wehub-resource-sync
148 lines
4.3 KiB
Python
148 lines
4.3 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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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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import unittest
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import numpy as np
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import paddle
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from paddle.base import core
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@unittest.skipIf(
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not core.is_compiled_with_cuda(),
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"not support cpu TestEagerCompareAccuracyApi",
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)
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class TestEagerCompareAccuracyApi(unittest.TestCase):
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def calc(self, path, dtype):
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paddle.base.core.set_nan_inf_debug_path(path)
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x = paddle.to_tensor(
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[2000, 3000, 4, 0], place=core.CUDAPlace(0), dtype=dtype
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)
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y = paddle.to_tensor(
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[100, 500, 2, 10000], place=core.CUDAPlace(0), dtype=dtype
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)
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# normal
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z1 = x + y
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# inf
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z2 = x * y
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def test(self):
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paddle.set_flags(
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{"FLAGS_check_nan_inf": 1, "FLAGS_check_nan_inf_level": 3}
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)
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fp32_path = "workerlog_fp32_log_dir"
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fp16_path = "workerlog_fp16_log_dir"
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self.calc(fp32_path, "float32")
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self.calc(fp16_path, "float16")
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out_excel = "compare_accuracy_out_excel.csv"
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paddle.amp.debugging.compare_accuracy(
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fp32_path,
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fp16_path,
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out_excel,
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loss_scale=1,
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dump_all_tensors=False,
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)
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def test2(self):
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fp32_path = "workerlog_fp32_log_dir"
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fp16_path = "workerlog_fp16_null_log_dir"
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self.calc(fp32_path, "float32")
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out_excel = "compare_accuracy_out_excel_2.csv"
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paddle.amp.debugging.compare_accuracy(
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fp32_path,
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fp16_path,
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out_excel,
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loss_scale=1,
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dump_all_tensors=False,
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)
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@unittest.skipIf(
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not core.is_compiled_with_cuda(),
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"not support cpu TestPirCompareAccuracyApi",
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)
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class TestPirCompareAccuracyApi(unittest.TestCase):
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def calc(self, path, dtype):
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paddle.base.core.set_nan_inf_debug_path(path)
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with paddle.pir_utils.IrGuard():
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startup = paddle.static.Program()
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main = paddle.static.Program()
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with paddle.static.program_guard(main, startup):
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x = paddle.static.data(
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'x',
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[
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4,
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],
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dtype,
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)
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y = paddle.static.data(
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'y',
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[
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4,
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],
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dtype,
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)
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# normal
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z1 = x + y
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# inf
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z2 = x * y
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place = paddle.CUDAPlace(0)
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exe = paddle.static.Executor(place)
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exe.run(startup)
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exe.run(
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main,
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feed={
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'x': np.array([2000, 3000, 4, 0]).astype(dtype),
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'y': np.array([100, 500, 2, 10000]).astype(dtype),
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},
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fetch_list=[z2],
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)
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def test(self):
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paddle.set_flags(
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{"FLAGS_check_nan_inf": 1, "FLAGS_check_nan_inf_level": 3}
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)
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fp32_path = "workerlog_fp32_log_dir"
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fp16_path = "workerlog_fp16_log_dir"
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self.calc(fp32_path, "float32")
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self.calc(fp16_path, "float16")
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out_excel = "compare_accuracy_out_excel.csv"
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paddle.amp.debugging.compare_accuracy(
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fp32_path,
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fp16_path,
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out_excel,
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loss_scale=1,
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dump_all_tensors=False,
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)
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def test2(self):
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fp32_path = "workerlog_fp32_log_dir"
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fp16_path = "workerlog_fp16_null_log_dir"
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self.calc(fp32_path, "float32")
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out_excel = "compare_accuracy_out_excel_2.csv"
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paddle.amp.debugging.compare_accuracy(
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fp32_path,
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fp16_path,
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out_excel,
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loss_scale=1,
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dump_all_tensors=False,
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)
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if __name__ == '__main__':
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unittest.main()
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