Ekaterina Aidova
3f5d7ad7a0
* [PT FE]: support aten::var_mean and aten::remainder * upd headers * fix gather version
57 lines
2.4 KiB
Python
57 lines
2.4 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 TestVar(PytorchLayerTest):
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def _prepare_input(self):
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import numpy as np
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return (np.random.randn(1, 3, 224, 224).astype(np.float32),)
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def create_model(self, unbiased, dim=None, keepdim=True, two_args_case=True, return_mean=False):
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import torch
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class aten_var(torch.nn.Module):
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def __init__(self, dim, unbiased, keepdim, return_mean):
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super(aten_var, self).__init__()
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self.unbiased = unbiased
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self.dim = dim
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self.keepdim = keepdim
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self.op = torch.var if not return_mean else torch.var_mean
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def forward(self, x):
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return self.op(x, self.dim, unbiased=self.unbiased, keepdim=self.keepdim)
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class aten_var2args(torch.nn.Module):
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def __init__(self, unbiased, return_mean):
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super(aten_var2args, self).__init__()
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self.unbiased = unbiased
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self.op = torch.var if not return_mean else torch.var_mean
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def forward(self, x):
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return torch.var(x, self.unbiased)
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ref_net = None
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op_name = "aten::var" if not return_mean else "aten::var_mean"
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if two_args_case:
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return aten_var2args(unbiased, return_mean), ref_net, op_name
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return aten_var(dim, unbiased, keepdim, return_mean), ref_net, op_name
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.parametrize("unbiased", [True, False])
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@pytest.mark.parametrize("return_mean", [True, False])
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def test_var2args(self, unbiased, return_mean, ie_device, precision, ir_version):
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self._test(*self.create_model(unbiased, return_mean), ie_device, precision, ir_version)
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.parametrize("unbiased", [False, True])
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@pytest.mark.parametrize("dim", [None, 0, 1, 2, 3, -1, -2, (0, 1), (-1, -2), (0, 1, -1), (0, 1, 2, 3)])
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@pytest.mark.parametrize("keepdim", [True, False])
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@pytest.mark.parametrize("return_mean", [True, False])
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def test_var(self, unbiased, dim, keepdim, return_mean, ie_device, precision, ir_version):
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self._test(*self.create_model(unbiased, dim, keepdim, two_args_case=False, return_mean=return_mean), ie_device, precision, ir_version) |