merge_fusion_with_dequantize: bool,
  ):
    lhs_dim_size, rhs_dim_size = dim_sizes
    input_shape = (*lhs_dim_size,)
    filter_shape = (*rhs_dim_size,)
    static_input_shape = [dim if dim is not None else 2 for dim in input_shape]
    model = self._create_matmul_model(
        input_shape,
        filter_shape,
        self._input_saved_model_path,
        bias_fn,
        activation_fn,
    )

      %1 = stablehlo.get_dimension_size %0, dim = 0 : (tensor<?x3xf32>) -> tensor<i32>
      %2 = stablehlo.reshape %1 : (tensor<i32>) -> tensor<1xi32>
      %3 = stablehlo.concatenate %2, %cst_0, dim = 0 : (tensor<1xi32>, tensor<1xi32>) -> tensor<2xi32>

foreach actFnPair = [[TFL_ReluOp, TFL_AF_Relu],
                     [TFL_Relu6Op, TFL_AF_Relu6],
                     [TFL_Relu1Op, TFL_AF_Relu1]] in {
  defm : FuseActFnIntoConvOpPat<!cast<Op>(actFnPair[0]), !cast<ConstantStrAttr>(actFnPair[1])>;
  defm : FuseActFnIntoPoolOpPat<!cast<Op>(actFnPair[0]), !cast<ConstantStrAttr>(actFnPair[1])>;
}

class CanFuseConvOrDepthwiseConv<string is_depthwise> : Constraint<

  %0 = "tf.Squeeze"(%arg0) {T = f32, _output_shapes = ["tfshape$dim { size: 4 } dim { size: 64 } dim { size: 64 }"], device = "", squeeze_dims = []} : (tensor<4x64x64x1xf32>) -> tensor<4x64x64xf32>

	if len(st.str) == 0 {
		st.fail("missing array dimension")
	}

	var dim AST
	if st.str[0] == '_' {
		dim = &Name{Name: ""}
	} else if isDigit(st.str[0]) {
		i := 1
		for len(st.str) > i && isDigit(st.str[i]) {
			i++
		}
		dim = &Name{Name: st.str[:i]}
		st.advance(i)
	} else {
		dim = st.expression()
	}

	if len(st.str) == 0 || st.str[0] != '_' {

		tmpl, err := New("delims").Delims(left, right).Parse(text)
		if err != nil {
			t.Fatalf("delim %q text %q parse err %s", left, text, err)
		}
		var b = new(strings.Builder)
		err = tmpl.Execute(b, value)
		if err != nil {
			t.Fatalf("delim %q exec err %s", left, err)
		}
		if b.String() != hello+trueLeft {
			t.Errorf("expected %q got %q", hello+trueLeft, b.String())
		}

		tmpl, err := New("delims").Delims(left, right).Parse(text)
		if err != nil {
			t.Fatalf("delim %q text %q parse err %s", left, text, err)
		}
		var b = new(strings.Builder)
		err = tmpl.Execute(b, value)
		if err != nil {
			t.Fatalf("delim %q exec err %s", left, err)
		}
		if b.String() != hello+trueLeft {
			t.Errorf("expected %q got %q", hello+trueLeft, b.String())
		}

    if (!out_size_ty.hasRank() || out_size_ty.getRank() != 1 ||
        out_size_ty.getShape()[0] != 2) {
      return failure();
    }

    // Extract the output width / height dim size.
    int out_height_constant = -1;
    int out_width_constant = -1;
    DenseIntElementsAttr out_size_cst;
    if (matchPattern(out_size, m_Constant(&out_size_cst))) {

	customStorageLock sync.Mutex
	// customStorage contains a crdStorageMap
	// atomic.Value has a very good read performance compared to sync.RWMutex
	// see https://gist.github.com/dim/152e6bf80e1384ea72e17ac717a5000a
	// which is suited for most read and rarely write cases
	customStorage atomic.Value

	crdLister listers.CustomResourceDefinitionLister

	delegate          http.Handler

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