fdb22c8610
* Add opset-13 bitwise implementation * Improvements in test * Add transformation BitwiseOps->LogicalOps for bool * Improve existing tests to better tests dtypes * Disable transformatiions for supported bitwise ops * Improvebitwise test inputs * Update src/common/transformations/src/transformations/op_conversions/convert_bitwise_to_logical_bool.cpp Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com> * Update src/common/transformations/src/transformations/op_conversions/convert_bitwise_to_logical_bool.cpp Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com> * Update src/common/transformations/src/transformations/op_conversions/convert_bitwise_to_logical_bool.cpp Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com> * Update src/common/transformations/src/transformations/op_conversions/convert_bitwise_to_logical_bool.cpp Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com> * Update to REGISETR_PASS --------- Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com>
79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import pytest
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import torch
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from pytorch_layer_test_class import PytorchLayerTest
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class TestAnd(PytorchLayerTest):
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def _prepare_input(self):
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return self.input_data
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def create_model_tensor_input(self):
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class aten_and_tensor(torch.nn.Module):
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def __init__(self) -> None:
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super().__init__()
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def forward(self, tensor_a, tensor_b):
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return tensor_a & tensor_b
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ref_net = None
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return aten_and_tensor(), ref_net, "aten::__and__"
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def create_model_bool_input(self):
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class aten_and_bool(torch.nn.Module):
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def __init__(self) -> None:
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super().__init__()
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def forward(self, bool_a: bool, bool_b: bool):
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return bool_a & bool_b
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ref_net = None
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return aten_and_bool(), ref_net, "aten::__and__"
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def create_model_int_input(self):
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class aten_and_int(torch.nn.Module):
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def __init__(self) -> None:
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super().__init__()
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def forward(self, int_a: int, int_b: int):
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return int_a & int_b
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ref_net = None
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return aten_and_int(), ref_net, "aten::__and__"
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_and_tensor(self, ie_device, precision, ir_version):
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self.input_data = (
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np.array([True, False, False], dtype=np.bool_),
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np.array([True, True, False], dtype=np.bool_),
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)
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self._test(*self.create_model_tensor_input(), ie_device, precision, ir_version)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_and_bool(self, ie_device, precision, ir_version):
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self.input_data = (np.array(True, dtype=np.bool_), np.array(True, dtype=np.bool_))
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self._test(*self.create_model_bool_input(), ie_device, precision, ir_version)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_and_int(self, ie_device, precision, ir_version):
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self.input_data = (np.array(3, dtype=np.int32), np.array(4, dtype=np.int32))
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self._test(*self.create_model_int_input(), ie_device, precision, ir_version)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_and_tensor(self, ie_device, precision, ir_version):
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self.input_data = (np.array([3, 5, 8], dtype=np.int32), np.array([7, 11, 2], dtype=np.int32))
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self._test(
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*self.create_model_tensor_input(), ie_device, precision, ir_version, freeze_model=False, trace_model=True
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)
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