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@@ -112,12 +112,12 @@ def sequence_mask(lengths, maxlen): |
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If lengths has shape [d_1, d_2, ..., d_n], then the resulting tensor mask has type dtype and shape |
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[d_1, d_2, ..., d_n, maxlen], with mask[i_1, i_2, ..., i_n, j] = (j < lengths[i_1, i_2, ..., i_n]) |
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Args: |
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length (Tensor): Tensor to calculate the mask for. All values in this tensor must be |
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Inputs: |
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- **lengths** (Tensor) - Tensor to calculate the mask for. All values in this tensor must be |
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less than or equal to `maxlen`. Must be type int32 or int64. |
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maxlen (int): size of the last dimension of returned tensor. Must be positive and same |
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type as elements in `lengths`. |
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- **maxlen** (int) - size of the last dimension of returned tensor. Must be positive and same |
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type as elements in `lengths`. Default is the maximum value in lengths. |
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Outputs: |
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One mask tensor of shape lengths.shape + (maxlen,). |
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@@ -126,9 +126,8 @@ def sequence_mask(lengths, maxlen): |
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``GPU`` |
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Examples: |
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>>> x = Tensor(np.array([[1, 3], [2, 0]]) |
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>>> sequence_mask = P.SequenceMask() |
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>>> output = sequence_mask(x, 3) |
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>>> x = Tensor(np.array([[1, 3], [2, 0]])) |
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>>> output = C.sequence_mask(x, 3) |
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>>> print(output) |
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[[[True, False, False], |
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[True, True, True]], |
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