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Computes the theoretical and numeric Jacobian of `f`.

With y = f(x), computes the theoretical and numeric Jacobian dy/dx.

`f` the function.
`x` a list arguments for the function
`delta` (optional) perturbation used to compute numeric Jacobian.

A pair of lists, where the first is a list of 2-d numpy arrays representing the theoretical Jacobians for each argument, and the second list is the numerical ones. Each 2-d array has "x_size" rows and "y_size" columns where "x_size" is the number of elements in the corresponding argument and "y_size" is the number of elements in f(x).

`ValueError` If result is empty but the gradient is nonzero.
`ValueError` If x is not list, but any other type.

#### Example:

``````@tf.function
def test_func(x):
return x*x

theoretical, numerical
# ((array([[2.]], dtype=float32),), (array([[2.000004]], dtype=float32),))
``````
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]