78 lines
2.4 KiB
Python
78 lines
2.4 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
|
|
import numpy as np
|
|
import pytest
|
|
|
|
from pytorch_layer_test_class import PytorchLayerTest
|
|
|
|
|
|
class TestStack2D(PytorchLayerTest):
|
|
def _prepare_input(self):
|
|
return self.input_tensors
|
|
|
|
def create_model(self, dim):
|
|
import torch
|
|
|
|
class aten_stack(torch.nn.Module):
|
|
def __init__(self, dim):
|
|
super(aten_stack, self).__init__()
|
|
self.dim = dim
|
|
|
|
def forward(self, x, y):
|
|
inputs = [x, y]
|
|
return torch.stack(inputs, self.dim)
|
|
|
|
ref_net = None
|
|
|
|
return aten_stack(dim), ref_net, "aten::stack"
|
|
|
|
@pytest.mark.parametrize("input_tensor", ([
|
|
[np.random.rand(1, 3, 3), np.random.rand(1, 3, 3)],
|
|
[np.random.rand(4, 4, 2), np.random.rand(4, 4, 2)],
|
|
[np.random.rand(8, 1, 1, 9), np.random.rand(8, 1, 1, 9)]
|
|
]))
|
|
@pytest.mark.parametrize("dim", ([
|
|
0, 1, 2,
|
|
]))
|
|
@pytest.mark.nightly
|
|
@pytest.mark.precommit
|
|
def test_stack2D(self, input_tensor, dim, ie_device, precision, ir_version):
|
|
self.input_tensors = input_tensor
|
|
self._test(*self.create_model(dim), ie_device, precision, ir_version)
|
|
|
|
|
|
class TestStack3D(PytorchLayerTest):
|
|
def _prepare_input(self):
|
|
return self.input_tensors
|
|
|
|
def create_model(self, dim):
|
|
import torch
|
|
|
|
class aten_stack(torch.nn.Module):
|
|
def __init__(self, dim):
|
|
super(aten_stack, self).__init__()
|
|
self.dim = dim
|
|
|
|
def forward(self, x, y, z):
|
|
inputs = [x, y, z]
|
|
return torch.stack(inputs, self.dim)
|
|
|
|
ref_net = None
|
|
|
|
return aten_stack(dim), ref_net, "aten::stack"
|
|
|
|
@pytest.mark.parametrize("input_tensor", ([
|
|
[np.random.rand(1, 3, 3), np.random.rand(1, 3, 3), np.random.rand(1, 3, 3)],
|
|
[np.random.rand(4, 4, 2), np.random.rand(4, 4, 2), np.random.rand(4, 4, 2)],
|
|
[np.random.rand(8, 1, 1, 9), np.random.rand(8, 1, 1, 9), np.random.rand(8, 1, 1, 9)]
|
|
]))
|
|
@pytest.mark.parametrize("dim", ([
|
|
0, 1, 2,
|
|
]))
|
|
@pytest.mark.nightly
|
|
@pytest.mark.precommit
|
|
def test_stack3D(self, input_tensor, dim, ie_device, precision, ir_version):
|
|
self.input_tensors = input_tensor
|
|
self._test(*self.create_model(dim), ie_device, precision, ir_version)
|