// RUN: tf-quant-opt %s -split-input-file -quant-preprocess-op | FileCheck %s

module {
  // For UniformQuantized depthwise convolution, tensor shape should have
  // transformed from [H,W,C,M] to [H,W,1,CxM],
  func.func @depthwise_conv(%arg0: tensor<1x3x4x3xf32>) -> (tensor<*xf32>) {
    %cst_0 = "tf.Const"() {value = dense<0.000000e+00> : tensor<6xf32>} : () -> tensor<6xf32>

module {
  // For XLA weight-only per-channel depthwise convolution, tensor shape should have
  // transformed from [H,W,C,M] to [H,W,1,CxM],
  func.func @depthwise_conv(%arg0: tensor<1x3x4x3xf32>) -> (tensor<*xf32>) {

                "non-broadcastable operands";
      });
    }
    filter_value = filter.getValue();
    mul_value = multiplier.getValue();
    // In MHLO, Conv filter is in HWIO format, Depthwise conv filter is in HW1O
    // format and backprop input conv filter is in HWOI format.
    // Only fuses multiplier if all dimensions other than the out channel
    // dimension are equal to 1.