| | |
|---|
| | | return pad |
|---|
| | | |
|---|
| | | |
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| | | def pad_list_all_dim(xs, pad_value): |
|---|
| | | """Perform padding for the list of tensors. |
|---|
| | | |
|---|
| | | Args: |
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| | | xs (List): List of Tensors [(T_1, `*`), (T_2, `*`), ..., (T_B, `*`)]. |
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| | | pad_value (float): Value for padding. |
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| | | |
|---|
| | | Returns: |
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| | | Tensor: Padded tensor (B, Tmax, `*`). |
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| | | |
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| | | Examples: |
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| | | >>> x = [torch.ones(4), torch.ones(2), torch.ones(1)] |
|---|
| | | >>> x |
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| | | [tensor([1., 1., 1., 1.]), tensor([1., 1.]), tensor([1.])] |
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| | | >>> pad_list(x, 0) |
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| | | tensor([[1., 1., 1., 1.], |
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| | | [1., 1., 0., 0.], |
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| | | [1., 0., 0., 0.]]) |
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| | | |
|---|
| | | """ |
|---|
| | | n_batch = len(xs) |
|---|
| | | num_dim = len(xs[0].shape) |
|---|
| | | max_len_all_dim = [] |
|---|
| | | for i in range(num_dim): |
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| | | max_len_all_dim.append(max(x.size(i) for x in xs)) |
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| | | pad = xs[0].new(n_batch, *max_len_all_dim).fill_(pad_value) |
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| | | |
|---|
| | | for i in range(n_batch): |
|---|
| | | if num_dim == 1: |
|---|
| | | pad[i, : xs[i].size(0)] = xs[i] |
|---|
| | | elif num_dim == 2: |
|---|
| | | pad[i, : xs[i].size(0), : xs[i].size(1)] = xs[i] |
|---|
| | | elif num_dim == 3: |
|---|
| | | pad[i, : xs[i].size(0), : xs[i].size(1), : xs[i].size(2)] = xs[i] |
|---|
| | | else: |
|---|
| | | raise ValueError( |
|---|
| | | "pad_list_all_dim only support 1-D, 2-D and 3-D tensors, not {}-D.".format(num_dim) |
|---|
| | | ) |
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| | | |
|---|
| | | return pad |
|---|
| | | |
|---|
| | | |
|---|
| | | def make_pad_mask(lengths, xs=None, length_dim=-1, maxlen=None): |
|---|
| | | """Make mask tensor containing indices of padded part. |
|---|
| | | |
|---|
