func.return %0 : tensor<?xf32>
}

//===----------------------------------------------------------------------===//
// tf.UniformQuantizedConvolutionHybrid legalization
//===----------------------------------------------------------------------===//

// -----

// CHECK-LABEL: func @uniform_quantized_convolution_hybrid

  %filter_zp = "tf.Const"() { value = dense<0> : tensor<i32> } : () -> tensor<i32>
  %quant_filter = "tf.Cast"(%filter) {} : (tensor<3x3x10x20xi8>) -> tensor<3x3x10x20x!tf_type.qint8>
  %0 = "tf.UniformQuantizedConvolutionHybrid"(
    %input, %quant_filter, %filter_scale, %filter_zp
  ) {
    Tin = "tfdtype$DT_QINT8", Tout = "tfdtype$DT_FLOAT",
    attr_map = "", batch_group_count = 1 : i64,

          self._contains_op(
              output_graphdef, 'UniformQuantizedConvolutionHybrid'
          )
      )
      self.assertFalse(self._contains_op(output_graphdef, 'Conv2D'))
      if enable_per_channel_quantization:
        self.assertTrue(
            self._contains_op(
                output_graphdef,
                'UniformQuantizedConvolutionHybrid',
                'rhs_quantization_axis',

  TF_DerivedResultTypeAttr Tout = TF_DerivedResultTypeAttr<0>;

  let hasVerifier = 1;
}

def TF_UniformQuantizedConvolutionHybridOp : TF_Op<"UniformQuantizedConvolutionHybrid", [Pure]> {
  let summary = [{
Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`.
  }];

  let description = [{