compare_accuracy¶

paddle.amp.debugging. compare_accuracy ( dump_path, another_dump_path, output_filename, loss_scale=1, dump_all_tensors=False ) [source]

This is a precision comparison tool that can be used to compare log data of float16 and float32.

Parameters

• dump_path (str) – The path of the running log, such as the log for execution using the float32 data type.

• another_dump_path (str) – the path of another running log ,such as the log for execution using the float16 data type.

• output_filename (str) – the excel file nmae of compare output.

• loss_scale (float, optional) – the loss_scale during the training phase. Default is 1.

• dump_all_tensors (bool, optional) – dump all tensor, It is currently not support. Default is False.

Examples

>>> import paddle
>>> from paddle.base import core
>>> try:
...     import xlsxwriter as xlw
... except ImportError:
...     import subprocess
...     subprocess.check_call(
...         ['python', '-m', 'pip', 'install', 'xlsxwriter==3.0.9']
...     )
...     import xlsxwriter as xlw
...     if core.is_compiled_with_cuda():
...         paddle.set_flags(
...             {"FLAGS_check_nan_inf": 1, "FLAGS_check_nan_inf_level": 3}
...         )
...         path = "workerlog_log_dir"
...         paddle.base.core.set_nan_inf_debug_path(path)
...         x = paddle.to_tensor(
...             [2, 3, 4, 0], dtype="float32"
...         )
...         y = paddle.to_tensor(
...             [1, 5, 2, 0], dtype="float32"
...         )
...         z1 = x + y
...         out_excel = "compary_accuracy_out_excel.csv"
...         paddle.amp.debugging.compare_accuracy(
...             path, path, out_excel, loss_scale=1, dump_all_tensors=False
...         )