// Ternary ops patterns.
//===----------------------------------------------------------------------===//
// Multi-pattern consisting of matching stand-alone convolution op followed by
// activation op.
multiclass FuseActFnIntoConvOpPat<Op ActFnOp, ConstantStrAttr ActFnAttr> {
  def FuseActivationFuncWithConv#ActFnOp#ActFnAttr : Pat<
    (ActFnOp (TFL_Conv2DOp:$conv_out $input, $filter, $bias, $h_factor,

// dynamic batch dimension is properly quantized.

// Note that this checks for identical condition as
// quantize_conv_with_bias_dynamic_fn, omitting stablehlo.maximum.
// This is because activation clipping which includes 0.0f can be simply
// omitted from the graph as the lifted function's out_scale and out_zp are
// already calculated based on the clipped distribution.