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⚡️ Speed up function create_rename_keys by 119% #395

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171 changes: 98 additions & 73 deletions src/transformers/models/deprecated/deta/convert_deta_swin_to_pytorch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,85 +73,110 @@ def get_deta_config(model_name):

# here we list all keys to be renamed (original name on the left, our name on the right)
def create_rename_keys(config):
rename_keys = []

# stem
# fmt: off
rename_keys.append(("backbone.0.body.patch_embed.proj.weight", "model.backbone.model.embeddings.patch_embeddings.projection.weight"))
rename_keys.append(("backbone.0.body.patch_embed.proj.bias", "model.backbone.model.embeddings.patch_embeddings.projection.bias"))
rename_keys.append(("backbone.0.body.patch_embed.norm.weight", "model.backbone.model.embeddings.norm.weight"))
rename_keys.append(("backbone.0.body.patch_embed.norm.bias", "model.backbone.model.embeddings.norm.bias"))
# stages
for i in range(len(config.backbone_config.depths)):
for j in range(config.backbone_config.depths[i]):
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.norm1.weight", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.layernorm_before.weight"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.norm1.bias", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.layernorm_before.bias"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.attn.relative_position_bias_table", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.attention.self.relative_position_bias_table"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.attn.relative_position_index", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.attention.self.relative_position_index"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.attn.proj.weight", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.attention.output.dense.weight"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.attn.proj.bias", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.attention.output.dense.bias"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.norm2.weight", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.layernorm_after.weight"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.norm2.bias", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.layernorm_after.bias"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.mlp.fc1.weight", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.intermediate.dense.weight"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.mlp.fc1.bias", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.intermediate.dense.bias"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.mlp.fc2.weight", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.output.dense.weight"))
rename_keys.append((f"backbone.0.body.layers.{i}.blocks.{j}.mlp.fc2.bias", f"model.backbone.model.encoder.layers.{i}.blocks.{j}.output.dense.bias"))
# Collect all keys in a single list for faster append operations
rename_keys = [
# stem
("backbone.0.body.patch_embed.proj.weight", "model.backbone.model.embeddings.patch_embeddings.projection.weight"),
("backbone.0.body.patch_embed.proj.bias", "model.backbone.model.embeddings.patch_embeddings.projection.bias"),
("backbone.0.body.patch_embed.norm.weight", "model.backbone.model.embeddings.norm.weight"),
("backbone.0.body.patch_embed.norm.bias", "model.backbone.model.embeddings.norm.bias"),
]

# stages (use local vars for repeated attributes so attribute lookups don't repeat)
depths = config.backbone_config.depths
num_stages = len(depths)
for i in range(num_stages):
depth_i = depths[i]
for j in range(depth_i):
# Use local variables for precalculated string prefixes (minor optimization in tight loop)
src_prefix = f"backbone.0.body.layers.{i}.blocks.{j}"
tgt_prefix = f"model.backbone.model.encoder.layers.{i}.blocks.{j}"
rename_keys.extend([
(f"{src_prefix}.norm1.weight", f"{tgt_prefix}.layernorm_before.weight"),
(f"{src_prefix}.norm1.bias", f"{tgt_prefix}.layernorm_before.bias"),
(f"{src_prefix}.attn.relative_position_bias_table", f"{tgt_prefix}.attention.self.relative_position_bias_table"),
(f"{src_prefix}.attn.relative_position_index", f"{tgt_prefix}.attention.self.relative_position_index"),
(f"{src_prefix}.attn.proj.weight", f"{tgt_prefix}.attention.output.dense.weight"),
(f"{src_prefix}.attn.proj.bias", f"{tgt_prefix}.attention.output.dense.bias"),
(f"{src_prefix}.norm2.weight", f"{tgt_prefix}.layernorm_after.weight"),
(f"{src_prefix}.norm2.bias", f"{tgt_prefix}.layernorm_after.bias"),
(f"{src_prefix}.mlp.fc1.weight", f"{tgt_prefix}.intermediate.dense.weight"),
(f"{src_prefix}.mlp.fc1.bias", f"{tgt_prefix}.intermediate.dense.bias"),
(f"{src_prefix}.mlp.fc2.weight", f"{tgt_prefix}.output.dense.weight"),
(f"{src_prefix}.mlp.fc2.bias", f"{tgt_prefix}.output.dense.bias"),
])

if i < 3:
rename_keys.append((f"backbone.0.body.layers.{i}.downsample.reduction.weight", f"model.backbone.model.encoder.layers.{i}.downsample.reduction.weight"))
rename_keys.append((f"backbone.0.body.layers.{i}.downsample.norm.weight", f"model.backbone.model.encoder.layers.{i}.downsample.norm.weight"))
rename_keys.append((f"backbone.0.body.layers.{i}.downsample.norm.bias", f"model.backbone.model.encoder.layers.{i}.downsample.norm.bias"))

rename_keys.append(("backbone.0.body.norm1.weight", "model.backbone.model.hidden_states_norms.stage2.weight"))
rename_keys.append(("backbone.0.body.norm1.bias", "model.backbone.model.hidden_states_norms.stage2.bias"))
rename_keys.append(("backbone.0.body.norm2.weight", "model.backbone.model.hidden_states_norms.stage3.weight"))
rename_keys.append(("backbone.0.body.norm2.bias", "model.backbone.model.hidden_states_norms.stage3.bias"))
rename_keys.append(("backbone.0.body.norm3.weight", "model.backbone.model.hidden_states_norms.stage4.weight"))
rename_keys.append(("backbone.0.body.norm3.bias", "model.backbone.model.hidden_states_norms.stage4.bias"))
if i < 3:
src_down_prefix = f"backbone.0.body.layers.{i}.downsample"
tgt_down_prefix = f"model.backbone.model.encoder.layers.{i}.downsample"
rename_keys.extend([
(f"{src_down_prefix}.reduction.weight", f"{tgt_down_prefix}.reduction.weight"),
(f"{src_down_prefix}.norm.weight", f"{tgt_down_prefix}.norm.weight"),
(f"{src_down_prefix}.norm.bias", f"{tgt_down_prefix}.norm.bias"),
])

# Add static backbone norm keys (grouped in a single extend for fewer `append` calls)
rename_keys.extend([
("backbone.0.body.norm1.weight", "model.backbone.model.hidden_states_norms.stage2.weight"),
("backbone.0.body.norm1.bias", "model.backbone.model.hidden_states_norms.stage2.bias"),
("backbone.0.body.norm2.weight", "model.backbone.model.hidden_states_norms.stage3.weight"),
("backbone.0.body.norm2.bias", "model.backbone.model.hidden_states_norms.stage3.bias"),
("backbone.0.body.norm3.weight", "model.backbone.model.hidden_states_norms.stage4.weight"),
("backbone.0.body.norm3.bias", "model.backbone.model.hidden_states_norms.stage4.bias"),
])

# transformer encoder
for i in range(config.encoder_layers):
rename_keys.append((f"transformer.encoder.layers.{i}.self_attn.sampling_offsets.weight", f"model.encoder.layers.{i}.self_attn.sampling_offsets.weight"))
rename_keys.append((f"transformer.encoder.layers.{i}.self_attn.sampling_offsets.bias", f"model.encoder.layers.{i}.self_attn.sampling_offsets.bias"))
rename_keys.append((f"transformer.encoder.layers.{i}.self_attn.attention_weights.weight", f"model.encoder.layers.{i}.self_attn.attention_weights.weight"))
rename_keys.append((f"transformer.encoder.layers.{i}.self_attn.attention_weights.bias", f"model.encoder.layers.{i}.self_attn.attention_weights.bias"))
rename_keys.append((f"transformer.encoder.layers.{i}.self_attn.value_proj.weight", f"model.encoder.layers.{i}.self_attn.value_proj.weight"))
rename_keys.append((f"transformer.encoder.layers.{i}.self_attn.value_proj.bias", f"model.encoder.layers.{i}.self_attn.value_proj.bias"))
rename_keys.append((f"transformer.encoder.layers.{i}.self_attn.output_proj.weight", f"model.encoder.layers.{i}.self_attn.output_proj.weight"))
rename_keys.append((f"transformer.encoder.layers.{i}.self_attn.output_proj.bias", f"model.encoder.layers.{i}.self_attn.output_proj.bias"))
rename_keys.append((f"transformer.encoder.layers.{i}.norm1.weight", f"model.encoder.layers.{i}.self_attn_layer_norm.weight"))
rename_keys.append((f"transformer.encoder.layers.{i}.norm1.bias", f"model.encoder.layers.{i}.self_attn_layer_norm.bias"))
rename_keys.append((f"transformer.encoder.layers.{i}.linear1.weight", f"model.encoder.layers.{i}.fc1.weight"))
rename_keys.append((f"transformer.encoder.layers.{i}.linear1.bias", f"model.encoder.layers.{i}.fc1.bias"))
rename_keys.append((f"transformer.encoder.layers.{i}.linear2.weight", f"model.encoder.layers.{i}.fc2.weight"))
rename_keys.append((f"transformer.encoder.layers.{i}.linear2.bias", f"model.encoder.layers.{i}.fc2.bias"))
rename_keys.append((f"transformer.encoder.layers.{i}.norm2.weight", f"model.encoder.layers.{i}.final_layer_norm.weight"))
rename_keys.append((f"transformer.encoder.layers.{i}.norm2.bias", f"model.encoder.layers.{i}.final_layer_norm.bias"))
encoder_layers = config.encoder_layers
for i in range(encoder_layers):
src_prefix = f"transformer.encoder.layers.{i}"
tgt_prefix = f"model.encoder.layers.{i}"
rename_keys.extend([
(f"{src_prefix}.self_attn.sampling_offsets.weight", f"{tgt_prefix}.self_attn.sampling_offsets.weight"),
(f"{src_prefix}.self_attn.sampling_offsets.bias", f"{tgt_prefix}.self_attn.sampling_offsets.bias"),
(f"{src_prefix}.self_attn.attention_weights.weight", f"{tgt_prefix}.self_attn.attention_weights.weight"),
(f"{src_prefix}.self_attn.attention_weights.bias", f"{tgt_prefix}.self_attn.attention_weights.bias"),
(f"{src_prefix}.self_attn.value_proj.weight", f"{tgt_prefix}.self_attn.value_proj.weight"),
(f"{src_prefix}.self_attn.value_proj.bias", f"{tgt_prefix}.self_attn.value_proj.bias"),
(f"{src_prefix}.self_attn.output_proj.weight", f"{tgt_prefix}.self_attn.output_proj.weight"),
(f"{src_prefix}.self_attn.output_proj.bias", f"{tgt_prefix}.self_attn.output_proj.bias"),
(f"{src_prefix}.norm1.weight", f"{tgt_prefix}.self_attn_layer_norm.weight"),
(f"{src_prefix}.norm1.bias", f"{tgt_prefix}.self_attn_layer_norm.bias"),
(f"{src_prefix}.linear1.weight", f"{tgt_prefix}.fc1.weight"),
(f"{src_prefix}.linear1.bias", f"{tgt_prefix}.fc1.bias"),
(f"{src_prefix}.linear2.weight", f"{tgt_prefix}.fc2.weight"),
(f"{src_prefix}.linear2.bias", f"{tgt_prefix}.fc2.bias"),
(f"{src_prefix}.norm2.weight", f"{tgt_prefix}.final_layer_norm.weight"),
(f"{src_prefix}.norm2.bias", f"{tgt_prefix}.final_layer_norm.bias"),
])

# transformer decoder
for i in range(config.decoder_layers):
rename_keys.append((f"transformer.decoder.layers.{i}.cross_attn.sampling_offsets.weight", f"model.decoder.layers.{i}.encoder_attn.sampling_offsets.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.cross_attn.sampling_offsets.bias", f"model.decoder.layers.{i}.encoder_attn.sampling_offsets.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.cross_attn.attention_weights.weight", f"model.decoder.layers.{i}.encoder_attn.attention_weights.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.cross_attn.attention_weights.bias", f"model.decoder.layers.{i}.encoder_attn.attention_weights.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.cross_attn.value_proj.weight", f"model.decoder.layers.{i}.encoder_attn.value_proj.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.cross_attn.value_proj.bias", f"model.decoder.layers.{i}.encoder_attn.value_proj.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.cross_attn.output_proj.weight", f"model.decoder.layers.{i}.encoder_attn.output_proj.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.cross_attn.output_proj.bias", f"model.decoder.layers.{i}.encoder_attn.output_proj.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.norm1.weight", f"model.decoder.layers.{i}.encoder_attn_layer_norm.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.norm1.bias", f"model.decoder.layers.{i}.encoder_attn_layer_norm.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.self_attn.out_proj.weight", f"model.decoder.layers.{i}.self_attn.out_proj.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.self_attn.out_proj.bias", f"model.decoder.layers.{i}.self_attn.out_proj.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.norm2.weight", f"model.decoder.layers.{i}.self_attn_layer_norm.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.norm2.bias", f"model.decoder.layers.{i}.self_attn_layer_norm.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.linear1.weight", f"model.decoder.layers.{i}.fc1.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.linear1.bias", f"model.decoder.layers.{i}.fc1.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.linear2.weight", f"model.decoder.layers.{i}.fc2.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.linear2.bias", f"model.decoder.layers.{i}.fc2.bias"))
rename_keys.append((f"transformer.decoder.layers.{i}.norm3.weight", f"model.decoder.layers.{i}.final_layer_norm.weight"))
rename_keys.append((f"transformer.decoder.layers.{i}.norm3.bias", f"model.decoder.layers.{i}.final_layer_norm.bias"))

# fmt: on
decoder_layers = config.decoder_layers
for i in range(decoder_layers):
src_prefix = f"transformer.decoder.layers.{i}"
tgt_prefix = f"model.decoder.layers.{i}"
rename_keys.extend([
(f"{src_prefix}.cross_attn.sampling_offsets.weight", f"{tgt_prefix}.encoder_attn.sampling_offsets.weight"),
(f"{src_prefix}.cross_attn.sampling_offsets.bias", f"{tgt_prefix}.encoder_attn.sampling_offsets.bias"),
(f"{src_prefix}.cross_attn.attention_weights.weight", f"{tgt_prefix}.encoder_attn.attention_weights.weight"),
(f"{src_prefix}.cross_attn.attention_weights.bias", f"{tgt_prefix}.encoder_attn.attention_weights.bias"),
(f"{src_prefix}.cross_attn.value_proj.weight", f"{tgt_prefix}.encoder_attn.value_proj.weight"),
(f"{src_prefix}.cross_attn.value_proj.bias", f"{tgt_prefix}.encoder_attn.value_proj.bias"),
(f"{src_prefix}.cross_attn.output_proj.weight", f"{tgt_prefix}.encoder_attn.output_proj.weight"),
(f"{src_prefix}.cross_attn.output_proj.bias", f"{tgt_prefix}.encoder_attn.output_proj.bias"),
(f"{src_prefix}.norm1.weight", f"{tgt_prefix}.encoder_attn_layer_norm.weight"),
(f"{src_prefix}.norm1.bias", f"{tgt_prefix}.encoder_attn_layer_norm.bias"),
(f"{src_prefix}.self_attn.out_proj.weight", f"{tgt_prefix}.self_attn.out_proj.weight"),
(f"{src_prefix}.self_attn.out_proj.bias", f"{tgt_prefix}.self_attn.out_proj.bias"),
(f"{src_prefix}.norm2.weight", f"{tgt_prefix}.self_attn_layer_norm.weight"),
(f"{src_prefix}.norm2.bias", f"{tgt_prefix}.self_attn_layer_norm.bias"),
(f"{src_prefix}.linear1.weight", f"{tgt_prefix}.fc1.weight"),
(f"{src_prefix}.linear1.bias", f"{tgt_prefix}.fc1.bias"),
(f"{src_prefix}.linear2.weight", f"{tgt_prefix}.fc2.weight"),
(f"{src_prefix}.linear2.bias", f"{tgt_prefix}.fc2.bias"),
(f"{src_prefix}.norm3.weight", f"{tgt_prefix}.final_layer_norm.weight"),
(f"{src_prefix}.norm3.bias", f"{tgt_prefix}.final_layer_norm.bias"),
])

return rename_keys

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