code: def test_fake_quantize_transposeconv():
      for out_dtype in ["int8", "uint8"]:
          x = relay.var("x", shape=[1, 3, 224, 224], dtype="int8")
          w = relay.var("w", shape=[3, 16, 5, 5], dtype="int8")
          one = relay.const(1.0)
          zero = relay.const(0)
  
          op = relay.op.nn.conv2d_transpose(
              relay.qnn.op.dequantize(x, relay.const(2.0), zero),
              relay.qnn.op.dequantize(w, relay.const(0.5), zero),
              kernel_size=[5, 5],
              data_layout="NCHW",
              kernel_layout="IOHW",
          )
          op = relay.qnn.op.quantize(op, one, zero, out_dtype=out_dtype)
  
          x_np = np.random.randint(
              -128, 127, size=[1, 3, 224, 224], dtype="int8"
          )
          w_np = np.random.randint(
              -128, 127, size=[3, 16, 5, 5], dtype="int8"
          )
  
          compare_fq_to_int(op, [x_np, w_np])
  
imports: import numpy
  import pytest
  import tvm
  import tvm.testing
  from tvm import relay
  from tvm.relay.transform import fake_quantization_to_integer
label_desc: Use image node_id 4 for calling a global function with example usage: test_fake_quantize_transposeconv() without return types