tf.signal.frame
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 50 frames are generated since the last
# 152 samples do not form a full frame.
frames = tf.signal.frame(audio, 512, 180)
frames.shape.assert_is_compatible_with([3, 50, 512])
# When pad_end is enabled, the final frame is kept (padded with zeros).
frames = tf.signal.frame(audio, 512, 180, pad_end=True)
frames.shape.assert_is_compatible_with([3, 51, 512])
| Args | |
|---|---|
signal |
A [..., samples, ...] Tensor. The rank and dimensions may be unknown. Rank must be at least 1. |
frame_length |
The frame length in samples. An integer or scalar Tensor. |
frame_step |
The frame hop size in samples. An integer or scalar Tensor. |
pad_end |
Whether to pad the end of signal with pad_value. |
pad_value |
An optional scalar Tensor to use where the input signal does not exist when pad_end is True. |
axis |
A scalar integer Tensor indicating the axis to frame. Defaults to the last axis. Supports negative values for indexing from the end. |
name |
An optional name for the operation. |
| Returns | |
|---|---|
A Tensor of frames with shape [..., frames, frame_length, ...]. |
| Raises | |
|---|---|
ValueError |
If frame_length, frame_step, pad_value, or axis are not scalar. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/signal/frame