mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
861147c730
* sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * bugfix * update with main (#1631) * update seaco finetune * v1.0.24 --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com> * sensevoice * sensevoice * sensevoice * update with main (#1638) * update seaco finetune * v1.0.24 * update rwkv template --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com> * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * whisper * whisper * update style * update style --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com>
81 lines
2.5 KiB
Python
81 lines
2.5 KiB
Python
import os
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import io
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import shutil
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import logging
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from collections import OrderedDict
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import numpy as np
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from omegaconf import DictConfig, OmegaConf
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def statistic_model_parameters(model, prefix=None):
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var_dict = model.state_dict()
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numel = 0
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for i, key in enumerate(
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sorted(list([x for x in var_dict.keys() if "num_batches_tracked" not in x]))
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):
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if prefix is None or key.startswith(prefix):
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numel += var_dict[key].numel()
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return numel
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def int2vec(x, vec_dim=8, dtype=np.int32):
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b = ("{:0" + str(vec_dim) + "b}").format(x)
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# little-endian order: lower bit first
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return (np.array(list(b)[::-1]) == "1").astype(dtype)
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def seq2arr(seq, vec_dim=8):
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return np.row_stack([int2vec(int(x), vec_dim) for x in seq])
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def load_scp_as_dict(scp_path, value_type="str", kv_sep=" "):
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with io.open(scp_path, "r", encoding="utf-8") as f:
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ret_dict = OrderedDict()
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for one_line in f.readlines():
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one_line = one_line.strip()
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pos = one_line.find(kv_sep)
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key, value = one_line[:pos], one_line[pos + 1 :]
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if value_type == "list":
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value = value.split(" ")
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ret_dict[key] = value
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return ret_dict
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def load_scp_as_list(scp_path, value_type="str", kv_sep=" "):
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with io.open(scp_path, "r", encoding="utf8") as f:
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ret_dict = []
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for one_line in f.readlines():
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one_line = one_line.strip()
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pos = one_line.find(kv_sep)
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key, value = one_line[:pos], one_line[pos + 1 :]
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if value_type == "list":
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value = value.split(" ")
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ret_dict.append((key, value))
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return ret_dict
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def deep_update(original, update):
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for key, value in update.items():
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if isinstance(value, dict) and key in original:
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if len(value) == 0:
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original[key] = value
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deep_update(original[key], value)
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else:
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original[key] = value
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def prepare_model_dir(**kwargs):
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os.makedirs(kwargs.get("output_dir", "./"), exist_ok=True)
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yaml_file = os.path.join(kwargs.get("output_dir", "./"), "config.yaml")
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OmegaConf.save(config=kwargs, f=yaml_file)
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print(kwargs)
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logging.info("config.yaml is saved to: %s", yaml_file)
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# model_path = kwargs.get("model_path")
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# if model_path is not None:
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# config_json = os.path.join(model_path, "configuration.json")
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# if os.path.exists(config_json):
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# shutil.copy(config_json, os.path.join(kwargs.get("output_dir", "./"), "configuration.json"))
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