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import torch as th
class EasyDict:
def __init__(self, sub_dict):
for k, v in sub_dict.items():
setattr(self, k, v)
def __getitem__(self, key):
return getattr(self, key)
def mean_flat(x):
"""
Take the mean over all non-batch dimensions.
"""
return th.mean(x, dim=list(range(1, len(x.size()))))
def log_state(state):
result = []
sorted_state = dict(sorted(state.items()))
for key, value in sorted_state.items():
# Check if the value is an instance of a class
if "<object" in str(value) or "object at" in str(value):
result.append(f"{key}: [{value.__class__.__name__}]")
else:
result.append(f"{key}: {value}")
return '\n'.join(result) |