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Tidy _prepare_attention_processors(...) logic.
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@ -13,22 +13,10 @@ def _prepare_attention_processors(unet: UNet2DConditionModel, ip_adapters: list[
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Note that the `unet` param is only used to determine attention block dimensions and naming.
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"""
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# TODO(ryand): This logic can be simplified.
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# Construct a dict of attention processors based on the UNet's architecture.
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attn_procs = {}
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for idx, name in enumerate(unet.attn_processors.keys()):
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cross_attention_dim = None if name.endswith("attn1.processor") else unet.config.cross_attention_dim
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if name.startswith("mid_block"):
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hidden_size = unet.config.block_out_channels[-1]
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elif name.startswith("up_blocks"):
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block_id = int(name[len("up_blocks.")])
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hidden_size = list(reversed(unet.config.block_out_channels))[block_id]
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elif name.startswith("down_blocks"):
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block_id = int(name[len("down_blocks.")])
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hidden_size = unet.config.block_out_channels[block_id]
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if cross_attention_dim is None:
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if name.endswith("attn1.processor"):
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attn_procs[name] = AttnProcessor2_0()
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else:
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# Collect the weights from each IP Adapter for the idx'th attention processor.
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@ -43,8 +31,7 @@ def apply_ip_adapter_attention(unet: UNet2DConditionModel, ip_adapters: list[IPA
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"""A context manager that patches `unet` with IP-Adapter attention processors.
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Yields:
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Scales: The Scales object, which can be used to dynamically alter the scales of the
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IP-Adapters.
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Scales: The Scales object, which can be used to dynamically alter the scales of the IP-Adapters.
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"""
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scales = Scales([1.0] * len(ip_adapters))
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