class_docstr: Test large corner cases for tensorflow.
class_docstr_tok: ["Test","large","corner","cases","for","tensorflow","."]
docstr: Test that CNOT with large batched states works as expected.
docstr_tok: ["Test","that","CNOT","with","large","batched","states","works","as","expected","."]
code: def test_cnot_large_batched_state_tf(self):
      """Test that CNOT with large batched states works as expected."""
      import tensorflow as tf
  
      dev = qml.device("default.qubit", wires=8)
  
      @qml.qnode(dev, interface="tf")
      def ancillary_qcnn_circuit(inputs):
          qml.AmplitudeEmbedding(
              features=inputs, wires=range(4), normalize=True
          )
          qml.CNOT(wires=[0, 1])
          qml.PauliZ(1)
          qml.Toffoli(wires=[0, 2, 4])
          qml.Toffoli(wires=[0, 2, 5])
          qml.Toffoli(wires=[0, 2, 6])
          qml.Toffoli(wires=[0, 2, 7])
          return [qml.expval(qml.PauliZ(i)) for i in range(4, 8)]
  
      batch_size = 3
      params = np.random.rand(batch_size, 16)
      result = ancillary_qcnn_circuit(tf.Variable(params))
      assert qml.math.shape(result) == (4, batch_size)
  
imports: from functools import reduce
  import pytest
  import numpy
  from scipy.stats import unitary_group
  import pennylane
  from pennylane.operation import _UNSET_BATCH_SIZE, Operation
  from pennylane.devices.qubit.apply_operation import apply_operation, apply_operation_einsum, apply_operation_tensordot
label_desc: Use image node_id 2 for calling the TestLargeTFCornerCases obj's underlying member method code with example usage: obj.test_cnot_large_batched_state_tf() and returns: unknown