mirror of https://github.com/hpcaitech/ColossalAI
[NFC] polish colossalai/utils/tensor_detector/tensor_detector.py code style (#1566)
parent
0c4c9aa6e0
commit
c7d4932956
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@ -5,18 +5,17 @@ import torch.nn as nn
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from typing import Optional
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from collections import defaultdict
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LINE_WIDTH = 108
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LINE = '-' * LINE_WIDTH + '\n'
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class TensorDetector():
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def __init__(self,
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show_info: bool = True,
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log: str = None,
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include_cpu: bool = False,
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module: Optional[nn.Module] = None
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):
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module: Optional[nn.Module] = None):
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"""This class is a detector to detect tensor on different devices.
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Args:
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@ -57,12 +56,12 @@ class TensorDetector():
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def mem_format(self, real_memory_size):
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# format the tensor memory into a reasonal magnitude
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if real_memory_size >= 2 ** 30:
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return str(real_memory_size / (2 ** 30)) + ' GB'
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if real_memory_size >= 2 ** 20:
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return str(real_memory_size / (2 ** 20)) + ' MB'
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if real_memory_size >= 2 ** 10:
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return str(real_memory_size / (2 ** 10)) + ' KB'
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if real_memory_size >= 2**30:
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return str(real_memory_size / (2**30)) + ' GB'
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if real_memory_size >= 2**20:
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return str(real_memory_size / (2**20)) + ' MB'
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if real_memory_size >= 2**10:
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return str(real_memory_size / (2**10)) + ' KB'
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return str(real_memory_size) + ' B'
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def collect_tensors_state(self):
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@ -125,33 +124,30 @@ class TensorDetector():
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minus = outdated + minus
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if len(self.order) > 0:
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for tensor_id in self.order:
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self.info += template_format.format('+',
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str(self.tensor_info[tensor_id][0]),
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str(self.tensor_info[tensor_id][1]),
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str(tuple(self.tensor_info[tensor_id][2])),
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str(self.tensor_info[tensor_id][3]),
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str(self.tensor_info[tensor_id][4]),
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str(self.tensor_info[tensor_id][5]))
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self.info += template_format.format('+', str(self.tensor_info[tensor_id][0]),
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str(self.tensor_info[tensor_id][1]),
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str(tuple(self.tensor_info[tensor_id][2])),
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str(self.tensor_info[tensor_id][3]),
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str(self.tensor_info[tensor_id][4]),
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str(self.tensor_info[tensor_id][5]))
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self.info += '\n'
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if len(self.order) > 0 and len(minus) > 0:
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self.info += '\n'
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if len(minus) > 0:
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for tensor_id in minus:
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self.info += template_format.format('-',
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str(self.saved_tensor_info[tensor_id][0]),
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str(self.saved_tensor_info[tensor_id][1]),
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str(tuple(self.saved_tensor_info[tensor_id][2])),
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str(self.saved_tensor_info[tensor_id][3]),
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str(self.saved_tensor_info[tensor_id][4]),
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str(self.saved_tensor_info[tensor_id][5]))
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self.info += template_format.format('-', str(self.saved_tensor_info[tensor_id][0]),
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str(self.saved_tensor_info[tensor_id][1]),
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str(tuple(self.saved_tensor_info[tensor_id][2])),
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str(self.saved_tensor_info[tensor_id][3]),
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str(self.saved_tensor_info[tensor_id][4]),
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str(self.saved_tensor_info[tensor_id][5]))
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self.info += '\n'
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# deleted the updated tensor
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self.saved_tensor_info.pop(tensor_id)
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# trace where is the detect()
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locate_info = inspect.stack()[2]
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locate_msg = '"' + locate_info.filename + '" line ' + str(locate_info.lineno)
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locate_msg = '"' + locate_info.filename + '" line ' + str(locate_info.lineno)
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self.info += LINE
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self.info += f"Detect Location: {locate_msg}\n"
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@ -168,7 +164,7 @@ class TensorDetector():
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with open(self.log + '.log', 'a') as f:
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f.write(self.info)
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def detect(self, include_cpu = False):
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def detect(self, include_cpu=False):
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self.include_cpu = include_cpu
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self.collect_tensors_state()
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self.print_tensors_state()
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