[PTQ][OV] Sequential models support for Engine by TensorCollectorAdapter #16
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@alexsu52, @KodiaqQ, @l-bat, @kshpv, @andrey-churkin |
daniil-lyakhov
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| if isinstance(aggregator, ShapeAggregator): | ||
| x = self._tensor_processor.unstack(x, axis=0)[0] |
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This is needed for bias correction algo: it expects not stacked tensor shape for input creation
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| new_params = {"reduction_shape": self._stack_axis, "keepdims": False} | ||
| if not all(k in kwargs for k in new_params): | ||
| return per_element_result |
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Now special reducers are filtered by this ugly filter
TensorReducerSequence Reducer adapter inside reducer TensorCollectorAdapter
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Changes
Sequential dataset with correspondent changes in engine in OV is presented: now user can specify two functions:
** get_tokens_from_sequence_func
** fill_sequential_inputs_fn
to infer sequential a model
New TensorCollectorAdapters are presented: now TensorAggregator can alter logic of statistic collection by specifying rules for reduction and aggregation
Reason for changes
Related tickets
110654
Tests
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