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58 lines
2.0 KiB
58 lines
2.0 KiB
3 years ago
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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# Modified from espnet(https://github.com/espnet/espnet)
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import numpy
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class ChannelSelector():
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"""Select 1ch from multi-channel signal"""
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def __init__(self, train_channel="random", eval_channel=0, axis=1):
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self.train_channel = train_channel
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self.eval_channel = eval_channel
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self.axis = axis
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def __repr__(self):
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return ("{name}(train_channel={train_channel}, "
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"eval_channel={eval_channel}, axis={axis})".format(
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name=self.__class__.__name__,
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train_channel=self.train_channel,
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eval_channel=self.eval_channel,
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axis=self.axis, ))
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def __call__(self, x, train=True):
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# Assuming x: [Time, Channel] by default
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if x.ndim <= self.axis:
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# If the dimension is insufficient, then unsqueeze
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# (e.g [Time] -> [Time, 1])
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ind = tuple(
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slice(None) if i < x.ndim else None
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for i in range(self.axis + 1))
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x = x[ind]
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if train:
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channel = self.train_channel
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else:
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channel = self.eval_channel
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if channel == "random":
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ch = numpy.random.randint(0, x.shape[self.axis])
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else:
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ch = channel
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ind = tuple(
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slice(None) if i != self.axis else ch for i in range(x.ndim))
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return x[ind]
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