wehub-resource-sync
53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
#
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# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""Test pytorch_quantization.utils"""
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import pytest
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import numpy as np
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import torch
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from pytorch_quantization import utils as quant_utils
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from tests.fixtures import verbose
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np.random.seed(12345)
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# pylint:disable=missing-docstring, no-self-use
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class TestQuantUtils():
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def test_reduce_amax(self):
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x_np = (np.random.rand(3, 7, 11, 13, 17) - 0.1).astype(np.float32)
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x_torch = torch.tensor(x_np)
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# Test reduce to one value
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amax_np = np.max(np.abs(x_np))
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amax_torch = quant_utils.reduce_amax(x_torch)
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np.testing.assert_array_equal(amax_np, amax_torch.cpu().numpy())
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# Test different axis
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axes = [(1, 2, 3), (0, 2, 3), (0, 3), (0, 1, 3, 4)]
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for axis in axes:
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keepdims = np.random.rand() > 0.5
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amax_np = np.max(np.abs(x_np), axis=axis, keepdims=keepdims)
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amax_torch = quant_utils.reduce_amax(x_torch, axis=axis, keepdims=keepdims)
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np.testing.assert_array_almost_equal(amax_np, amax_torch.cpu().numpy())
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with pytest.raises(ValueError) as excinfo:
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quant_utils.reduce_amax(x_torch, axis=(0, 1, 2, 3, 4, 5))
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assert "Cannot reduce more axes" in str(excinfo.value)
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