// CHECK: %[[CONV:.*]] = stablehlo.convolution(%[[QUANT_ARG]], %[[FILTER]]) {{.*}} : (tensor<1x3x3x4x!quant.uniform<i8:f32, {{.*}}>>, tensor<3x3x4x4x!quant.uniform<i8:f32:3, {{.*}}>>) -> tensor<1x3x3x4x!quant.uniform<i8:f32, {{.*}}>>
// CHECK: %[[DEQUANT:.*]] = stablehlo.uniform_dequantize %[[CONV]] : (tensor<1x3x3x4x!quant.uniform<i8:f32, {{.*}}>>) -> tensor<1x3x3x4xf32>

	src = typecheck.Expr(src)
	if dst.Kind() == types.TBLANK || types.Identical(dst, src.Type()) {
		return src
	}

	n := ir.NewConvExpr(nrange.Pos(), ir.OCONV, dst, src)
	n.TypeWord = typeWord
	n.SrcRType = srcRType
	return typecheck.Expr(n)
}

// isMapClear checks if n is of the form:
//
//	for k := range m {
//		delete(m, k)
//	}
//

				reportf(arg.Pos(), "possibly passing Go type with embedded pointer to C")
				break
			}

			// Check for passing the address of a bad type.
			if conv, ok := arg.(*ast.CallExpr); ok && len(conv.Args) == 1 &&
				isUnsafePointer(info, conv.Fun) {
				arg = conv.Args[0]
			}
			if u, ok := arg.(*ast.UnaryExpr); ok && u.Op == token.AND {
				if !typeOKForCgoCall(cgoBaseType(info, u.X), make(map[types.Type]bool)) {

		if types.SimType[src.Kind()] == types.SimType[dst.Kind()] {
			return ir.OCONVNOP, ""
		}
		return ir.OCONV, ""
	}

	// 5. src and dst are both complex types.
	if src.IsComplex() && dst.IsComplex() {
		if types.SimType[src.Kind()] == types.SimType[dst.Kind()] {
			return ir.OCONVNOP, ""
		}
		return ir.OCONV, ""
	}

	// Special case for constant conversions: any numeric

			got := tt.enc.EncodeToString([]byte(p.decoded))
			testEqual(t, "Encode(%q) = %q, want %q", p.decoded, got, tt.conv(p.encoded))
			dst := tt.enc.AppendEncode([]byte("lead"), []byte(p.decoded))
			testEqual(t, `AppendEncode("lead", %q) = %q, want %q`, p.decoded, string(dst), "lead"+tt.conv(p.encoded))
		}
	}
}

func TestEncoder(t *testing.T) {
	for _, p := range pairs {
		bb := &strings.Builder{}

				a.Type = obj.TYPE_MEM
			}
			// fmt.Printf("CONST %d %s\n", a.Offset, obj.Dconv(&emptyProg, 0, a))
			p.expectOperandEnd()
			return
		}
		// fmt.Printf("offset %d \n", a.Offset)
	}

	// Register indirection: (reg) or (index*scale). We are on the opening paren.
	p.registerIndirect(a, prefix)
	// fmt.Printf("DONE %s\n", p.arch.Dconv(&emptyProg, 0, a))

	p.expectOperandEnd()
	return
}

  ASSERT_EQ(status.message(),
            "'optimize_func' field in TP_Optimizer must be set.");
}

TEST(TF_GrapplerItem, NodesToPreserve) {
  GrapplerItem item;
  item.fetch = std::vector<string>{"Conv", "BiasAdd"};
  std::unordered_set<string> nodes_preserved = item.NodesToPreserve();
  TF_GrapplerItem* c_item = reinterpret_cast<TF_GrapplerItem*>(&item);

  int list_total_size = 0;

			return true
		}
		// We may have skipped past one or more OCONVNOPs, so
		// use conv to ensure r is assignable to l (#13263).
		dst := ir.Node(l)
		if loff != 0 || !types.Identical(typ, l.Type()) {
			dst = ir.NewNameOffsetExpr(base.Pos, l, loff, typ)
		}
		s.append(ir.NewAssignStmt(base.Pos, dst, typecheck.Conv(r, typ)))
		return true

	case ir.ONIL:
		return true

	case ir.OLITERAL:

// CHECK: %[[conv:.*]] = "tf.Conv2D"(%[[dq_input]], %[[dq_weight]])
// CHECK: %[[bias:.*]] = "tf.BiasAdd"(%[[conv]], %[[cst_0]]) <{data_format = "NHWC"}>
// CHECK: %[[relu6:.*]] = "tf.Relu6"(%[[bias]])

// -----

// CHECK: %[[cst1:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 1.000000e-01>>, value = dense<1> : tensor<32x3x3x3xi8>}>
// CHECK: %[[conv:.*]] = "tfl.conv_2d"(%arg0, %[[cst1]], %[[cst0]])
// CHECK: return %[[conv]] : tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>
}

// CHECK-LABEL: QuantizeConv2D4Bit