コード例 #1
0
    def test_set_eval_mode(self, mock_eval, mock_call):
        """ Make sure that evaluation is done in evaluation mode. """
        mock_mgr = MagicMock()
        mock_mgr.attach_mock(mock_eval, 'eval')
        mock_mgr.attach_mock(mock_call, 'call')

        evaluator = Evaluator()
        evaluator.evaluate(self.seq2seq, self.dataset)

        expected_calls = [call.eval()] + \
            self.dataset.num_batches(evaluator.batch_size) * [call.call(ANY, ANY, volatile=ANY)]
        self.assertEquals(expected_calls, mock_mgr.mock_calls)
コード例 #2
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    def test_set_eval_mode(self, mock_eval, mock_call):
        """ Make sure that evaluation.txt is done in evaluation.txt mode. """
        mock_mgr = MagicMock()
        mock_mgr.attach_mock(mock_eval, 'eval')
        mock_mgr.attach_mock(mock_call, 'call')

        evaluator = Evaluator(batch_size=64)
        with patch('seq2seq.evaluator.evaluator.torch.stack', return_value=None), \
                patch('seq2seq.loss.NLLLoss.eval_batch', return_value=None):
            evaluator.evaluate(self.seq2seq, self.dataset)

        num_batches = int(math.ceil(len(self.dataset) / evaluator.batch_size))
        expected_calls = [call.eval()] + num_batches * [call.call(ANY, ANY, ANY)]
        self.assertEquals(expected_calls, mock_mgr.mock_calls)
コード例 #3
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    def test_set_eval_mode(self, mock_eval, mock_call):
        """ Make sure that evaluation is done in evaluation mode. """
        mock_mgr = MagicMock()
        mock_mgr.attach_mock(mock_eval, 'eval')
        mock_mgr.attach_mock(mock_call, 'call')

        evaluator = Evaluator()
        with patch('machine.evaluator.evaluator.torch.stack', return_value=None), \
                patch('machine.metrics.WordAccuracy.eval_batch', return_value=None), \
                patch('machine.metrics.WordAccuracy.eval_batch', return_value=None), \
                patch('machine.loss.NLLLoss.eval_batch', return_value=None):
            evaluator.evaluate(self.seq2seq, self.data_iterator,
                               trainer.get_batch_data)

        num_batches = len(self.data_iterator)
        expected_calls = [call.eval()] + num_batches * \
            [call.call(ANY, ANY, ANY)]
        self.assertEqual(expected_calls, mock_mgr.mock_calls)
コード例 #4
0
ファイル: test_evaluator.py プロジェクト: YannDubs/machine
            param.data.uniform_(-0.08, 0.08)

    @patch.object(Seq2seq, '__call__', return_value=(
        [], None, dict(inputs=[], length=[10] * 64, sequence=MagicMock())))
    @patch.object(Seq2seq, 'eval')
    def test_set_eval_mode(self, mock_eval, mock_call):
        """ Make sure that evaluation is done in evaluation mode. """
        mock_mgr = MagicMock()
        mock_mgr.attach_mock(mock_eval, 'eval')
        mock_mgr.attach_mock(mock_call, 'call')

        evaluator = Evaluator(batch_size=64)
<<<<<<< HEAD
        with patch('seq2seq.evaluator.evaluator.torch.stack', return_value=None), \
             patch('seq2seq.metrics.WordAccuracy.eval_batch', return_value=None), \
             patch('seq2seq.loss.NLLLoss.eval_batch', return_value=None):
            evaluator.evaluate(self.seq2seq, self.dataset, trainer.get_batch_data)
=======
        with patch('machine.evaluator.evaluator.torch.stack', return_value=None), \
                patch('machine.metrics.WordAccuracy.eval_batch', return_value=None), \
                patch('machine.metrics.WordAccuracy.eval_batch', return_value=None), \
                patch('machine.loss.NLLLoss.eval_batch', return_value=None):
            evaluator.evaluate(self.seq2seq, self.dataset,
                               trainer.get_batch_data)
>>>>>>> upstream/master

        num_batches = int(math.ceil(len(self.dataset) / evaluator.batch_size))
        expected_calls = [call.eval()] + num_batches * \
            [call.call(ANY, ANY, ANY)]
        self.assertEquals(expected_calls, mock_mgr.mock_calls)
コード例 #5
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def editor(vim):
    mockeditor = Editor(vim)
    assert vim.mock_calls == [call.eval("has('nvim')")]

    vim.reset_mock()  # Clear above constructor vim calls from call list
    return mockeditor