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55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
"""Tests for the quantized array/tensors."""
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import numpy
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import pytest
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from concrete.quantization import QuantizedArray
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N_BITS_ATOL_TUPLE_LIST = [
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(32, 10 ** -2),
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(28, 10 ** -2),
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(20, 10 ** -2),
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(16, 10 ** -1),
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(8, 10 ** -0),
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(4, 10 ** -0),
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]
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@pytest.mark.parametrize(
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"n_bits, atol",
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[pytest.param(n_bits, atol) for n_bits, atol in N_BITS_ATOL_TUPLE_LIST],
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)
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@pytest.mark.parametrize("is_signed", [pytest.param(True), pytest.param(False)])
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@pytest.mark.parametrize("values", [pytest.param(numpy.random.randn(2000))])
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def test_quant_dequant_update(values, n_bits, atol, is_signed, check_array_equality):
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"""Test the quant and dequant function."""
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quant_array = QuantizedArray(n_bits, values, is_signed)
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qvalues = quant_array.quant()
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# Quantized values must be contained between 0 and 2**n_bits
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assert numpy.max(qvalues) <= 2 ** (n_bits) - 1 - quant_array.offset
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assert numpy.min(qvalues) >= -quant_array.offset
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# Dequantized values must be close to original values
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dequant_values = quant_array.dequant()
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# Check that all values are close
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assert numpy.isclose(dequant_values, values, atol=atol).all()
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# Test update functions
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new_values = numpy.array([0.3, 0.5, -1.2, -3.4])
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new_qvalues_ = quant_array.update_values(new_values)
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# Make sure the shape changed for the qvalues
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assert new_qvalues_.shape != qvalues.shape
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new_qvalues = numpy.array([1, 4, 7, 29])
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new_values_updated = quant_array.update_qvalues(new_qvalues)
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# Make sure that we can see at least one change.
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assert not numpy.array_equal(new_qvalues, new_qvalues_)
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assert not numpy.array_equal(new_values, new_values_updated)
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# Check that the __call__ returns also the qvalues.
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check_array_equality(quant_array(), new_qvalues)
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