memory_util.py 文件源码

def __exit__(self, exc_type, exc_value, traceback):
    os.dup2(self.prevfd, self.fd)


################################################################################
# LOG_MEMORY_PARSING
################################################################################
# Until https://github.com/tensorflow/tensorflow/issues/6716 is resolved, the
# reliable way to get access to tensor deallocation information is to parse
# __LOG_MEMORY__ from VLOG print statements. This is sensitive to print order
# run unbuffered to prevent interleaving:
#   python -u script.py

# Regex'es to parse __LOG_MEMORY__ statements
# Each regex is preceded by an example of line it's meant to pass

# I 5143420588.000000 file tensorflow/core/framework/log_memory.cc:41] __LOG_MEMORY__ MemoryLogTensorAllocation { step_id: -6 kernel_name: "Unknown (from Proto)" tensor { dtype: DT_INT32 shape { dim { size: 3 } } allocation_description { requested_bytes: 12 allocated_bytes: 12 allocator_name: "cpu" allocation_id: 3 has_single_reference: true ptr: 29496256 } } }