code: def test_tflite_fully_connected(
      accel_type,
      ifm_shape,
      ofm_channels,
      use_bias,
      activation_function,
  ):
      np.random.seed(0)
  
      @tf.function
      def fully_connected(x):
          bias_shape = ofm_channels
          bias = tf.constant(
              np.random.uniform(size=bias_shape), dtype=tf.float32
          )
          w = tf.constant(
              np.random.uniform(size=[ifm_shape[1], ofm_channels]),
              dtype=tf.float32,
          )
          x = tf.matmul(x, w)
          if use_bias:
              x = tf.nn.bias_add(x, bias)
          if activation_function:
              x = tf.nn.relu(x)
          return x
  
      infra.compare_tvm_with_tflite(
          fully_connected,
          [ifm_shape],
          accel_type,
          enable_cascader=is_u55_accel_type(accel_type),
      )
  
imports: import pytest
  import numpy
  import tflite.Model
  import tvm
  import tensorflow
  from tvm import relay
  from tvm.relay.backend.contrib.ethosu import util
  from tvm.relay.op.contrib.ethosu import partition_for_ethosu
  from tvm.testing.aot import generate_ref_data
  from .None import infra
label_desc: Use image node_id 49 for calling a global function with example usage: test_tflite_fully_connected(accel_type, ifm_shape, ofm_channels, use_bias, activation_function) and returns: x