e14d1b2a07
* Added torch script backend * Added ts_backend to pytorch layer tests * Added use_ts_backend fixture to the test suite to activate the torchscript backend * Fixed failing test_dict layer test * Added USE_TS_BACKEND as an env variable * Removed use_ts_backend fixture * Added more tests for ts backend * Added more information in the comments about usage * Removed convolution3d test from precommit_ts_backend * Added some torchscript backend tests to ci * Removed tests from CI as torch.compile doesn't support 3.11 currently * Fixed linter issues * Addressed PR comments and linter issues
128 lines
5.0 KiB
Python
128 lines
5.0 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import pytest
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import torch
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from pytorch_layer_test_class import PytorchLayerTest
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@pytest.mark.parametrize('alpha', (-0.5, 0, 0.5, 1, 2))
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@pytest.mark.parametrize('input_rhs', (np.random.randn(2, 5, 3, 4).astype(np.float32),
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np.random.randn(
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1, 5, 3, 4).astype(np.float32),
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np.random.randn(1).astype(np.float32)))
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class TestAdd(PytorchLayerTest):
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def _prepare_input(self):
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return (np.random.randn(2, 5, 3, 4).astype(np.float32), self.input_rhs)
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def create_model(self, alpha, op_type):
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class aten_add(torch.nn.Module):
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def __init__(self, alpha, op) -> None:
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super().__init__()
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self.alpha = alpha
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self.forward = self.forward1 if op == "add" else self.forward2
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def forward1(self, lhs, rhs):
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return torch.add(lhs, rhs, alpha=self.alpha)
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def forward2(self, lhs, rhs):
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return lhs.add_(rhs, alpha=self.alpha)
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ref_net = None
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return aten_add(alpha, op_type), ref_net, f"aten::{op_type}"
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.precommit_ts_backend
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@pytest.mark.parametrize("op_type", ["add", "add_"])
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def test_add(self, ie_device, precision, ir_version, alpha, input_rhs, op_type):
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self.input_rhs = input_rhs
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self._test(*self.create_model(alpha, op_type), ie_device, precision, ir_version)
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class TestAddTypes(PytorchLayerTest):
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def _prepare_input(self):
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if len(self.lhs_shape) == 0:
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return (torch.randn(self.rhs_shape).to(self.rhs_type).numpy(),)
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elif len(self.rhs_shape) == 0:
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return (torch.randn(self.lhs_shape).to(self.lhs_type).numpy(),)
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return (torch.randn(self.lhs_shape).to(self.lhs_type).numpy(),
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torch.randn(self.rhs_shape).to(self.rhs_type).numpy())
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def create_model(self, lhs_type, lhs_shape, rhs_type, rhs_shape):
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class aten_add(torch.nn.Module):
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def __init__(self, lhs_type, lhs_shape, rhs_type, rhs_shape):
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super().__init__()
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self.lhs_type = lhs_type
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self.rhs_type = rhs_type
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if len(lhs_shape) == 0:
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self.forward = self.forward1
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elif len(rhs_shape) == 0:
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self.forward = self.forward2
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else:
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self.forward = self.forward3
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def forward1(self, rhs):
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return torch.add(torch.tensor(3).to(self.lhs_type), rhs.to(self.rhs_type), alpha=2)
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def forward2(self, lhs):
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return torch.add(lhs.to(self.lhs_type), torch.tensor(3).to(self.rhs_type), alpha=2)
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def forward3(self, lhs, rhs):
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return torch.add(lhs.to(self.lhs_type), rhs.to(self.rhs_type), alpha=2)
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ref_net = None
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return aten_add(lhs_type, lhs_shape, rhs_type, rhs_shape), ref_net, "aten::add"
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@pytest.mark.parametrize(("lhs_type", "rhs_type"),
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[[torch.int32, torch.int64],
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[torch.int32, torch.float32],
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[torch.int32, torch.float64],
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[torch.int64, torch.int32],
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[torch.int64, torch.float32],
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[torch.int64, torch.float64],
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[torch.float32, torch.int32],
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[torch.float32, torch.int64],
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[torch.float32, torch.float64],
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])
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@pytest.mark.parametrize(("lhs_shape", "rhs_shape"), [([2, 3], [2, 3]),
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([2, 3], []),
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([], [2, 3]),
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])
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.precommit_ts_backend
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def test_add_types(self, ie_device, precision, ir_version, lhs_type, lhs_shape, rhs_type, rhs_shape):
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self.lhs_type = lhs_type
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self.lhs_shape = lhs_shape
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self.rhs_type = rhs_type
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self.rhs_shape = rhs_shape
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self._test(*self.create_model(lhs_type, lhs_shape, rhs_type, rhs_shape),
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ie_device, precision, ir_version)
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class TestAddLists(PytorchLayerTest):
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def _prepare_input(self):
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return (np.random.randn(2, 5, 3, 4).astype(np.float32),)
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def create_model(self):
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class aten_add(torch.nn.Module):
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def forward(self, x):
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return x.reshape(x.shape[:-1] + (-1,))
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return aten_add(), None, "aten::add"
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.precommit_ts_backend
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def test_add(self, ie_device, precision, ir_version):
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self._test(*self.create_model(), ie_device, precision, ir_version)
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