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Add batch splitting ratio check #336

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Add batch splitting ratio check #336

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6 changes: 4 additions & 2 deletions dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,14 +29,16 @@ def __init__(self, opt):
print(f'dataset_root: {opt.train_data}\nopt.select_data: {opt.select_data}\nopt.batch_ratio: {opt.batch_ratio}')
log.write(f'dataset_root: {opt.train_data}\nopt.select_data: {opt.select_data}\nopt.batch_ratio: {opt.batch_ratio}\n')
assert len(opt.select_data) == len(opt.batch_ratio)
opt.batch_ratio = [float(x) for x in opt.batch_ratio]
assert np.sum(opt.batch_ratio) == 1.0

_AlignCollate = AlignCollate(imgH=opt.imgH, imgW=opt.imgW, keep_ratio_with_pad=opt.PAD)
self.data_loader_list = []
self.dataloader_iter_list = []
batch_size_list = []
Total_batch_size = 0
for selected_d, batch_ratio_d in zip(opt.select_data, opt.batch_ratio):
_batch_size = max(round(opt.batch_size * float(batch_ratio_d)), 1)
_batch_size = max(round(opt.batch_size * batch_ratio_d), 1)
print(dashed_line)
log.write(dashed_line + '\n')
_dataset, _dataset_log = hierarchical_dataset(root=opt.train_data, opt=opt, select_data=[selected_d])
Expand All @@ -54,7 +56,7 @@ def __init__(self, opt):
_dataset, _ = [Subset(_dataset, indices[offset - length:offset])
for offset, length in zip(_accumulate(dataset_split), dataset_split)]
selected_d_log = f'num total samples of {selected_d}: {total_number_dataset} x {opt.total_data_usage_ratio} (total_data_usage_ratio) = {len(_dataset)}\n'
selected_d_log += f'num samples of {selected_d} per batch: {opt.batch_size} x {float(batch_ratio_d)} (batch_ratio) = {_batch_size}'
selected_d_log += f'num samples of {selected_d} per batch: {opt.batch_size} x {batch_ratio_d} (batch_ratio) = {_batch_size}'
print(selected_d_log)
log.write(selected_d_log + '\n')
batch_size_list.append(str(_batch_size))
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