diff --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
@@ -108,7 +108,7 @@
 
   let arguments = (ins
     Tosa_Tensor4D:$input,
-    Tosa_Tensor4D:$weight,
+    4DTensorOf<[Tosa_Weight]>:$weight,
     Tosa_Tensor1D:$bias,
 
     Tosa_IntArrayAttr4:$pad,
@@ -140,7 +140,7 @@
 
   let arguments = (ins
     Tosa_Tensor5D:$input,
-    Tosa_Tensor5D:$weight,
+    TensorRankOf<[Tosa_Weight], [5]>:$weight,
     Tosa_Tensor1D:$bias,
 
     Tosa_IntArrayAttr6:$pad,
@@ -173,7 +173,7 @@
 
   let arguments = (ins
     Tosa_Tensor4D:$input,
-    Tosa_Tensor4D:$weight,
+    4DTensorOf<[Tosa_Weight]>:$weight,
     Tosa_Tensor1D:$bias,
 
     Tosa_IntArrayAttr4:$pad,
@@ -235,7 +235,7 @@
 
   let arguments = (ins
     Tosa_Tensor2D:$input,
-    Tosa_Tensor2D:$weight,
+    2DTensorOf<[Tosa_Weight]>:$weight,
     Tosa_Tensor1D:$bias,
     OptionalAttr<Tosa_ConvOpQuantizationAttr>:$quantization_info
   );
@@ -351,7 +351,7 @@
 
   let arguments = (ins
     Tosa_Tensor4D:$input,
-    Tosa_Tensor4D:$filter,
+    4DTensorOf<[Tosa_Weight]>:$filter,
     Tosa_Tensor1D:$bias,
 
     Tosa_IntArrayAttr4:$out_pad,
@@ -1817,7 +1817,7 @@
   );
 
   let results = (outs
-    Tosa_Tensor_Plus_F64:$output
+    TensorOf<[AnyTypeOf<[Tosa_AnyNumber_Plus_F64, Tosa_Int4]>]>:$output
   );
   let hasFolder = 1;
 }
diff --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaTypesBase.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaTypesBase.td
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaTypesBase.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaTypesBase.td
@@ -41,6 +41,7 @@
 def Tosa_UInt8 : UI<8>;
 def Tosa_UInt16 : UI<16>;
 
+def Tosa_Int4 : I<4>;
 def Tosa_Int8 : I<8>;
 def Tosa_Int16 : I<16>;
 def Tosa_Int32 : I<32>;
@@ -95,10 +96,16 @@
 //===----------------------------------------------------------------------===//
 def Tosa_AnyNumber : AnyTypeOf<[Tosa_Int, Tosa_QuantizedInt, Tosa_Float],
                                "number">;
+
 // Add F64 type support just for tosa::CastOp and tosa::ConstOp
 def Tosa_AnyNumber_Plus_F64 : AnyTypeOf<[Tosa_Int, Tosa_QuantizedInt, Tosa_Float, F64],
                                "number_plus_f64">;
 
+// For weight tensors from tosa::Conv2DOp, tosa::Conv3DOp,
+// tosa::DepthwiseConv2DOp, tosa::TransposeConv2DOp, tosa::FullyConnectedOp
+def Tosa_Weight : AnyTypeOf<[Tosa_Int4, Tosa_Int8,
+                             Tosa_QuantizedInt, Tosa_Float]>;
+
 //===----------------------------------------------------------------------===//
 // Tensor types
 //===----------------------------------------------------------------------===//
@@ -109,6 +116,7 @@
 // Either ranked or unranked tensor of TOSA supported element types.
 def Tosa_Tensor : TensorOf<[Tosa_AnyNumber]>;
 def Tosa_Tensor_Plus_F64 : TensorOf<[Tosa_AnyNumber_Plus_F64]>;
+
 // Must be ranked but no further constraints
 def Tosa_RankedTensor : RankedTensorOf<[Tosa_AnyNumber]>;
 
diff --git a/mlir/test/Dialect/Tosa/invalid.mlir b/mlir/test/Dialect/Tosa/invalid.mlir
--- a/mlir/test/Dialect/Tosa/invalid.mlir
+++ b/mlir/test/Dialect/Tosa/invalid.mlir
@@ -20,13 +20,12 @@
 // -----
 
 func.func @test_conv2d(%arg0: tensor<1x29x29x4xi8>, %arg1: tensor<*xi8>, %arg2: tensor<16xi8>) -> tensor<1x27x27x16xi8> {
-  // expected-error@+1 {{expect a ranked tensor for weight, got <block argument> of type 'tensor<*xi8>' at index: 1}}
+  // expected-error@+1 {{'tosa.conv2d' op operand #1 must be 4D tensor of 4-bit signless integer or 8-bit signless integer or Quint8 type or Qint4 type or Qint8 type or Qint16 type or Qint32 type or 32-bit float or 16-bit float or bfloat16 type values, but got 'tensor<*xi8>'}}
   %0 = "tosa.conv2d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>}
            : (tensor<1x29x29x4xi8>, tensor<*xi8>, tensor<16xi8>) -> tensor<1x27x27x16xi8>
   return %0 : tensor<1x27x27x16xi8>
 }
 
-
 // -----
 
 func.func @test_conv2d(%arg0: tensor<1x29x29x4xi8>, %arg1: tensor<16x3x3x4xi8>, %arg2: tensor<16xi8>) -> tensor<1x27x27x16xi8> {