
+// CHECK:         %[[VAL_5:.*]] = torch_c.to_builtin_tensor %[[VAL_0]] : !torch.vtensor<[1000000,64],f32> -> tensor<1000000x64xf32>
+// CHECK-DAG:     %[[VAL_6:.*]] = torch.constant.bool true
+// CHECK-DAG:     %[[VAL_7:.*]] = torch.constant.int 0
+// CHECK-DAG:     %[[VAL_8:.*]] = torch.constant.bool true
+func.func @torchAtenEmbeddingBagPaddingIdx(%weight: !torch.vtensor<[1000000,64],f32>,
+                                           %indices: !torch.vtensor<[204790],si64>,
+                                           %offsets: !torch.vtensor<[2048],si64>) -> (!torch.vtensor<[2048,64],f32>,
+                                                                                     !torch.vtensor<[0],si64>,
+                                                                                     !torch.vtensor<[2048],si64>,
+                                                                                     !torch.vtensor<[2048],si64>)
+ {
+    %scale_grad_by_freq = torch.constant.bool true
+    %mode = torch.constant.int 0
+    %sparse = torch.constant.bool true
+    %per_sample_weights = torch.constant.none
+    %include_last_offset = torch.constant.bool false
+    %padding_idx = torch.constant.none
+    %result0, %result1, %result2, %result3 = torch.aten.embedding_bag.padding_idx %weight,
+                                                                                  %indices,
+                                                                                  %offsets,
+                                                                                  %scale_grad_by_freq,
+                                                                                  %mode,
+                                                                                  %sparse,
+                                                                                  %per_sample_weights,
+                                                                                  %include_last_offset,
+                                                                                  %padding_idx :
+                                                                                               !torch.vtensor<[1000000,64],f32>,
+                                                                                               !torch.vtensor<[204790],si64>,
+                                                                                               !torch.vtensor<[2048],si64>,
+                                                                                               !torch.bool,
+                                                                                               !torch.int,
+                                                                                               !torch.bool,
+                                                                                               !torch.none,
+                                                                                               !torch.bool,
+                                                                                               !torch.none -> !torch.vtensor<[2048,64],f32>,
+                                                                                                              !torch.vtensor<[0],si64>,
+                                                                                                              !torch.vtensor<[2048],si64>,
+                                                                                                              !torch.vtensor<[2048],si64>
+
+    return %result0, %result1, %result2, %result3 : !torch.vtensor<[2048,64],f32>, !torch.vtensor<[0],si64>, !torch.vtensor<[2048],si64>, !torch.vtensor<[2048],si64>
+}