diff --git a/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td b/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
index bd9f968f433..5b6e9562e48 100644
--- a/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
+++ b/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
@@ -1736,6 +1736,146 @@ tf.cumsum([a, b, c], exclusive=True, reverse=True)  # => [b + c, c, 0]
   TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<1>;
 }
 
+def TF_DecodeAndCropJpegOp : TF_Op<"DecodeAndCropJpeg", [NoSideEffect]> {
+  let summary = "Decode and Crop a JPEG-encoded image to a uint8 tensor.";
+
+  let description = [{
+The attr `channels` indicates the desired number of color channels for the
+decoded image.
+
+Accepted values are:
+
+*   0: Use the number of channels in the JPEG-encoded image.
+*   1: output a grayscale image.
+*   3: output an RGB image.
+
+If needed, the JPEG-encoded image is transformed to match the requested number
+of color channels.
+
+The attr `ratio` allows downscaling the image by an integer factor during
+decoding.  Allowed values are: 1, 2, 4, and 8.  This is much faster than
+downscaling the image later.
+
+
+It is equivalent to a combination of decode and crop, but much faster by only
+decoding partial jpeg image.
+  }];
+
+  let arguments = (ins
+    TF_StrTensor:$contents,
+    I32Tensor:$crop_window,
+
+    DefaultValuedAttr<I64Attr, "0">:$channels,
+    DefaultValuedAttr<I64Attr, "1">:$ratio,
+    DefaultValuedAttr<BoolAttr, "true">:$fancy_upscaling,
+    DefaultValuedAttr<BoolAttr, "false">:$try_recover_truncated,
+    DefaultValuedAttr<F32Attr, "1.0f">:$acceptable_fraction,
+    StrAttr:$dct_method
+  );
+
+  let results = (outs
+    TF_Uint8Tensor:$image
+  );
+}
+
+def TF_DecodeGifOp : TF_Op<"DecodeGif", [NoSideEffect]> {
+  let summary = "Decode the frame(s) of a GIF-encoded image to a uint8 tensor.";
+
+  let description = [{
+GIF images with frame or transparency compression are not supported.
+On Linux and MacOS systems, convert animated GIFs from compressed to
+uncompressed by running:
+
+    convert $src.gif -coalesce $dst.gif
+
+This op also supports decoding JPEGs and PNGs, though it is cleaner to use
+`tf.io.decode_image`.
+  }];
+
+  let arguments = (ins
+    TF_StrTensor:$contents
+  );
+
+  let results = (outs
+    TF_Uint8Tensor:$image
+  );
+}
+
+def TF_DecodeJpegOp : TF_Op<"DecodeJpeg", [NoSideEffect]> {
+  let summary = "Decode a JPEG-encoded image to a uint8 tensor.";
+
+  let description = [{
+The attr `channels` indicates the desired number of color channels for the
+decoded image.
+
+Accepted values are:
+
+*   0: Use the number of channels in the JPEG-encoded image.
+*   1: output a grayscale image.
+*   3: output an RGB image.
+
+If needed, the JPEG-encoded image is transformed to match the requested number
+of color channels.
+
+The attr `ratio` allows downscaling the image by an integer factor during
+decoding.  Allowed values are: 1, 2, 4, and 8.  This is much faster than
+downscaling the image later.
+
+
+This op also supports decoding PNGs and non-animated GIFs since the interface is
+the same, though it is cleaner to use `tf.io.decode_image`.
+  }];
+
+  let arguments = (ins
+    TF_StrTensor:$contents,
+
+    DefaultValuedAttr<I64Attr, "0">:$channels,
+    DefaultValuedAttr<I64Attr, "1">:$ratio,
+    DefaultValuedAttr<BoolAttr, "true">:$fancy_upscaling,
+    DefaultValuedAttr<BoolAttr, "false">:$try_recover_truncated,
+    DefaultValuedAttr<F32Attr, "1.0f">:$acceptable_fraction,
+    StrAttr:$dct_method
+  );
+
+  let results = (outs
+    TF_Uint8Tensor:$image
+  );
+}
+
+def TF_DecodePngOp : TF_Op<"DecodePng", [NoSideEffect]> {
+  let summary = "Decode a PNG-encoded image to a uint8 or uint16 tensor.";
+
+  let description = [{
+The attr `channels` indicates the desired number of color channels for the
+decoded image.
+
+Accepted values are:
+
+*   0: Use the number of channels in the PNG-encoded image.
+*   1: output a grayscale image.
+*   3: output an RGB image.
+*   4: output an RGBA image.
+
+If needed, the PNG-encoded image is transformed to match the requested number
+of color channels.
+
+This op also supports decoding JPEGs and non-animated GIFs since the interface
+is the same, though it is cleaner to use `tf.io.decode_image`.
+  }];
+
+  let arguments = (ins
+    TF_StrTensor:$contents,
+
+    DefaultValuedAttr<I64Attr, "0">:$channels
+  );
+
+  let results = (outs
+    TensorOf<[TF_Uint16, TF_Uint8]>:$image
+  );
+
+  TF_DerivedResultTypeAttr dtype = TF_DerivedResultTypeAttr<0>;
+}
+
 def TF_DepthToSpaceOp : TF_Op<"DepthToSpace", [NoSideEffect]> {
   let summary = "DepthToSpace for tensors of type T.";
 
diff --git a/tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td b/tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td
index 80a2b1925e6..cb17341cefd 100644
--- a/tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td
+++ b/tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td
@@ -129,9 +129,16 @@ def TF_I32Or64 : SignlessIntOfWidths<[32, 64]>;
 def TF_I32OrI64Tensor : TensorOf<[TF_I32Or64]>;
 
 def TF_Uint8 : UI<8>;
+def TF_Uint8Tensor : TensorOf<[TF_Uint8]>;
+
 def TF_Uint16 : UI<16>;
+def TF_Uint16Tensor : TensorOf<[TF_Uint16]>;
+
 def TF_Uint32 : UI<32>;
+def TF_Uint32Tensor : TensorOf<[TF_Uint32]>;
+
 def TF_Uint64 : UI<64>;
+def TF_Uint64Tensor : TensorOf<[TF_Uint64]>;
 
 // Any unsigned integer type
 def TF_UInt : UnsignedIntOfWidths<[8, 16, 32, 64]>;