openvino/tests/layer_tests/pytorch_tests/test_len.py

78 lines
2.2 KiB
Python

# Copyright (C) 2018-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import numpy as np
import pytest
import torch
from pytorch_layer_test_class import PytorchLayerTest
@pytest.mark.parametrize('input_tensor',
[
[2, 1, 3], [3, 7], [1, 1, 4, 4]
])
class TestLen(PytorchLayerTest):
def _prepare_input(self):
input_tensor = self.input_tensor * 10
return (input_tensor.astype(np.int64),)
def create_model(self):
class aten_len(torch.nn.Module):
def forward(self, input_tensor):
return torch.tensor(len(input_tensor))
ref_net = None
return aten_len(), ref_net, "aten::len"
def create_model_int_list(self):
class aten_len(torch.nn.Module):
def forward(self, input_tensor):
int_list = input_tensor.size()
return torch.tensor(len(int_list))
ref_net = None
return aten_len(), ref_net, "aten::len"
@pytest.mark.nightly
@pytest.mark.precommit
def test_len(self, ie_device, precision, ir_version, input_tensor):
self.input_tensor = np.random.randn(*input_tensor).astype(np.float32)
self._test(*self.create_model(), ie_device, precision, ir_version)
@pytest.mark.nightly
@pytest.mark.precommit
def test_len_int_list(self, ie_device, precision, ir_version, input_tensor):
self.input_tensor = np.random.randn(*input_tensor).astype(np.float32)
self._test(*self.create_model_int_list(),
ie_device, precision, ir_version, use_convert_model=True)
class TestLenEmpty(PytorchLayerTest):
def _prepare_input(self):
input_tensor = np.random.randn(1, 2, 3) * 10
return (input_tensor.astype(np.int64),)
def create_model_empty(self):
class aten_len(torch.nn.Module):
def forward(self, input_tensor):
# len of empty slice
return torch.tensor(len(input_tensor[0:0]))
ref_net = None
return aten_len(), ref_net, "aten::len"
@pytest.mark.nightly
@pytest.mark.precommit
def test_len_empty(self, ie_device, precision, ir_version):
self._test(*self.create_model_empty(),
ie_device, precision, ir_version)