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55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
# Copyright 2021 Xiaomi Corp. (authors: Mingshuang Luo)
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#
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# See ../../LICENSE for clarification regarding multiple authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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This script is to encodes the supervisions as Tuple list.
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The supervision tensor has shape ``(batch_size, 3)``.
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Its second dimension contains information about sequence index [0],
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start frames [1] and num frames [2].
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In GRID, the start frame of each audio sample is 0.
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"""
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import torch
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def encode_supervisions(nnet_output_shape: int, batch: dict):
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"""
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Args:
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nnet_output_shape:
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The shape of nnet_output, e.g: (N, T, D).
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batch:
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A batch of dataloader, it's a dict file
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including text and aud/vid arrays.
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Return:
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The tuple list of supervisions and the text in batch.
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"""
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N, T, D = nnet_output_shape
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supervisions_idx = torch.arange(0, N, dtype=torch.int32)
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supervisions_start_frame = torch.full((1, N), 0, dtype=torch.int32)[0]
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supervisions_num_frames = torch.full((1, N), T, dtype=torch.int32)[0]
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supervision_segments = torch.stack(
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(
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supervisions_idx,
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supervisions_start_frame,
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supervisions_num_frames,
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),
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1,
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)
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texts = batch["txt"]
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return supervision_segments, texts
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