openvino/tests/layer_tests/pytorch_tests/test_linspace.py

96 lines
3.7 KiB
Python

# Copyright (C) 2018-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import platform
import numpy as np
import pytest
import torch
from pytorch_layer_test_class import PytorchLayerTest
class TestLinspace(PytorchLayerTest):
def _prepare_input(self, start, end, steps, dtype=None, ref_dtype=None):
inputs = [np.array(start).astype(dtype), np.array(end).astype(dtype), np.array(steps).astype("int32")]
if ref_dtype:
inputs.append(np.zeros(1).astype(ref_dtype))
return inputs
def create_model(self, dtype=None, use_out=False, ref_dtype=False):
dtype_map = {
"float32": torch.float32,
"float64": torch.float64,
"int64": torch.int64,
"int32": torch.int32,
"uint8": torch.uint8,
"int8": torch.int8,
}
class aten_linspace_dtype(torch.nn.Module):
def __init__(self, dtype) -> None:
super().__init__()
self.dtype = dtype
def forward(self, start, end, steps):
return torch.linspace(start=start, end=end, steps=steps, dtype=self.dtype)
class aten_linspace_out(torch.nn.Module):
def __init__(self, out) -> None:
super().__init__()
# Size of empty tensor needs to be of equal or larger size than linspace steps
self.out = torch.empty(25, dtype=out)
def forward(self, start, end, steps):
return torch.linspace(start=start, end=end, steps=steps, out=self.out)
class aten_linspace_prim_dtype(torch.nn.Module):
def forward(self, start, end, steps, d):
return torch.linspace(start=start, end=end, steps=steps, dtype=d.dtype)
dtype = dtype_map.get(dtype)
if ref_dtype:
model_class = aten_linspace_prim_dtype()
elif not use_out:
model_class = aten_linspace_dtype(dtype)
else:
model_class = aten_linspace_out(dtype)
ref_net = None
return model_class, ref_net, "aten::linspace"
@pytest.mark.nightly
@pytest.mark.precommit
@pytest.mark.parametrize("dtype", ["float32", "float64", "int32", "int64", "int8"])
@pytest.mark.parametrize(
"start,end,steps", [(0, 1, 5), (-2, 1, 5), (1, -5, 7), (1, 10, 2), (-1, -5, 2), (-1, -5, 1), (1.25, -5.5, 5)]
)
@pytest.mark.xfail(condition=platform.system() == 'Darwin' and platform.machine() == 'arm64',
reason='Ticket - 122715')
def test_linspace_with_prim_dtype(self, dtype, end, start, steps, ie_device, precision, ir_version):
self._test(
*self.create_model(dtype, ref_dtype=True),
ie_device,
precision,
ir_version,
kwargs_to_prepare_input={"end": end, "start": start, "steps": steps, "ref_dtype": dtype}
)
@pytest.mark.nightly
@pytest.mark.precommit
@pytest.mark.parametrize("dtype", [None, "float32", "float64", "int32", "int64", "int8", "uin8"])
@pytest.mark.parametrize(
"start,end,steps", [(0, 1, 5), (-2, 1, 5), (1, -5, 7), (1, 10, 2), (-1, -5, 2), (-1, -5, 1), (1.25, -5.5, 5)]
)
@pytest.mark.parametrize("use_out", [False, True])
@pytest.mark.xfail(condition=platform.system() == 'Darwin' and platform.machine() == 'arm64',
reason='Ticket - 122715')
def test_linspace_with_out(self, dtype, use_out, end, start, steps, ie_device, precision, ir_version):
self._test(
*self.create_model(dtype=dtype, use_out=use_out),
ie_device,
precision,
ir_version,
kwargs_to_prepare_input={"end": end, "start": start, "steps": steps}
)