986e3c0a00677355c1edbd89a959264fa0aea1c4,test/quantization/test_numeric_suite_fx.py,TestFXNumericSuiteCoreAPIsModels,test_sparsenn_compare_activations,#TestFXNumericSuiteCoreAPIsModels#,989

Before Change

            sparse_nn(idx, offsets, x)

            // convert
            sparse_nn_q = copy.deepcopy(sparse_nn)
            sparse_nn_q.dense_top = convert_fx(sparse_nn_q.dense_top)

            // test out compare activations API
            sparse_nn.dense_top, sparse_nn_q.dense_top = add_loggers(
                "fp32_prepared", sparse_nn.dense_top, "int8", sparse_nn_q.dense_top, OutputLogger,
                should_log_inputs=should_log_inputs)

            // calibrate
            sparse_nn(idx, offsets, x)
            sparse_nn_q(idx, offsets, x)

After Change

            idx = torch.LongTensor([1, 2, 4, 5, 4, 3, 2, 9])
            offsets = torch.LongTensor([0, 4])
            x = torch.randn(2, 4)
            self._test_match_activations(
                sparse_nn, (idx, offsets, x),
                results_len=4,
                should_log_inputs=should_log_inputs)

    @skipIfNoFBGEMM
    def test_sparsenn_shadow(self):
        for should_log_inputs in (True, False):

Instances