Spaces:
Runtime error
Runtime error
File size: 1,569 Bytes
5b765fe |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
import numbers
from collections import defaultdict
import numpy as np
import paddle
class DictCollator(object):
"""
data batch
"""
def __call__(self, batch):
# todo：support batch operators
data_dict = defaultdict(list)
to_tensor_keys = []
for sample in batch:
for k, v in sample.items():
if isinstance(v, (np.ndarray, paddle.Tensor, numbers.Number)):
if k not in to_tensor_keys:
to_tensor_keys.append(k)
data_dict[k].append(v)
for k in to_tensor_keys:
data_dict[k] = paddle.to_tensor(data_dict[k])
return data_dict
class ListCollator(object):
"""
data batch
"""
def __call__(self, batch):
# todo：support batch operators
data_dict = defaultdict(list)
to_tensor_idxs = []
for sample in batch:
for idx, v in enumerate(sample):
if isinstance(v, (np.ndarray, paddle.Tensor, numbers.Number)):
if idx not in to_tensor_idxs:
to_tensor_idxs.append(idx)
data_dict[idx].append(v)
for idx in to_tensor_idxs:
data_dict[idx] = paddle.to_tensor(data_dict[idx])
return list(data_dict.values())
class SSLRotateCollate(object):
"""
bach: [
[(4*3xH*W), (4,)]
[(4*3xH*W), (4,)]
...
]
"""
def __call__(self, batch):
output = [np.concatenate(d, axis=0) for d in zip(*batch)]
return output
|