# Copyright (C) 2018-2026 Intel Corporation
# SPDX-License-Identifier: Apache-2.0

import pytest

from pytorch_layer_test_class import PytorchLayerTest


class TestSqueeze(PytorchLayerTest):
    def _prepare_input(self):
        return (self.random.randn(1, 1, 32),)

    def create_model(self, dim):
        import torch

        class aten_squeeze(torch.nn.Module):
            def __init__(self, dim):
                super().__init__()
                self.dim = dim

            def forward(self, x):
                if self.dim is not None:
                    return torch.squeeze(x, self.dim)
                return torch.squeeze(x)

        return aten_squeeze(dim), "aten::squeeze"

    @pytest.mark.parametrize("dim,dynamic_shapes", [(-2, True), (0, True), (None, False)])
    @pytest.mark.nightly
    @pytest.mark.precommit
    @pytest.mark.precommit_torch_export
    @pytest.mark.precommit_fx_backend
    def test_squeeze(self, dim, dynamic_shapes, ie_device, precision, ir_version):
        if PytorchLayerTest.use_torch_export() and dim is None:
            pytest.xfail(reason="export fails if dim is not provided")
        self._test(*self.create_model(dim), ie_device, precision, ir_version, dynamic_shapes=dynamic_shapes)

    @pytest.mark.parametrize("dim", [-1, 2])
    @pytest.mark.nightly
    @pytest.mark.precommit
    @pytest.mark.precommit_torch_export
    def test_squeeze_non_1(self, dim, ie_device, precision, ir_version):
        # Dynamic shapes are introducing dynamic rank, with is not suppoerted by Squeeze operation.
        self._test(*self.create_model(dim), ie_device, precision, ir_version, dynamic_shapes=False)

class TestSqueezeCopy(PytorchLayerTest):
    def _prepare_input(self):
        return (self.random.randn(1, 1, 32),)

    def create_model(self, dim):
        import torch

        class aten_squeeze_copy(torch.nn.Module):
            def __init__(self, dim):
                super().__init__()
                self.dim = dim

            def forward(self, x):
                if self.dim is not None:
                    return torch.squeeze_copy(x, self.dim)
                return torch.squeeze_copy(x)

        return aten_squeeze_copy(dim), "aten::squeeze_copy"

    @pytest.mark.parametrize("dim,dynamic_shapes", [(-2, True), (0, True), (None, False)])
    @pytest.mark.precommit_fx_backend
    def test_squeeze_copy(self, dim, dynamic_shapes, ie_device, precision, ir_version):
        if PytorchLayerTest.use_torch_export() and dim is None:
            pytest.xfail(reason="export fails if dim is not provided")
        self._test(*self.create_model(dim), ie_device, precision, ir_version, dynamic_shapes=dynamic_shapes)
