class_docstr: Unit tests for the pennylane.qnn.torch.TorchLayer class.
class_docstr_tok: ["Unit","tests","for","the","pennylane.qnn.torch.TorchLayer","class","."]
docstr: Test if weights are initialized according to the uniform distribution in [0, 2 pi]
docstr_tok: ["Test","if","weights","are","initialized","according","to","the","uniform","distribution","in","[","0",",","2","pi","]"]
code: def test_nonspecified_init(
      self, get_circuit, monkeypatch
  ):  # pylint: disable=no-self-use
      """Test if weights are initialized according to the uniform distribution in [0, 2 pi]"""
      c, w = get_circuit
  
      uniform_ = mock.MagicMock(return_value=torch.Tensor(1))
      with monkeypatch.context() as m:
          m.setattr(torch.nn.init, "uniform_", uniform_)
          TorchLayer(c, w)
          kwargs = uniform_.call_args[1]
          assert kwargs["b"] == 2 * math.pi
  
imports: from unittest import mock
  import math
  from collections import defaultdict
  import numpy
  import pytest
  import pennylane
  from pennylane.qnn.torch import TorchLayer
label_desc: Use image node_id 7 for calling the TestTorchLayer obj's underlying member method code with example usage: obj.test_nonspecified_init(get_circuit, monkeypatch) without return types