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Unverified Commit b98b314b authored by Sayak Paul's avatar Sayak Paul Committed by GitHub
Browse files

[Training] remove depcreated method from lora scripts. (#6207)

remove depcreated method from lora scripts.
parent 74558ff6
...@@ -64,39 +64,6 @@ check_min_version("0.25.0.dev0") ...@@ -64,39 +64,6 @@ check_min_version("0.25.0.dev0")
logger = get_logger(__name__) logger = get_logger(__name__)
# TODO: This function should be removed once training scripts are rewritten in PEFT
def text_encoder_lora_state_dict(text_encoder):
state_dict = {}
def text_encoder_attn_modules(text_encoder):
from transformers import CLIPTextModel, CLIPTextModelWithProjection
attn_modules = []
if isinstance(text_encoder, (CLIPTextModel, CLIPTextModelWithProjection)):
for i, layer in enumerate(text_encoder.text_model.encoder.layers):
name = f"text_model.encoder.layers.{i}.self_attn"
mod = layer.self_attn
attn_modules.append((name, mod))
return attn_modules
for name, module in text_encoder_attn_modules(text_encoder):
for k, v in module.q_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.q_proj.lora_linear_layer.{k}"] = v
for k, v in module.k_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.k_proj.lora_linear_layer.{k}"] = v
for k, v in module.v_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.v_proj.lora_linear_layer.{k}"] = v
for k, v in module.out_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.out_proj.lora_linear_layer.{k}"] = v
return state_dict
def save_model_card( def save_model_card(
repo_id: str, repo_id: str,
images=None, images=None,
......
...@@ -64,39 +64,6 @@ check_min_version("0.25.0.dev0") ...@@ -64,39 +64,6 @@ check_min_version("0.25.0.dev0")
logger = get_logger(__name__) logger = get_logger(__name__)
# TODO: This function should be removed once training scripts are rewritten in PEFT
def text_encoder_lora_state_dict(text_encoder):
state_dict = {}
def text_encoder_attn_modules(text_encoder):
from transformers import CLIPTextModel, CLIPTextModelWithProjection
attn_modules = []
if isinstance(text_encoder, (CLIPTextModel, CLIPTextModelWithProjection)):
for i, layer in enumerate(text_encoder.text_model.encoder.layers):
name = f"text_model.encoder.layers.{i}.self_attn"
mod = layer.self_attn
attn_modules.append((name, mod))
return attn_modules
for name, module in text_encoder_attn_modules(text_encoder):
for k, v in module.q_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.q_proj.lora_linear_layer.{k}"] = v
for k, v in module.k_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.k_proj.lora_linear_layer.{k}"] = v
for k, v in module.v_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.v_proj.lora_linear_layer.{k}"] = v
for k, v in module.out_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.out_proj.lora_linear_layer.{k}"] = v
return state_dict
def save_model_card( def save_model_card(
repo_id: str, repo_id: str,
images=None, images=None,
......
...@@ -54,39 +54,6 @@ check_min_version("0.25.0.dev0") ...@@ -54,39 +54,6 @@ check_min_version("0.25.0.dev0")
logger = get_logger(__name__, log_level="INFO") logger = get_logger(__name__, log_level="INFO")
# TODO: This function should be removed once training scripts are rewritten in PEFT
def text_encoder_lora_state_dict(text_encoder):
state_dict = {}
def text_encoder_attn_modules(text_encoder):
from transformers import CLIPTextModel, CLIPTextModelWithProjection
attn_modules = []
if isinstance(text_encoder, (CLIPTextModel, CLIPTextModelWithProjection)):
for i, layer in enumerate(text_encoder.text_model.encoder.layers):
name = f"text_model.encoder.layers.{i}.self_attn"
mod = layer.self_attn
attn_modules.append((name, mod))
return attn_modules
for name, module in text_encoder_attn_modules(text_encoder):
for k, v in module.q_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.q_proj.lora_linear_layer.{k}"] = v
for k, v in module.k_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.k_proj.lora_linear_layer.{k}"] = v
for k, v in module.v_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.v_proj.lora_linear_layer.{k}"] = v
for k, v in module.out_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.out_proj.lora_linear_layer.{k}"] = v
return state_dict
def save_model_card(repo_id: str, images=None, base_model=str, dataset_name=str, repo_folder=None): def save_model_card(repo_id: str, images=None, base_model=str, dataset_name=str, repo_folder=None):
img_str = "" img_str = ""
for i, image in enumerate(images): for i, image in enumerate(images):
......
...@@ -63,39 +63,6 @@ check_min_version("0.25.0.dev0") ...@@ -63,39 +63,6 @@ check_min_version("0.25.0.dev0")
logger = get_logger(__name__) logger = get_logger(__name__)
# TODO: This function should be removed once training scripts are rewritten in PEFT
def text_encoder_lora_state_dict(text_encoder):
state_dict = {}
def text_encoder_attn_modules(text_encoder):
from transformers import CLIPTextModel, CLIPTextModelWithProjection
attn_modules = []
if isinstance(text_encoder, (CLIPTextModel, CLIPTextModelWithProjection)):
for i, layer in enumerate(text_encoder.text_model.encoder.layers):
name = f"text_model.encoder.layers.{i}.self_attn"
mod = layer.self_attn
attn_modules.append((name, mod))
return attn_modules
for name, module in text_encoder_attn_modules(text_encoder):
for k, v in module.q_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.q_proj.lora_linear_layer.{k}"] = v
for k, v in module.k_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.k_proj.lora_linear_layer.{k}"] = v
for k, v in module.v_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.v_proj.lora_linear_layer.{k}"] = v
for k, v in module.out_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.out_proj.lora_linear_layer.{k}"] = v
return state_dict
def save_model_card( def save_model_card(
repo_id: str, repo_id: str,
images=None, images=None,
......
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