From 98c94ab3ab0266482117343a064beeb6bd6bcedc Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 28 二月 2024 20:45:07 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR merge
---
funasr/train_utils/load_pretrained_model.py | 123 +++++++++++-----------------------------
1 files changed, 35 insertions(+), 88 deletions(-)
diff --git a/funasr/train_utils/load_pretrained_model.py b/funasr/train_utils/load_pretrained_model.py
index 8493bf5..84c6320 100644
--- a/funasr/train_utils/load_pretrained_model.py
+++ b/funasr/train_utils/load_pretrained_model.py
@@ -38,52 +38,17 @@
)
return match_state
-def assigment_scope_map(dst_state: dict, src_state: dict, scope_map: str=None):
- """Compute the union of the current variables and checkpoint variables."""
- import collections
- import re
-
- # current model variables
- name_to_variable = collections.OrderedDict()
- for name, var in dst_state.items():
- name_to_variable[name] = var
-
- scope_map_num = 0
- if scope_map is not None:
- scope_map = scope_map.split(",")
- scope_map_num = len(scope_map) // 2
- for scope_map_idx in range(scope_map_num):
- scope_map_id = scope_map_idx * 2
- logging.info('assignment_map from scope {} to {}'.format(scope_map[scope_map_id], scope_map[scope_map_id+1]))
-
- assignment_map = {}
- for name, var in src_state.items():
-
- if scope_map:
- for scope_map_idx in range(scope_map_num):
- scope_map_id = scope_map_idx * 2
- try:
- idx = name.index(scope_map[scope_map_id])
- new_name = scope_map[scope_map_id+1] + name[idx + len(scope_map[scope_map_id]):]
- if new_name in name_to_variable:
- assignment_map[name] = var
- except:
- continue
- else:
- if name in name_to_variable:
- assignment_map[name] = var
-
- return assignment_map
-
def load_pretrained_model(
path: str,
model: torch.nn.Module,
- ignore_init_mismatch: bool,
+ ignore_init_mismatch: bool=True,
map_location: str = "cpu",
oss_bucket=None,
- scope_map=None,
+ scope_map=[],
excludes=None,
+ ignore_mismatch=False,
+ **kwargs,
):
"""Load a model state and set it to the model.
@@ -108,57 +73,39 @@
src_state = src_state["model"] if "model" in src_state else src_state
+ if isinstance(scope_map, str):
+ scope_map = scope_map.split(",")
+ scope_map += ["module.", "None"]
+
for k in dst_state.keys():
- if not k.startswith("module.") and "module." + k in src_state.keys():
- k_ddp = "module." + k
+
+ k_src = k
+
+ if scope_map is not None:
+ src_prefix = ""
+ dst_prefix = ""
+ for i in range(0, len(scope_map), 2):
+ src_prefix = scope_map[i] if scope_map[i].lower() != "none" else ""
+ dst_prefix = scope_map[i+1] if scope_map[i+1].lower() != "none" else ""
+
+ if dst_prefix == "" and (src_prefix + k) in src_state.keys():
+ k_src = src_prefix + k
+ if not k_src.startswith("module."):
+ print(f"init param, map: {k} from {k_src} in ckpt")
+ elif k.startswith(dst_prefix) and k.replace(dst_prefix, src_prefix, 1) in src_state.keys():
+ k_src = k.replace(dst_prefix, src_prefix, 1)
+ if not k_src.startswith("module."):
+ print(f"init param, map: {k} from {k_src} in ckpt")
+
+ if k_src in src_state.keys():
+ if ignore_init_mismatch and dst_state[k].shape != src_state[k_src].shape:
+ print(f"ignore_mismatch:{ignore_mismatch}, dst: {k, dst_state[k].shape}, src: {k_src, src_state[k_src].shape}")
+ else:
+ dst_state[k] = src_state[k_src]
+
+
else:
- k_ddp = k
- if k_ddp in src_state:
- dst_state[k] = src_state[k_ddp]
- else:
- print(f"Warning, miss key in ckpt: {k}, mapped: {k_ddp}")
+ print(f"Warning, miss key in ckpt: {k}, mapped: {k_src}")
flag = obj.load_state_dict(dst_state, strict=True)
# print(flag)
-
-# def load_pretrained_model(
-# path: str,
-# model: torch.nn.Module,
-# ignore_init_mismatch: bool,
-# map_location: str = "cpu",
-# oss_bucket=None,
-# scope_map=None,
-# excludes=None,
-# ):
-# """Load a model state and set it to the model.
-#
-# Args:
-# init_param: <file_path>:<src_key>:<dst_key>:<exclude_Keys>
-#
-# Examples:
-#
-# """
-#
-# obj = model
-#
-# if oss_bucket is None:
-# src_state = torch.load(path, map_location=map_location)
-# else:
-# buffer = BytesIO(oss_bucket.get_object(path).read())
-# src_state = torch.load(buffer, map_location=map_location)
-# src_state = src_state["model"] if "model" in src_state else src_state
-#
-# if excludes is not None:
-# for e in excludes.split(","):
-# src_state = {k: v for k, v in src_state.items() if not k.startswith(e)}
-#
-# dst_state = obj.state_dict()
-# src_state = assigment_scope_map(dst_state, src_state, scope_map)
-#
-# if ignore_init_mismatch:
-# src_state = filter_state_dict(dst_state, src_state)
-#
-# logging.debug("Loaded src_state keys: {}".format(src_state.keys()))
-# logging.debug("Loaded dst_state keys: {}".format(dst_state.keys()))
-# dst_state.update(src_state)
-# obj.load_state_dict(dst_state, strict=True)
--
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