From 32f0ccbf33c6f910e9ca8c417a3a093335a7e84b Mon Sep 17 00:00:00 2001 From: v1docq Date: Thu, 24 Oct 2024 17:06:13 +0300 Subject: [PATCH] fix test 0.4 --- .../test_column_sampling_decomposition.py | 8 +-- .../decomposition/test_decomposed_conv.py | 50 ------------------- 2 files changed, 1 insertion(+), 57 deletions(-) delete mode 100644 tests/unit/core/operation/decomposition/test_decomposed_conv.py diff --git a/tests/unit/core/operation/decomposition/test_column_sampling_decomposition.py b/tests/unit/core/operation/decomposition/test_column_sampling_decomposition.py index d69fee3d5..37191c81b 100644 --- a/tests/unit/core/operation/decomposition/test_column_sampling_decomposition.py +++ b/tests/unit/core/operation/decomposition/test_column_sampling_decomposition.py @@ -1,8 +1,7 @@ import numpy as np import pytest -from fedot_ind.core.operation.decomposition.matrix_decomposition.column_sampling_decomposition import CURDecomposition, \ - get_random_sparse_matrix +from fedot_ind.core.operation.decomposition.matrix_decomposition.column_sampling_decomposition import CURDecomposition @pytest.fixture @@ -36,8 +35,3 @@ def test_matrix_to_ts(sample_matrix): assert isinstance(ts, np.ndarray) assert len(ts.shape) == 1 - -def test_get_random_sparse_matrix(): - matrix = get_random_sparse_matrix(size=(10, 10)) - assert isinstance(matrix, np.ndarray) - assert matrix.mean() < 0.5 diff --git a/tests/unit/core/operation/decomposition/test_decomposed_conv.py b/tests/unit/core/operation/decomposition/test_decomposed_conv.py deleted file mode 100644 index e874cc1f3..000000000 --- a/tests/unit/core/operation/decomposition/test_decomposed_conv.py +++ /dev/null @@ -1,50 +0,0 @@ -import pytest -import random -import torch -from fedot_ind.core.operation.decomposition.decomposed_conv import DecomposedConv2d - - -@pytest.fixture(scope='module') -def params(): - return dict(in_channels=3, - out_channels=32, - kernel_size=(3, 5), - stride=(1, 2), - padding=(1, 2), - dilation=(1, 2)) - - -def run(mode, params): - base_conv = torch.nn.Conv2d( - in_channels=params['in_channels'], - out_channels=params['out_channels'], - kernel_size=params['kernel_size'], - stride=params['stride'], - padding=params['padding'], - dilation=params['dilation'], - ) - dconvs = { - 'dconv': DecomposedConv2d(base_conv, None), - 'one_layer': DecomposedConv2d(base_conv, mode), - 'two_layers': DecomposedConv2d(base_conv, mode, forward_mode='two_layers'), - 'three_layers': DecomposedConv2d(base_conv, mode, forward_mode='three_layers') - } - x = torch.rand( - (random.randint( - 1, 16), params['in_channels'], random.randint( - 28, 1000), random.randint( - 28, 1000))) - y_true = base_conv(x) - for name, dconv in dconvs.items(): - y = dconv(x) - is_ok = torch.allclose(y, y_true, rtol=0.0001, atol=0.00001) - print(is_ok) - assert is_ok, f"{mode}: {base_conv} {torch.isclose(y, y_true)}" - - -def test_channel_decomposed_conv(params): - run('channel', params) - - -def test_spatial_decomposed_conv(params): - run('spatial', params)