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Add signatures for cumulative_prod
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# cumulative_prod
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## NumPy
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```
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numpy.cumprod(a, axis=None, dtype=None, out=None) → ndarray
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```
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## CuPy
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```
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cupy.cumprod(a, axis=None, dtype=None, out=None) → ndarray
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```
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## dask.array
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```
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dask.array.cumprod(x, axis=None, dtype=None, out=None, method='sequential') → ndarray
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```
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## JAX
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```
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jax.numpy.cumprod(a, axis=None, dtype=None, out=None) → ndarray
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```
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## MXNet
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```
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np.cumprod(a, axis=None, dtype=None, out=None) → ndarray
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```
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## PyTorch
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```
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torch.cumprod(input, dim, *, dtype=None, out=None) → Tensor
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```
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`dim` positional/kwarg argument is required.
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## TensorFlow
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```
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tf.math.cumprod(x, axis=0, exclusive=False, reverse=False, name=None) → Tensor
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```
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Uses `exclusive` kwarg to indicate whether to include the starting value and exclude the ending value

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