| | |
|---|
| | | mask_idc = np.random.choice(sz - min_len, num_mask, replace=False) |
|---|
| | | |
|---|
| | | mask_idc = np.asarray( |
|---|
| | | [ |
|---|
| | | mask_idc[j] + offset |
|---|
| | | for j in range(len(mask_idc)) |
|---|
| | | for offset in range(lengths[j]) |
|---|
| | | ] |
|---|
| | | [mask_idc[j] + offset for j in range(len(mask_idc)) for offset in range(lengths[j])] |
|---|
| | | ) |
|---|
| | | |
|---|
| | | mask_idcs.append(np.unique(mask_idc[mask_idc < sz])) |
|---|
| | |
|---|
| | | mask_idc = np.random.choice(mask_idc, min_len, replace=False) |
|---|
| | | if mask_dropout > 0: |
|---|
| | | num_holes = np.rint(len(mask_idc) * mask_dropout).astype(int) |
|---|
| | | mask_idc = np.random.choice( |
|---|
| | | mask_idc, len(mask_idc) - num_holes, replace=False |
|---|
| | | ) |
|---|
| | | mask_idc = np.random.choice(mask_idc, len(mask_idc) - num_holes, replace=False) |
|---|
| | | |
|---|
| | | mask[i, mask_idc] = True |
|---|
| | | |
|---|
