diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml b/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
@@ -1311,6 +1311,104 @@
                 - !ScalarExpression
                   scalar_arg: K
 --- !LinalgOpConfig
+metadata: !LinalgOpMetadata
+  name: conv_2d_nhwc_fhwc
+  cpp_class_name: Conv2DNhwcFhwcOp
+  doc: |-
+    Performs 2-D convolution.
+
+    Layout:
+      * Input: NHWC.
+      * Kernel: FHWC.
+
+    Numeric casting is performed on the operands to the inner multiply, promoting
+    them to the same data type as the accumulator/output.
+  implements:
+  - LinalgConvolutionOpInterface
+structured_op: !LinalgStructuredOpConfig
+  args:
+  - !LinalgOperandDefConfig
+    name: I
+    kind: input_tensor
+    type_var: T1
+    shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10] -> (s0,
+      s1 * s2 + s3 * s4, s5 * s6 + s7 * s8, s9)>
+  - !LinalgOperandDefConfig
+    name: K
+    kind: input_tensor
+    type_var: T2
+    shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10] -> (s10, s3,
+      s7, s9)>
+  - !LinalgOperandDefConfig
+    name: O
+    kind: output_tensor
+    type_var: U
+    shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10] -> (s0,
+      s1, s5, s10)>
+  - !LinalgOperandDefConfig
+    name: strides
+    kind: index_attr
+    index_attr_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10] ->
+      (s2, s6)>
+    default_indices:
+    - 1
+    - 1
+  - !LinalgOperandDefConfig
+    name: dilations
+    kind: index_attr
+    index_attr_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10] ->
+      (s4, s8)>
+    default_indices:
+    - 1
+    - 1
+  indexing_maps: !LinalgIndexingMapsConfig
+    static_indexing_maps:
+    - affine_map<(d0, d1, d2, d3, d4, d5, d6)[s0, s1, s2, s3, s4, s5, s6, s7, s8,
+      s9, s10] -> (d0, d1 * s2 + d4 * s4, d2 * s6 + d5 * s8, d6)>
+    - affine_map<(d0, d1, d2, d3, d4, d5, d6)[s0, s1, s2, s3, s4, s5, s6, s7, s8,
+      s9, s10] -> (d3, d4, d5, d6)>
+    - affine_map<(d0, d1, d2, d3, d4, d5, d6)[s0, s1, s2, s3, s4, s5, s6, s7, s8,
+      s9, s10] -> (d0, d1, d2, d3)>
+  iterator_types:
+  - parallel
+  - parallel
+  - parallel
+  - parallel
+  - reduction
+  - reduction
+  - reduction
+  assignments:
+  - !ScalarAssign
+    arg: O
+    value: !ScalarExpression
+      scalar_fn:
+        kind: binary
+        fn_name: add
+        operands:
+        - !ScalarExpression
+          scalar_arg: O
+        - !ScalarExpression
+          scalar_fn:
+            kind: binary
+            fn_name: mul
+            operands:
+            - !ScalarExpression
+              scalar_fn:
+                kind: type
+                fn_name: cast_signed
+                type_var: U
+                operands:
+                - !ScalarExpression
+                  scalar_arg: I
+            - !ScalarExpression
+              scalar_fn:
+                kind: type
+                fn_name: cast_signed
+                type_var: U
+                operands:
+                - !ScalarExpression
+                  scalar_arg: K
+--- !LinalgOpConfig
 metadata: !LinalgOpMetadata
   name: conv_2d_nhwc_hwcf_q
   cpp_class_name: Conv2DNhwcHwcfQOp
diff --git a/mlir/test/Dialect/Linalg/named-ops.mlir b/mlir/test/Dialect/Linalg/named-ops.mlir
--- a/mlir/test/Dialect/Linalg/named-ops.mlir
+++ b/mlir/test/Dialect/Linalg/named-ops.mlir
@@ -178,6 +178,38 @@
 
 // -----
 
+// CHECK-LABEL: func @conv_2d_nhwc_fhwc
+func.func @conv_2d_nhwc_fhwc(%input: tensor<?x?x?x?xf32>, %filter: tensor<?x?x?x?xf32>, %init: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32> {
+  // CHECK:      %{{.+}} = linalg.conv_2d_nhwc_fhwc
+  // CHECK-SAME:   dilations = dense<1> : tensor<2xi64>
+  // CHECK-SAME:   strides = dense<1> : tensor<2xi64>
+  // CHECK-SAME:   ins(%{{.+}}, %{{.+}} : tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>)
+  // CHECK-SAME:   outs(%{{.+}} : tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
+  %0 = linalg.conv_2d_nhwc_fhwc {dilations = dense<1> : tensor<2xi64>,
+                                 strides = dense<1> : tensor<2xi64>}
+     ins (%input, %filter: tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>)
+    outs (%init: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
+  return %0 : tensor<?x?x?x?xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func @conv_2d_nhwc_fhwc_static
+func.func @conv_2d_nhwc_fhwc_static(%input: tensor<?x128x128x32xf32>, %filter: tensor<64x3x3x32xf32>, %init: tensor<?x126x126x64xf32>) -> tensor<?x126x126x64xf32> {
+  // CHECK:      %{{.+}} = linalg.conv_2d_nhwc_fhwc
+  // CHECK-SAME:   dilations = dense<1> : tensor<2xi64>
+  // CHECK-SAME:   strides = dense<1> : tensor<2xi64>
+  // CHECK-SAME:   ins(%{{.+}}, %{{.+}} : tensor<?x128x128x32xf32>, tensor<64x3x3x32xf32>)
+  // CHECK-SAME:   outs(%{{.+}} : tensor<?x126x126x64xf32>) -> tensor<?x126x126x64xf32>
+  %0 = linalg.conv_2d_nhwc_fhwc {dilations = dense<1> : tensor<2xi64>,
+                                 strides = dense<1> : tensor<2xi64>}
+     ins (%input, %filter: tensor<?x128x128x32xf32>, tensor<64x3x3x32xf32>)
+    outs (%init: tensor<?x126x126x64xf32>) -> tensor<?x126x126x64xf32>
+  return %0 : tensor<?x126x126x64xf32>
+}
+
+// -----
+
 // CHECK-LABEL: func @conv_2d_nhwc_hwcf
 func.func @conv_2d_nhwc_hwcf(%input: memref<?x?x?x?xf32>, %filter: memref<?x?x?x?xf32>, %output: memref<?x?x?x?xf32>) {
   // CHECK:      linalg.conv_2d_nhwc_hwcf