PyTensor utils

compile_pymc(inputs, outputs[, random_seed, ...])	Use pytensor.function with specialized pymc rewrites always enabled.
gradient(f[, vars])
hessian(f[, vars])
hessian_diag(f[, vars])
jacobian(f[, vars])
inputvars(a)	Get the inputs into PyTensor variables
cont_inputs(a)	Get the continuous inputs into PyTensor variables
floatX(X)	Convert an PyTensor tensor or numpy array to pytensor.config.floatX type.
intX(X)	Convert a pytensor tensor or numpy array to pytensor.tensor.int32 type.
smartfloatX(x)	Converts numpy float values to floatX and leaves values of other types unchanged.
constant_fold(xs[, raise_not_constant])	Use constant folding to get constant values of a graph.
CallableTensor(tensor)	Turns a symbolic variable with one input into a function that returns symbolic arguments with the one variable replaced with the input.
join_nonshared_inputs(point, outputs, inputs)	Create new outputs and input TensorVariables where the non-shared inputs are joined in a single raveled vector input.
make_shared_replacements(point, vars, model)	Makes shared replacements for all other variables than the ones passed.
generator(gen[, default])	Generator variable with possibility to set default value and new generator.
convert_observed_data(data)	Convert user provided dataset to accepted formats.