code: def original_mod_let_bound():
      return tvm.relay.parse(
          """
          #[version = "0.0.5"]
          def @main(%x0 : Tensor[(1600, 768), float16], %x3 : Tensor[(600, 32, 64), float16]) -> (Tensor[(1600, 2304), float16], Tensor[(600, 32, 32), float16]) {
            let %f = fn(%y_0_i0: Tensor[(1600, 768), float16], %y_0_i1: Tensor[(2304, 768), float16], %y_0_i2: Tensor[(2304), float16],
                        Inline=1, Compiler="cutlass", global_symbol="tvmgen_default_cutlass_main_0", Primitive=1) -> Tensor[(1600, 2304), float16] {
              %4 = fn (%FunctionVar_0_0: Tensor[(1600, 768), float16], %FunctionVar_0_1: Tensor[(2304, 768), float16], %FunctionVar_0_2: Tensor[(2304), float16],
                       PartitionedFromPattern="nn.dense_add_", Composite="cutlass.dense_bias") -> Tensor[(1600, 2304), float16] {
                %5 = nn.dense(%FunctionVar_0_0, %FunctionVar_0_1, units=2304);
                add(%5, %FunctionVar_0_2)
              };
              %4(%y_0_i0, %y_0_i1, %y_0_i2)
            };
            %1 = %f(%x0, meta[relay.Constant][0], meta[relay.Constant][1]);
            %2 = fn(%y_3_i0: Tensor[(600, 32, 64), float16], %y_3_i1: Tensor[(600, 32, 64), float16],
                    Inline=1, Compiler="cublas", global_symbol="tvmgen_default_cublas_main_3", Primitive=1) -> Tensor[(600, 32, 32), float16] {
              %6 = fn (%FunctionVar_0_01: Tensor[(600, 32, 64), float16], %FunctionVar_0_11: Tensor[(600, 32, 64), float16],
                       PartitionedFromPattern="nn.batch_matmul_", Composite="cublas.batch_matmul") -> Tensor[(600, 32, 32), float16] {
                nn.batch_matmul(%FunctionVar_0_01, %FunctionVar_0_11, out_dtype="float16", transpose_b=True)
              };
              %6(%y_3_i0, %y_3_i1)
            };
            %3 = %2(%x3, meta[relay.Constant][2]);
            (%1, %3)
          }
          """,
          "from_string",
          None,
          metatable,
      )
  
file_path: tvm/tests/python/relay/transform/test_compiler_function_utils.py
imports: import tvm
  import tvm.testing
  import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: original_mod_let_bound() and returns: tvm