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PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import struct
import sys
import time
import numpy as np
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__all__ = []
class ProgressBar:
"""progress bar"""
def __init__(
self,
num=None,
width=30,
verbose=1,
start=True,
file=sys.stdout,
name='step',
):
self._num = num
if isinstance(num, int) and num <= 0:
raise TypeError('num should be None or integer (> 0)')
max_width = self._get_max_width()
self._width = min(width, max_width)
self._total_width = 0
self._verbose = verbose
self.file = file
self._values = {}
self._values_order = []
if start:
self._start = time.time()
self._last_update = 0
self.name = name
self._dynamic_display = (
(hasattr(self.file, 'isatty') and self.file.isatty())
or 'ipykernel' in sys.modules
or 'posix' in sys.modules
or 'PYCHARM_HOSTED' in os.environ
)
def _get_max_width(self):
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from shutil import get_terminal_size
terminal_width, _ = get_terminal_size()
terminal_width = terminal_width if terminal_width > 0 else 80
max_width = min(int(terminal_width * 0.6), terminal_width - 50)
return max_width
def start(self):
self.file.flush()
self._start = time.time()
def update(self, current_num, values={}):
now = time.time()
def convert_uint16_to_float(in_list):
in_list = np.asarray(in_list)
out = np.vectorize(
lambda x: struct.unpack('<f', struct.pack('<I', x << 16))[0],
otypes=[np.float32],
)(in_list.flat)
return np.reshape(out, in_list.shape)
for i, (k, val) in enumerate(values):
if k == "loss":
if isinstance(val, list):
scalar_val = val[0]
else:
scalar_val = val
if isinstance(scalar_val, np.uint16):
values[i] = ("loss", list(convert_uint16_to_float(val)))
if current_num:
time_per_unit = (now - self._start) / current_num
else:
time_per_unit = 0
if time_per_unit >= 1 or time_per_unit == 0:
fps = f' - {time_per_unit:.0f}s/{self.name}'
elif time_per_unit >= 1e-3:
fps = f' - {time_per_unit * 1e3:.0f}ms/{self.name}'
else:
fps = f' - {time_per_unit * 1e6:.0f}us/{self.name}'
info = ''
if self._verbose == 1:
prev_total_width = self._total_width
if self._dynamic_display:
sys.stdout.write('\b' * prev_total_width)
sys.stdout.write('\r')
else:
sys.stdout.write('\n')
if self._num is not None:
numdigits = int(np.log10(self._num)) + 1
bar_chars = (self.name + ' %' + str(numdigits) + 'd/%d [') % (
current_num,
self._num,
)
prog = float(current_num) / self._num
prog_width = int(self._width * prog)
if prog_width > 0:
bar_chars += '=' * (prog_width - 1)
if current_num < self._num:
bar_chars += '>'
else:
bar_chars += '='
bar_chars += '.' * (self._width - prog_width)
bar_chars += ']'
else:
bar_chars = f'{self.name} {current_num:3}'
self._total_width = len(bar_chars)
sys.stdout.write(bar_chars)
for k, val in values:
info += f' - {k}:'
val = val if isinstance(val, list) else [val]
for i, v in enumerate(val):
if isinstance(v, (float, np.float32, np.float64)):
if abs(v) > 1e-3:
info += f' {v:.4f}'
else:
info += f' {v:.4e}'
else:
info += f' {v}'
if self._num is not None and current_num < self._num:
eta = int(time_per_unit * (self._num - current_num))
if eta > 3600:
eta_format = (
f'{eta // 3600}:{(eta % 3600) // 60:02}:{eta % 60:02}'
)
elif eta > 60:
eta_format = f'{eta // 60}:{eta % 60:02}'
else:
eta_format = f'{eta}s'
info += f' - ETA: {eta_format}'
info += fps
self._total_width += len(info)
if prev_total_width > self._total_width:
info += ' ' * (prev_total_width - self._total_width)
# newline for another epoch
if self._num is not None and current_num >= self._num:
info += '\n'
if self._num is None:
info += '\n'
sys.stdout.write(info)
sys.stdout.flush()
self._last_update = now
elif self._verbose == 2 or self._verbose == 3:
if self._num:
numdigits = int(np.log10(self._num)) + 1
count = (self.name + ' %' + str(numdigits) + 'd/%d') % (
current_num,
self._num,
)
else:
count = f'{self.name} {current_num:3}'
info = count + info
for k, val in values:
info += f' - {k}:'
val = val if isinstance(val, list) else [val]
for v in val:
if isinstance(v, (float, np.float32, np.float64)):
if abs(v) > 1e-3:
info += f' {v:.4f}'
else:
info += f' {v:.4e}'
elif (
isinstance(v, np.ndarray)
and v.size == 1
and v.dtype in [np.float32, np.float64]
):
if abs(v.item()) > 1e-3:
info += f' {v.item():.4f}'
else:
info += f' {v.item():.4e}'
else:
info += f' {v}'
info += fps
info += '\n'
sys.stdout.write(info)
sys.stdout.flush()