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TensorFlow 1 version
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View source on GitHub
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Expands signal's axis dimension into frames of frame_length.
tf.signal.frame(
signal, frame_length, frame_step, pad_end=False, pad_value=0, axis=-1, name=None
)
Slides a window of size frame_length over signal's axis dimension
with a stride of frame_step, replacing the axis dimension with
[frames, frame_length] frames.
If pad_end is True, window positions that are past the end of the axis
dimension are padded with pad_value until the window moves fully past the
end of the dimension. Otherwise, only window positions that fully overlap the
axis dimension are produced.
For example:
# A batch size 3 tensor of 9152 audio samples.audio = tf.random.normal([3, 9152])# Compute overlapping frames of length 512 with a step of 180 (frames overlap# by 332 samples). By default, only 49 frames are generated since a frame# with start position j*180 for j > 48 would overhang the end.frames = tf.signal.frame(audio, 512, 180)frames.shape.assert_is_compatible_with([3, 49, 512])# When pad_end is enabled, the final two frames are kept (padded with zeros).frames = tf.signal.frame(audio, 512, 180, pad_end=True)frames.shape.assert_is_compatible_with([3, 51, 512])
If the dimension along axis is N, and pad_end=False, the number of frames
can be computed by:
num_frames = 1 + (N - frame_size) // frame_step
If pad_end=True, the number of frames can be computed by:
num_frames = -(-N // frame_step) # ceiling division
Args | |
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signal
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A [..., samples, ...] Tensor. The rank and dimensions
may be unknown. Rank must be at least 1.
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frame_length
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The frame length in samples. An integer or scalar Tensor.
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frame_step
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The frame hop size in samples. An integer or scalar Tensor.
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pad_end
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Whether to pad the end of signal with pad_value.
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pad_value
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An optional scalar Tensor to use where the input signal
does not exist when pad_end is True.
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axis
|
A scalar integer Tensor indicating the axis to frame. Defaults to
the last axis. Supports negative values for indexing from the end.
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name
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An optional name for the operation. |
Returns | |
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A Tensor of frames with shape [..., num_frames, frame_length, ...].
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Raises | |
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ValueError
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If frame_length, frame_step, pad_value, or axis are not
scalar.
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