View source on GitHub
|
Compute the cross-correlation of two 1-dimensional tensors.
tf.keras.ops.correlate(
x1, x2, mode='valid'
)
Returns | |
|---|---|
Output tensor, cross-correlation of x1 and x2.
|
tf.keras.ops.correlate
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Last updated 2024-06-07 UTC.
[null,null,["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.ops.correlate\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/ops/numpy.py#L6079-L6098) |\n\nCompute the cross-correlation of two 1-dimensional tensors.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.keras.ops.numpy.correlate`](https://www.tensorflow.org/api_docs/python/tf/keras/ops/correlate)\n\n\u003cbr /\u003e\n\n tf.keras.ops.correlate(\n x1, x2, mode='valid'\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `x1` | First 1-dimensional input tensor of length M. |\n| `x2` | Second 1-dimensional input tensor of length N. |\n| `mode` | Either `valid`, `same` or `full`. By default the mode is set to `valid`, which returns an output of length max(M, N) - min(M, N) + 1. `same` returns an output of length max(M, N). `full` mode returns the convolution at each point of overlap, with an output length of N+M-1 |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| Output tensor, cross-correlation of `x1` and `x2`. ||\n\n\u003cbr /\u003e"]]