mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import io
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from collections import OrderedDict
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import numpy as np
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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(sorted(list([x for x in var_dict.keys() if "num_batches_tracked" not in x]))):
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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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