Function permute

Permutes the dimensions of the input according to a given pattern.

Useful for, e.g., connecting RNNs and convnets together.

Example:

const model = tf.sequential();
model.add(tf.layers.permute({
  dims: [2, 1],
  inputShape: [10, 64]
}));
console.log(model.outputShape);
// Now model's output shape is [null, 64, 10], where null is the
// unpermuted sample (batch) dimension.
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Input shape: Arbitrary. Use the configuration field inputShape when using this layer as the first layer in a model.

Output shape: Same rank as the input shape, but with the dimensions re-ordered (i.e., permuted) according to the dims configuration of this layer.

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