87e714eb5c
* Add support for concatenation in Loop * Apply suggestions from code review * Fix win build * Fix issues with propagation shapes and types in Loop * Fix einsum * Set type and shape of count in frontend
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import pytest
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from pytorch_layer_test_class import PytorchLayerTest
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class TestBool(PytorchLayerTest):
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def _prepare_input(self):
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import numpy as np
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return (np.random.randint(0, 10, 1).astype(np.int32),)
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def create_model(self, input_type):
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import torch
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class prim_bool(torch.nn.Module):
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def __init__(self, input_type):
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super(prim_bool, self).__init__()
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self.forward = self.forward_tensor if input_type != "scalar" else self.forward_scalar
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def forward_tensor(self, x):
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return bool(x)
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def forward_scalar(self, x:int):
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return bool(x)
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ref_net = None
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return prim_bool(input_type), ref_net, "aten::Bool"
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@pytest.mark.parametrize("input_type", ["tensor", "scalar"])
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_bool(self, ie_device, precision, ir_version, input_type):
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self._test(*self.create_model(input_type), ie_device, precision, ir_version)
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