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import importlib.metadata
import torch
import logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
log = logging.getLogger(__name__)
def check_diffusers_version():
try:
version = importlib.metadata.version('diffusers')
required_version = '0.31.0'
if version < required_version:
raise AssertionError(f"diffusers version {version} is installed, but version {required_version} or higher is required.")
except importlib.metadata.PackageNotFoundError:
raise AssertionError("diffusers is not installed.")
def remove_specific_blocks(model, block_indices_to_remove):
import torch.nn as nn
transformer_blocks = model.transformer_blocks
new_blocks = [block for i, block in enumerate(transformer_blocks) if i not in block_indices_to_remove]
model.transformer_blocks = nn.ModuleList(new_blocks)
return model
def print_memory(device):
memory = torch.cuda.memory_allocated(device) / 1024**3
max_memory = torch.cuda.max_memory_allocated(device) / 1024**3
max_reserved = torch.cuda.max_memory_reserved(device) / 1024**3
log.info(f"Allocated memory: {memory=:.3f} GB")
log.info(f"Max allocated memory: {max_memory=:.3f} GB")
log.info(f"Max reserved memory: {max_reserved=:.3f} GB") |