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| """Utility functions.""" |
|
|
| import fnmatch |
| import logging |
| import os |
| import sys |
|
|
| import h5py |
| import numpy as np |
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|
| def find_files(root_dir, query="*.wav", include_root_dir=True): |
| """Find files recursively. |
| |
| Args: |
| root_dir (str): Root root_dir to find. |
| query (str): Query to find. |
| include_root_dir (bool): If False, root_dir name is not included. |
| |
| Returns: |
| list: List of found filenames. |
| |
| """ |
| files = [] |
| for root, dirnames, filenames in os.walk(root_dir, followlinks=True): |
| for filename in fnmatch.filter(filenames, query): |
| files.append(os.path.join(root, filename)) |
| if not include_root_dir: |
| files = [file_.replace(root_dir + "/", "") for file_ in files] |
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|
| return files |
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|
| def read_hdf5(hdf5_name, hdf5_path): |
| """Read hdf5 dataset. |
| |
| Args: |
| hdf5_name (str): Filename of hdf5 file. |
| hdf5_path (str): Dataset name in hdf5 file. |
| |
| Return: |
| any: Dataset values. |
| |
| """ |
| if not os.path.exists(hdf5_name): |
| logging.error(f"There is no such a hdf5 file ({hdf5_name}).") |
| sys.exit(1) |
|
|
| hdf5_file = h5py.File(hdf5_name, "r") |
|
|
| if hdf5_path not in hdf5_file: |
| logging.error(f"There is no such a data in hdf5 file. ({hdf5_path})") |
| sys.exit(1) |
|
|
| hdf5_data = hdf5_file[hdf5_path][()] |
| hdf5_file.close() |
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|
| return hdf5_data |
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|
| def write_hdf5(hdf5_name, hdf5_path, write_data, is_overwrite=True): |
| """Write dataset to hdf5. |
| |
| Args: |
| hdf5_name (str): Hdf5 dataset filename. |
| hdf5_path (str): Dataset path in hdf5. |
| write_data (ndarray): Data to write. |
| is_overwrite (bool): Whether to overwrite dataset. |
| |
| """ |
| |
| write_data = np.array(write_data) |
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|
| |
| folder_name, _ = os.path.split(hdf5_name) |
| if not os.path.exists(folder_name) and len(folder_name) != 0: |
| os.makedirs(folder_name) |
|
|
| |
| if os.path.exists(hdf5_name): |
| |
| hdf5_file = h5py.File(hdf5_name, "r+") |
| |
| if hdf5_path in hdf5_file: |
| if is_overwrite: |
| logging.warning("Dataset in hdf5 file already exists. " |
| "recreate dataset in hdf5.") |
| hdf5_file.__delitem__(hdf5_path) |
| else: |
| logging.error("Dataset in hdf5 file already exists. " |
| "if you want to overwrite, please set is_overwrite = True.") |
| hdf5_file.close() |
| sys.exit(1) |
| else: |
| |
| hdf5_file = h5py.File(hdf5_name, "w") |
|
|
| |
| hdf5_file.create_dataset(hdf5_path, data=write_data) |
| hdf5_file.flush() |
| hdf5_file.close() |
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|
|
| class HDF5ScpLoader(object): |
| """Loader class for a fests.scp file of hdf5 file. |
| |
| Examples: |
| key1 /some/path/a.h5:feats |
| key2 /some/path/b.h5:feats |
| key3 /some/path/c.h5:feats |
| key4 /some/path/d.h5:feats |
| ... |
| >>> loader = HDF5ScpLoader("hdf5.scp") |
| >>> array = loader["key1"] |
| |
| key1 /some/path/a.h5 |
| key2 /some/path/b.h5 |
| key3 /some/path/c.h5 |
| key4 /some/path/d.h5 |
| ... |
| >>> loader = HDF5ScpLoader("hdf5.scp", "feats") |
| >>> array = loader["key1"] |
| |
| """ |
|
|
| def __init__(self, feats_scp, default_hdf5_path="feats"): |
| """Initialize HDF5 scp loader. |
| |
| Args: |
| feats_scp (str): Kaldi-style feats.scp file with hdf5 format. |
| default_hdf5_path (str): Path in hdf5 file. If the scp contain the info, not used. |
| |
| """ |
| self.default_hdf5_path = default_hdf5_path |
| with open(feats_scp) as f: |
| lines = [line.replace("\n", "") for line in f.readlines()] |
| self.data = {} |
| for line in lines: |
| key, value = line.split() |
| self.data[key] = value |
|
|
| def get_path(self, key): |
| """Get hdf5 file path for a given key.""" |
| return self.data[key] |
|
|
| def __getitem__(self, key): |
| """Get ndarray for a given key.""" |
| p = self.data[key] |
| if ":" in p: |
| return read_hdf5(*p.split(":")) |
| else: |
| return read_hdf5(p, self.default_hdf5_path) |
|
|
| def __len__(self): |
| """Return the length of the scp file.""" |
| return len(self.data) |
|
|
| def __iter__(self): |
| """Return the iterator of the scp file.""" |
| return iter(self.data) |
|
|
| def keys(self): |
| """Return the keys of the scp file.""" |
| return self.data.keys() |
|
|