org.apache.clojure-mxnet.ndarray
%
(% ndarray num-or-ndarray)
%=
(%= ndarray num-or-ndarray)
*
(* ndarray ndarray-or-num)
**
(** ndarray num-or-ndarray)
**=
(**= ndarray ndarray-or-num)
*=
(*= ndarray ndarray-or-num)
+
(+ ndarray ndarray-or-num)
+=
(+= ndarray num-or-ndarray)
-
(- ndarray ndarray-or-num)
-=
(-= ndarray ndarray-or-num)
->byte-vec
(->byte-vec ndarray)
->double-vec
(->double-vec ndarray)
->float-vec
(->float-vec ndarray)
->int-vec
(->int-vec ndarray)
->vec
(->vec ndarray)
Converts a nd-array to a vector (one dimensional)
/
(/ ndarray num-or-NDArray)
<
(< ndarray ndarray-or-num)
<=
(<= ndarray ndarray-or-num)
>
(> ndarray ndarray-or-num)
>=
(>= ndarray ndarray-or-num)
abs
(abs & nd-array-and-params)
activation
(activation & nd-array-and-params)
adam-update
(adam-update & nd-array-and-params)
add-n
(add-n & nd-array-and-params)
arange
(arange start stop {:keys [step repeat ctx dtype], :or {step (float 1), repeat (int 1), ctx (mx-context/default-context), dtype base/MX_REAL_TYPE}, :as opts})(arange start stop)
Returns evenly spaced values within a given interval.
Values are generated within the half-open interval [`start`, `stop`). In other
words, the interval includes `start` but excludes `stop`.
arccos
(arccos & nd-array-and-params)
arccosh
(arccosh & nd-array-and-params)
arcsin
(arcsin & nd-array-and-params)
arcsinh
(arcsinh & nd-array-and-params)
arctan
(arctan & nd-array-and-params)
arctanh
(arctanh & nd-array-and-params)
argmax
(argmax & nd-array-and-params)
argmax-channel
(argmax-channel & nd-array-and-params)
argmin
(argmin & nd-array-and-params)
argsort
(argsort & nd-array-and-params)
array
(array source-vec shape-vec {:keys [ctx dtype], :or {ctx (mx-context/default-context)}, :as opts})(array source-vec shape-vec)
Create a new NDArray that copies content from source vector
as-in-context
(as-in-context ndarray ctx)
Return an `NDArray` that lives in the target context. If the array
is already in that context, `self` is returned. Otherwise, a copy is made.
as-type
(as-type ndarray dtype)
Return a copied numpy array of current array with specified type.
batch-dot
(batch-dot & nd-array-and-params)
batch-norm
(batch-norm & nd-array-and-params)
batch-norm-v1
(batch-norm-v1 & nd-array-and-params)
batch-take
(batch-take & nd-array-and-params)
bilinear-sampler
(bilinear-sampler & nd-array-and-params)
block-grad
(block-grad & nd-array-and-params)
broadcast-add
(broadcast-add & nd-array-and-params)
broadcast-axes
(broadcast-axes & nd-array-and-params)
broadcast-axis
(broadcast-axis & nd-array-and-params)
broadcast-div
(broadcast-div & nd-array-and-params)
broadcast-equal
(broadcast-equal & nd-array-and-params)
broadcast-greater
(broadcast-greater & nd-array-and-params)
broadcast-greater-equal
(broadcast-greater-equal & nd-array-and-params)
broadcast-hypot
(broadcast-hypot & nd-array-and-params)
broadcast-lesser
(broadcast-lesser & nd-array-and-params)
broadcast-lesser-equal
(broadcast-lesser-equal & nd-array-and-params)
broadcast-like
(broadcast-like & nd-array-and-params)
broadcast-logical-and
(broadcast-logical-and & nd-array-and-params)
broadcast-logical-or
(broadcast-logical-or & nd-array-and-params)
broadcast-logical-xor
(broadcast-logical-xor & nd-array-and-params)
broadcast-maximum
(broadcast-maximum & nd-array-and-params)
broadcast-minimum
(broadcast-minimum & nd-array-and-params)
broadcast-minus
(broadcast-minus & nd-array-and-params)
broadcast-mod
(broadcast-mod & nd-array-and-params)
broadcast-mul
(broadcast-mul & nd-array-and-params)
broadcast-not-equal
(broadcast-not-equal & nd-array-and-params)
broadcast-plus
(broadcast-plus & nd-array-and-params)
broadcast-power
(broadcast-power & nd-array-and-params)
broadcast-sub
(broadcast-sub & nd-array-and-params)
broadcast-to
(broadcast-to & nd-array-and-params)
bytes-allocated
(bytes-allocated ndarray)
cast
(cast & nd-array-and-params)
cast-storage
(cast-storage & nd-array-and-params)
cbrt
(cbrt & nd-array-and-params)
ceil
(ceil & nd-array-and-params)
choose-element-0index
(choose-element-0index & nd-array-and-params)
clip
(clip & nd-array-and-params)
concat
(concat & nd-array-and-params)
concatenate
(concatenate ndarrays {:keys [axis always-copy], :or {axis 1, always-copy true}})(concatenate ndarrays)
convolution
(convolution & nd-array-and-params)
convolution-v1
(convolution-v1 & nd-array-and-params)
copy-to
(copy-to source-ndarray target-ndarray)
Copy the content of current array to other
correlation
(correlation & nd-array-and-params)
cos
(cos & nd-array-and-params)
cosh
(cosh & nd-array-and-params)
creation-trace
(creation-trace ndarray)
crop
(crop & nd-array-and-params)
ctc-loss
(ctc-loss & nd-array-and-params)
custom
(custom & nd-array-and-params)
deconvolution
(deconvolution & nd-array-and-params)
degrees
(degrees & nd-array-and-params)
dependencies
(dependencies ndarray)
depth-to-space
(depth-to-space & nd-array-and-params)
deserialize
(deserialize byte-array)
diag
(diag & nd-array-and-params)
dispose
(dispose ndarray)(dispose ndarray bool)
dispose-deps
(dispose-deps ndarray)
dispose-deps-except
(dispose-deps-except ndarray & nd-array-and-params)
div
(div ndarray num-or-ndarray)
div=
(div= ndarray num-or-ndarray)
dot
(dot & nd-array-and-params)
dropout
(dropout & nd-array-and-params)
element-wise-sum
(element-wise-sum & nd-array-and-params)
elemwise-add
(elemwise-add & nd-array-and-params)
elemwise-div
(elemwise-div & nd-array-and-params)
elemwise-mul
(elemwise-mul & nd-array-and-params)
elemwise-sub
(elemwise-sub & nd-array-and-params)
embedding
(embedding & nd-array-and-params)
empty
(empty shape-vec {:keys [ctx dtype], :or {ctx (mx-context/default-context), dtype base/MX_REAL_TYPE}, :as opts})(empty shape-vec)
Create an empty uninitialized new NDArray, with specified shape
equal
(equal ndarray-or-ndarray ndarray-or-num)
equals
(equals ndarray Object)
erf
(erf & nd-array-and-params)
exp
(exp & nd-array-and-params)
expand-dims
(expand-dims & nd-array-and-params)
expm1
(expm1 & nd-array-and-params)
fill-element-0index
(fill-element-0index & nd-array-and-params)
finalize
(finalize ndarray)
fix
(fix & nd-array-and-params)
flatten
(flatten & nd-array-and-params)
flip
(flip & nd-array-and-params)
floor
(floor & nd-array-and-params)
ftml-update
(ftml-update & nd-array-and-params)
ftrl-update
(ftrl-update & nd-array-and-params)
full
(full shape-vec value {:keys [ctx dtype], :or {ctx (mx-context/default-context)}, :as opts})(full shape-vec value)
Create a new NDArray filled with given value, with specified shape.
fully-connected
(fully-connected & nd-array-and-params)
gamma
(gamma & nd-array-and-params)
gammaln
(gammaln & nd-array-and-params)
gather-nd
(gather-nd & nd-array-and-params)
greater
(greater ndarray-or-ndarray ndarray-or-num)
greater-equal
(greater-equal ndarray-or-ndarray num-or-ndarray)
grid-generator
(grid-generator & nd-array-and-params)
hard-sigmoid
(hard-sigmoid & nd-array-and-params)
hash-code
(hash-code ndarray)
identity
(identity & nd-array-and-params)
identity-attach-kl-sparse-reg
(identity-attach-kl-sparse-reg & nd-array-and-params)
instance-norm
(instance-norm & nd-array-and-params)
internal
(internal ndarray)
is-de-allocated
(is-de-allocated ndarray)
is-disposed
(is-disposed ndarray)
khatri-rao
(khatri-rao & nd-array-and-params)
l2-normalization
(l2-normalization & nd-array-and-params)
layer-norm
(layer-norm & nd-array-and-params)
leaky-re-lu
(leaky-re-lu & nd-array-and-params)
lesser
(lesser ndarray-or-ndarray ndarray-or-num)
lesser-equal
(lesser-equal ndarray-or-ndarray ndarray-or-num)
linalg-gelqf
(linalg-gelqf & nd-array-and-params)
linalg-gemm
(linalg-gemm & nd-array-and-params)
linalg-gemm2
(linalg-gemm2 & nd-array-and-params)
linalg-potrf
(linalg-potrf & nd-array-and-params)
linalg-potri
(linalg-potri & nd-array-and-params)
linalg-sumlogdiag
(linalg-sumlogdiag & nd-array-and-params)
linalg-syrk
(linalg-syrk & nd-array-and-params)
linalg-trmm
(linalg-trmm & nd-array-and-params)
linalg-trsm
(linalg-trsm & nd-array-and-params)
linear-regression-output
(linear-regression-output & nd-array-and-params)
load
(load filename)
Takes a filename and returns back a map of ndarray-name to ndarray
load-from-file
(load-from-file fname)
Load one ndarry from a file
load2-array
(load2-array String)
load2-map
(load2-map String)
log
(log & nd-array-and-params)
log-dispose-warning
(log-dispose-warning ndarray)
log-softmax
(log-softmax & nd-array-and-params)
log10
(log10 & nd-array-and-params)
log1p
(log1p & nd-array-and-params)
log2
(log2 & nd-array-and-params)
logical-not
(logical-not & nd-array-and-params)
logistic-regression-output
(logistic-regression-output & nd-array-and-params)
lrn
(lrn & nd-array-and-params)
mae-regression-output
(mae-regression-output & nd-array-and-params)
make-loss
(make-loss & nd-array-and-params)
max
(max & nd-array-and-params)
max-axis
(max-axis & nd-array-and-params)
maximum
(maximum num-or-ndarray-or-ndarray ndarray-or-num-or-ndarray)
mean
(mean & nd-array-and-params)
min
(min & nd-array-and-params)
min-axis
(min-axis & nd-array-and-params)
minimum
(minimum ndarray-or-ndarray-or-num num-or-ndarray-or-ndarray)
mp-sgd-mom-update
(mp-sgd-mom-update & nd-array-and-params)
mp-sgd-update
(mp-sgd-update & nd-array-and-params)
nanprod
(nanprod & nd-array-and-params)
nansum
(nansum & nd-array-and-params)
native-address
(native-address ndarray)
native-de-allocator
(native-de-allocator ndarray)
negative
(negative & nd-array-and-params)
norm
(norm & nd-array-and-params)
normal
(normal & nd-array-and-params)
not-equal
(not-equal ndarray-or-ndarray num-or-ndarray)
one-hot
(one-hot & nd-array-and-params)
onehot-encode
(onehot-encode ndarray ndarray-1)
ones
(ones shape-vec {:keys [ctx dtype], :or {ctx (mx-context/default-context), dtype base/MX_REAL_TYPE}, :as opts})(ones shape-vec)
Create a new NDArray filled with 1, with specified shape.
ones-like
(ones-like & nd-array-and-params)
org.apache.mxnet.nd-array
(org.apache.mxnet.nd-array ndarray long bool bool-1)
pad
(pad & nd-array-and-params)
pick
(pick & nd-array-and-params)
pooling
(pooling & nd-array-and-params)
pooling-v1
(pooling-v1 & nd-array-and-params)
power
(power num-or-ndarray-or-ndarray ndarray-or-num-or-ndarray)
prod
(prod & nd-array-and-params)
radians
(radians & nd-array-and-params)
random-exponential
(random-exponential & nd-array-and-params)
random-gamma
(random-gamma & nd-array-and-params)
random-generalized-negative-binomial
(random-generalized-negative-binomial & nd-array-and-params)
random-negative-binomial
(random-negative-binomial & nd-array-and-params)
random-normal
(random-normal & nd-array-and-params)
random-poisson
(random-poisson & nd-array-and-params)
random-randint
(random-randint & nd-array-and-params)
ravel-multi-index
(ravel-multi-index & nd-array-and-params)
rcbrt
(rcbrt & nd-array-and-params)
reciprocal
(reciprocal & nd-array-and-params)
register
(register ndarray)
relu
(relu & nd-array-and-params)
repeat
(repeat & nd-array-and-params)
reshape
(reshape ndarray Shape-or-vec-of-ints)
reshape-like
(reshape-like & nd-array-and-params)
reverse
(reverse & nd-array-and-params)
rint
(rint & nd-array-and-params)
rmsprop-update
(rmsprop-update & nd-array-and-params)
rmspropalex-update
(rmspropalex-update & nd-array-and-params)
rnn
(rnn & nd-array-and-params)
roi-pooling
(roi-pooling & nd-array-and-params)
round
(round & nd-array-and-params)
rsqrt
(rsqrt & nd-array-and-params)
sample-exponential
(sample-exponential & nd-array-and-params)
sample-gamma
(sample-gamma & nd-array-and-params)
sample-generalized-negative-binomial
(sample-generalized-negative-binomial & nd-array-and-params)
sample-multinomial
(sample-multinomial & nd-array-and-params)
sample-negative-binomial
(sample-negative-binomial & nd-array-and-params)
sample-normal
(sample-normal & nd-array-and-params)
sample-poisson
(sample-poisson & nd-array-and-params)
save
(save fname map-of-name-to-ndarray)
Save list of NDArray or dict of str->NDArray to binary file
(The name of the file.Can be S3 or HDFS address (remember built with S3 support))
Example of fname:
* - `s3://my-bucket/path/my-s3-ndarray`
* - `hdfs://my-bucket/path/my-hdfs-ndarray`
* - `/path-to/my-local-ndarray`
save-to-file
(save-to-file fname ndarray)
Save one ndarray to a file
scatter-nd
(scatter-nd & nd-array-and-params)
scope-=
(scope-= ndarray Option)
sequence-last
(sequence-last & nd-array-and-params)
sequence-mask
(sequence-mask & nd-array-and-params)
sequence-reverse
(sequence-reverse & nd-array-and-params)
serialize
(serialize ndarray)
set
(set ndarray ndarray-or-num-or-vec-of-floats)
sgd-mom-update
(sgd-mom-update & nd-array-and-params)
sgd-update
(sgd-update & nd-array-and-params)
shape-array
(shape-array & nd-array-and-params)
shape-vec
(shape-vec ndarray)
shuffle
(shuffle & nd-array-and-params)
sigmoid
(sigmoid & nd-array-and-params)
sign
(sign & nd-array-and-params)
signsgd-update
(signsgd-update & nd-array-and-params)
signum-update
(signum-update & nd-array-and-params)
sin
(sin & nd-array-and-params)
sinh
(sinh & nd-array-and-params)
size-array
(size-array & nd-array-and-params)
slice
(slice ndarray i)(slice ndarray start stop)
Return a sliced NDArray that shares memory with current one.
slice-axis
(slice-axis & nd-array-and-params)
slice-channel
(slice-channel & nd-array-and-params)
slice-like
(slice-like & nd-array-and-params)
smooth-l1
(smooth-l1 & nd-array-and-params)
softmax
(softmax & nd-array-and-params)
softmax-activation
(softmax-activation & nd-array-and-params)
softmax-cross-entropy
(softmax-cross-entropy & nd-array-and-params)
softmax-output
(softmax-output & nd-array-and-params)
softmin
(softmin & nd-array-and-params)
softsign
(softsign & nd-array-and-params)
sort
(sort & nd-array-and-params)
space-to-depth
(space-to-depth & nd-array-and-params)
split
(split & nd-array-and-params)
sqrt
(sqrt & nd-array-and-params)
square
(square & nd-array-and-params)
squeeze
(squeeze & nd-array-and-params)
stack
(stack & nd-array-and-params)
stop-gradient
(stop-gradient & nd-array-and-params)
sum
(sum & nd-array-and-params)
sum-axis
(sum-axis & nd-array-and-params)
svm-output
(svm-output & nd-array-and-params)
swap-axis
(swap-axis & nd-array-and-params)
swapaxes
(swapaxes & nd-array-and-params)
take
(take & nd-array-and-params)
tan
(tan & nd-array-and-params)
tanh
(tanh & nd-array-and-params)
tile
(tile & nd-array-and-params)
to-array
(to-array ndarray)
to-scalar
(to-scalar ndarray)
topk
(topk & nd-array-and-params)
tracing-enabled
(tracing-enabled ndarray)
transpose
(transpose & nd-array-and-params)
trunc
(trunc & nd-array-and-params)
unravel-index
(unravel-index & nd-array-and-params)
up-sampling
(up-sampling & nd-array-and-params)
wait-to-read
(wait-to-read ndarray)
where
(where & nd-array-and-params)
writable
(writable ndarray)
zeros
(zeros shape-vec {:keys [ctx dtype], :or {ctx (mx-context/default-context), dtype base/MX_REAL_TYPE}, :as opts})(zeros shape-vec)
Create a new NDArray filled with 0, with specified shape.
zeros-like
(zeros-like & nd-array-and-params)