wehub-resource-sync
61 lines
2.1 KiB
Python
61 lines
2.1 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 for str and repr
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Make sure things can print and in a nice form. Put all the print tests together so that running this test file alone
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can inspect all the print messages in the project
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"""
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import torch
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from torch import nn
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from pytorch_quantization import calib
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from pytorch_quantization import tensor_quant
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from pytorch_quantization import nn as quant_nn
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from pytorch_quantization.nn.modules.tensor_quantizer import TensorQuantizer
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# pylint:disable=missing-docstring, no-self-use
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class TestPrint():
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def test_print_descriptor(self):
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test_desc = tensor_quant.QUANT_DESC_8BIT_CONV2D_WEIGHT_PER_CHANNEL
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print(test_desc)
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def test_print_tensor_quantizer(self):
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test_quantizer = TensorQuantizer()
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print(test_quantizer)
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def test_print_module(self):
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class _TestModule(nn.Module):
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def __init__(self):
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super(_TestModule, self).__init__()
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self.conv = nn.Conv2d(33, 65, 3)
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self.quant_conv = quant_nn.Conv2d(33, 65, 3)
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self.linear = nn.Linear(33, 65)
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self.quant_linear = quant_nn.Linear(33, 65)
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test_module = _TestModule()
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print(test_module)
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def test_print_calibrator(self):
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print(calib.MaxCalibrator(7, 1, False))
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hist_calibrator = calib.HistogramCalibrator(8, None, True)
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hist_calibrator.collect(torch.rand(10))
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print(hist_calibrator)
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