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301 lines
4.2 KiB
ReStructuredText
301 lines
4.2 KiB
ReStructuredText
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jax.numpy package
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=================
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.. currentmodule:: jax.numpy
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.. automodule:: jax.numpy
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Implements the NumPy API, using the primitives in :mod:`jax.lax`.
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While JAX tries to follow the NumPy API as closely as possible, sometimes JAX
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cannot follow NumPy exactly.
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* Notably, since JAX arrays are immutable, NumPy APIs that mutate arrays
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in-place cannot be implemented in JAX. However, often JAX is able to provide a
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alternative API that is purely functional. For example, instead of in-place
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array updates (:code:`x[i] = y`), JAX provides an alternative pure indexed
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update function :func:`jax.ops.index_update`.
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* NumPy is very aggressive at promoting values to :code:`float64` type. JAX
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sometimes is less aggressive about type promotion.
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A small number of NumPy operations that have data-dependent output shapes are
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incompatible with :func:`jax.jit` compilation. The XLA compiler requires that
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shapes of arrays be known at compile time. While it would be possible to provide
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a JAX implementation of an API such as :func:`numpy.nonzero`, we would be unable
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to JIT-compile it because the shape of its output depends on the contents of the
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input data.
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Not every function in NumPy is implemented; contributions are welcome!
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.. autosummary::
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:toctree: _autosummary
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abs
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absolute
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add
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all
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allclose
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alltrue
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amax
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amin
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angle
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any
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append
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arange
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arccos
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arccosh
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arcsin
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arcsinh
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arctan
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arctan2
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arctanh
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argmax
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argmin
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argsort
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around
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array
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array_repr
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array_str
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asarray
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atleast_1d
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atleast_2d
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atleast_3d
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bartlett
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bitwise_and
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bitwise_not
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bitwise_or
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bitwise_xor
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blackman
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block
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broadcast_arrays
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broadcast_to
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can_cast
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ceil
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clip
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column_stack
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concatenate
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conj
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conjugate
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corrcoef
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cos
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cosh
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count_nonzero
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cov
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cross
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cumsum
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cumprod
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cumproduct
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deg2rad
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degrees
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diag
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diag_indices
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diagonal
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divide
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divmod
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dot
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dsplit
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dstack
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einsum
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equal
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empty
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empty_like
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exp
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exp2
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expand_dims
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expm1
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eye
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fabs
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fix
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flip
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fliplr
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flipud
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float_power
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floor
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floor_divide
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fmod
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full
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full_like
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gcd
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geomspace
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greater
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greater_equal
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hamming
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hanning
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heaviside
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hsplit
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hstack
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hypot
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identity
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imag
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inner
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isclose
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iscomplex
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isfinite
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isinf
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isnan
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isneginf
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isposinf
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isreal
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isscalar
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issubdtype
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issubsctype
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ix_
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kaiser
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kron
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lcm
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left_shift
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less
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less_equal
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linspace
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log
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log10
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log1p
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log2
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logaddexp
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logaddexp2
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logical_and
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logical_not
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logical_or
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logical_xor
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logspace
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matmul
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max
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maximum
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mean
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median
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meshgrid
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min
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minimum
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mod
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moveaxis
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msort
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multiply
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nan_to_num
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nancumprod
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nancumsum
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nanmax
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nanmin
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nanprod
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nansum
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negative
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nextafter
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nonzero
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not_equal
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ones
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ones_like
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outer
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pad
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percentile
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polyval
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power
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positive
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prod
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product
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promote_types
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ptp
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quantile
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rad2deg
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radians
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ravel
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real
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reciprocal
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remainder
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repeat
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reshape
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result_type
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right_shift
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roll
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rot90
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round
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row_stack
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select
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sign
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signbit
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sin
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sinc
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sinh
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sometrue
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sort
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split
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sqrt
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square
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squeeze
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stack
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std
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subtract
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sum
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swapaxes
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take
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take_along_axis
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tan
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tanh
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tensordot
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tile
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trace
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transpose
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tri
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tril
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tril_indices
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triu
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triu_indices
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true_divide
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vander
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var
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vdot
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vsplit
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vstack
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where
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zeros
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zeros_like
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jax.numpy.fft
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-------------
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.. automodule:: jax.numpy.fft
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.. autosummary::
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:toctree: _autosummary
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fft
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ifft
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fft2
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ifft2
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fftn
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ifftn
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rfft
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irfft
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rfft2
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irfft2
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rfftn
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irfftn
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fftfreq
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rfftfreq
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fftshift
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ifftshift
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jax.numpy.linalg
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----------------
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.. automodule:: jax.numpy.linalg
|
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|
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.. autosummary::
|
|
:toctree: _autosummary
|
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cholesky
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det
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eig
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eigh
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eigvals
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eigvalsh
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inv
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matrix_power
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matrix_rank
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norm
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pinv
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qr
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slogdet
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solve
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svd
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