(TFL_DequantizeOp
              (TFL_QuantizeOp (TF_ReshapeOp $input, $shape),
              (UpdateShapeWithAxis<3> $qtype, $old_value))),
  [(UsedBy<"DepthwiseConv2D"> $old_value),
   (CanUpdateShapeWithAxis<3> $qtype, $old_value)],
  [], (addBenefit 10)>;

// The axis is set to 3, because this transpose is from the legalization of

      attr_map = "strides:0,use_cudnn_on_gpu:1,padding:2,explicit_paddings:3,dilations:4"
    } : (tensor<*xi32>, tensor<*xi32>) -> tensor<*xi32>
    func.return %5 : tensor<*xi32>
  }

  // DepthwiseConv2D with (simulated) int32 accumulation.
  func.func private @internal_depthwise_conv2d_fn(
                         %input : tensor<*xi8>, %filter : tensor<*xi8>,

    // Disable quantization for the DepthwiseConv since it has no benefits in
    // the XLA opset.
    if (function_name.contains("depthwise_conv2d")) {
      return absl::InternalError(
          "DepthwiseConv2D doesn't get any benefit of quantization in XLA.");
    } else if (function_name.contains("conv2d")) {
      // For Conv2D, the channel dimension must be static to calculate the
      // feature group count.

}

func.func @depthwiseConv2D(tensor<256x32x32x3xf32>, tensor<3x3x3x4xf32>, tensor<256x3x32x32xf32>) -> (tensor<256x30x30x12xf32>, tensor<256x12x30x30xf32>, tensor<256x30x30x12xf32>, tensor<256x30x30x12xf32>) {

        /*depth_multiplier=*/rewriter.getI32IntegerAttr(multiplier));
  }

 private:
  /// Legalize the given filter by converting it from TensorFlow filter data
  /// format to TFLite DepthwiseConv2D op filter data format and return Value
  /// for the converted filter.  TensorFlow filter data format is
  /// [filter_height, filter_width, in_channels, channel_multiplier] and TFLite

        collisions across summary types.

*   When running on GPU (with cuDNN version 7.6.3 or
    later),`tf.nn.depthwise_conv2d` backprop to `filter` (and therefore also
    `tf.keras.layers.DepthwiseConv2D`) now operate deterministically (and
    `tf.errors.UnimplementedError` is no longer thrown) when op-determinism has
    been enabled via `tf.config.experimental.enable_op_determinism`. This closes