tf.signal.frame
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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
)
Used in the notebooks
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 |
|---|
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 [..., num_frames, frame_length, ...].
|
Raises |
|---|
ValueError
|
If frame_length, frame_step, pad_value, or axis are not
scalar.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.signal.frame\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/signal/shape_ops.py#L55-L231) |\n\nExpands `signal`'s `axis` dimension into frames of `frame_length`.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.signal.frame`](https://www.tensorflow.org/api_docs/python/tf/signal/frame)\n\n\u003cbr /\u003e\n\n tf.signal.frame(\n signal,\n frame_length,\n frame_step,\n pad_end=False,\n pad_value=0,\n axis=-1,\n name=None\n )\n\n### Used in the notebooks\n\n| Used in the tutorials |\n|-------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| - [Transfer Learning for the Audio Domain with TensorFlow Lite Model Maker](https://www.tensorflow.org/lite/models/modify/model_maker/audio_classification) |\n\nSlides a window of size `frame_length` over `signal`'s `axis` dimension\nwith a stride of `frame_step`, replacing the `axis` dimension with\n`[frames, frame_length]` frames.\n\nIf `pad_end` is True, window positions that are past the end of the `axis`\ndimension are padded with `pad_value` until the window moves fully past the\nend of the dimension. Otherwise, only window positions that fully overlap the\n`axis` dimension are produced.\n\n#### For example:\n\n # A batch size 3 tensor of 9152 audio samples.\n audio = tf.random.normal([3, 9152])\n\n # Compute overlapping frames of length 512 with a step of 180 (frames overlap\n # by 332 samples). By default, only 49 frames are generated since a frame\n # with start position j*180 for j \u003e 48 would overhang the end.\n frames = tf.signal.frame(audio, 512, 180)\n frames.shape.assert_is_compatible_with([3, 49, 512])\n\n # When pad_end is enabled, the final two frames are kept (padded with zeros).\n frames = tf.signal.frame(audio, 512, 180, pad_end=True)\n frames.shape.assert_is_compatible_with([3, 51, 512])\n\nIf the dimension along `axis` is N, and `pad_end=False`, the number of frames\ncan be computed by: \n\n num_frames = 1 + (N - frame_size) // frame_step\n\nIf `pad_end=True`, the number of frames can be computed by: \n\n num_frames = -(-N // frame_step) # ceiling division\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|----------------------------------------------------------------------------------------------------------------------------------------|\n| `signal` | A `[..., samples, ...]` `Tensor`. The rank and dimensions may be unknown. Rank must be at least 1. |\n| `frame_length` | The frame length in samples. An integer or scalar `Tensor`. |\n| `frame_step` | The frame hop size in samples. An integer or scalar `Tensor`. |\n| `pad_end` | Whether to pad the end of `signal` with `pad_value`. |\n| `pad_value` | An optional scalar `Tensor` to use where the input signal does not exist when `pad_end` is True. |\n| `axis` | A scalar integer `Tensor` indicating the axis to frame. Defaults to the last axis. Supports negative values for indexing from the end. |\n| `name` | An optional name for the operation. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of frames with shape `[..., num_frames, frame_length, ...]`. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|-------------------------------------------------------------------------|\n| `ValueError` | If `frame_length`, `frame_step`, `pad_value`, or `axis` are not scalar. |\n\n\u003cbr /\u003e"]]
View source on GitHub