module Tensorflow::Math
Public Class Methods
abs(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 4 def abs(x, dtype: nil) RawOps.abs(x, typeT: dtype) end
acos(x, dtype: nil)
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def accumulate_n end
# File lib/tensorflow/ops/math.rb, line 11 def acos(x, dtype: nil) RawOps.acos(x, typeT: dtype) end
acosh(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 15 def acosh(x, dtype: nil) RawOps.acosh(x, typeT: dtype) end
add(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 19 def add(x, y, dtype: nil) RawOps.add(x, y, typeT: dtype) end
add_n(inputs, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 23 def add_n(inputs, dtype: nil) RawOps.add_n(inputs, n: inputs.length, typeT: dtype) end
angle(input, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 27 def angle(input, dtype: nil) RawOps.angle(input, typeT: dtype) end
asin(x, dtype: nil)
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def argmin end
# File lib/tensorflow/ops/math.rb, line 37 def asin(x, dtype: nil) RawOps.asin(x, typeT: dtype) end
asinh(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 41 def asinh(x, dtype: nil) RawOps.asinh(x, typeT: dtype) end
atan(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 45 def atan(x, dtype: nil) RawOps.atan(x, typeT: dtype) end
atan2(y, x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 49 def atan2(y, x, dtype: nil) RawOps.atan2(y, x, typeT: dtype) end
atanh(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 53 def atanh(x, dtype: nil) RawOps.atanh(x, typeT: dtype) end
bessel_i0e(x, dtype: nil)
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def bessel_i0 end
# File lib/tensorflow/ops/math.rb, line 60 def bessel_i0e(x, dtype: nil) RawOps.bessel_i0e(x, typeT: dtype) end
bessel_i1e(x, dtype: nil)
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def bessel_i1 end
# File lib/tensorflow/ops/math.rb, line 67 def bessel_i1e(x, dtype: nil) RawOps.bessel_i1e(x, typeT: dtype) end
betainc(a, b, x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 71 def betainc(a, b, x, dtype: nil) RawOps.betainc(a, b, x, typeT: dtype) end
bincount(arr, size, weights, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 75 def bincount(arr, size, weights, dtype: nil) RawOps.bincount(arr, size, weights, typeT: dtype) end
ceil(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 79 def ceil(x, dtype: nil) RawOps.ceil(x, typeT: dtype) end
conj(input, dtype: nil)
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def confusion_matrix end
# File lib/tensorflow/ops/math.rb, line 86 def conj(input, dtype: nil) RawOps.conj(input, typeT: dtype) end
cos(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 90 def cos(x, dtype: nil) RawOps.cos(x, typeT: dtype) end
cosh(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 94 def cosh(x, dtype: nil) RawOps.cosh(x, typeT: dtype) end
cumprod(x, axis, exclusive: nil, reverse: nil, dtype: nil)
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def count_nonzero end
# File lib/tensorflow/ops/math.rb, line 101 def cumprod(x, axis, exclusive: nil, reverse: nil, dtype: nil) RawOps.cumprod(x, axis, exclusive: exclusive, reverse: reverse, typeT: dtype) end
cumsum(x, axis, exclusive: nil, reverse: nil, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 105 def cumsum(x, axis, exclusive: nil, reverse: nil, dtype: nil) RawOps.cumsum(x, axis, exclusive: exclusive, reverse: reverse, typeT: dtype) end
digamma(x, dtype: nil)
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def cumulative_logsumexp end
# File lib/tensorflow/ops/math.rb, line 112 def digamma(x, dtype: nil) RawOps.digamma(x, typeT: dtype) end
divide(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 116 def divide(x, y, dtype: nil) RawOps.div(x, y, typeT: dtype) end
equal(x, y, dtype: nil)
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def divide_no_nan end
# File lib/tensorflow/ops/math.rb, line 123 def equal(x, y, dtype: nil) RawOps.equal(x, y, typeT: dtype) end
erf(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 127 def erf(x, dtype: nil) RawOps.erf(x, typeT: dtype) end
erfc(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 131 def erfc(x, dtype: nil) RawOps.erfc(x, typeT: dtype) end
exp(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 135 def exp(x, dtype: nil) RawOps.exp(x, typeT: dtype) end
expm1(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 139 def expm1(x, dtype: nil) RawOps.expm1(x, typeT: dtype) end
floor(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 143 def floor(x, dtype: nil) RawOps.floor(x, typeT: dtype) end
floordiv(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 147 def floordiv(x, y, dtype: nil) RawOps.floor_div(x, y, typeT: dtype) end
floormod(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 151 def floormod(x, y, dtype: nil) RawOps.floor_mod(x, y, typeT: dtype) end
greater(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 155 def greater(x, y, dtype: nil) RawOps.greater(x, y, typeT: dtype) end
greater_equal(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 159 def greater_equal(x, y, dtype: nil) RawOps.greater_equal(x, y, typeT: dtype) end
igamma(a, x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 163 def igamma(a, x, dtype: nil) RawOps.igamma(a, x, typeT: dtype) end
igammac(a, x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 167 def igammac(a, x, dtype: nil) RawOps.igammac(a, x, typeT: dtype) end
imag(input, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 171 def imag(input, dtype: nil) RawOps.imag(input, typeT: dtype) end
in_top_k(predictions, targets, k=nil, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 175 def in_top_k(predictions, targets, k=nil, dtype: nil) RawOps.in_top_kv2(predictions, targets, k, typeT: dtype) end
invert_permutation(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 179 def invert_permutation(x, dtype: nil) RawOps.invert_permutation(x, typeT: dtype) end
is_finite(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 183 def is_finite(x, dtype: nil) RawOps.is_finite(x, typeT: dtype) end
is_inf(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 187 def is_inf(x, dtype: nil) RawOps.is_inf(x, typeT: dtype) end
is_nan(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 191 def is_nan(x, dtype: nil) RawOps.is_nan(x, typeT: dtype) end
less(x, y, dtype: nil)
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def lbeta end
# File lib/tensorflow/ops/math.rb, line 207 def less(x, y, dtype: nil) RawOps.less(x, y, typeT: dtype) end
less_equal(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 211 def less_equal(x, y, dtype: nil) RawOps.less_equal(x, y, typeT: dtype) end
lgamma(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 215 def lgamma(x, dtype: nil) RawOps.lgamma(x, typeT: dtype) end
log(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 219 def log(x, dtype: nil) RawOps.log(x, typeT: dtype) end
log1p(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 223 def log1p(x, dtype: nil) RawOps.log1p(x, typeT: dtype) end
log_sigmoid(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 227 def log_sigmoid(x, dtype: nil) negative(RawOps.softplus(-x, typeT: nil), dtype: dtype) end
log_softmax(logits, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 231 def log_softmax(logits, dtype: nil) RawOps.log_softmax(logits: logits, typeT: dtype) end
logical_and(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 235 def logical_and(x, y, dtype: nil) RawOps.logical_and(x, y) end
logical_not(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 239 def logical_not(x, dtype: nil) RawOps.logical_not(x) end
logical_or(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 243 def logical_or(x, y, dtype: nil) RawOps.logical_or(x, y) end
logical_xor(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 247 def logical_xor(x, y, dtype: nil) logical_and(logical_or(x, y, dtype: nil), logical_not(logical_and(x, y, dtype: nil), dtype: nil)) end
maximum(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 251 def maximum(x, y, dtype: nil) RawOps.maximum(x, y, typeT: dtype) end
minimum(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 255 def minimum(x, y, dtype: nil) RawOps.minimum(x, y, typeT: dtype) end
mod(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 259 def mod(x, y, dtype: nil) RawOps.mod(x, y, typeT: dtype) end
multiply(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 263 def multiply(x, y, dtype: nil) RawOps.mul(x, y, typeT: dtype) end
multiply_no_nan(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 267 def multiply_no_nan(x, y, dtype: nil) RawOps.mul_no_nan(x, y, typeT: dtype) end
negative(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 271 def negative(x, dtype: nil) RawOps.neg(x, typeT: dtype) end
not_equal(x, y, dtype: nil)
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def nextafter end
# File lib/tensorflow/ops/math.rb, line 278 def not_equal(x, y, dtype: nil) RawOps.not_equal(x, y, typeT: dtype) end
polygamma(a, x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 282 def polygamma(a, x, dtype: nil) RawOps.polygamma(a, x, typeT: dtype) end
pow(x, y, dtype: nil)
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def polyval end
# File lib/tensorflow/ops/math.rb, line 289 def pow(x, y, dtype: nil) RawOps.pow(x, y, typeT: dtype) end
real(input, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 293 def real(input, dtype: nil) RawOps.real(input, typeT: dtype) end
reciprocal(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 297 def reciprocal(x, dtype: nil) RawOps.reciprocal(x, typeT: dtype) end
reduce_any(input, axis: nil, keepdims: false, dtype: nil)
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def reduce_all end
# File lib/tensorflow/ops/math.rb, line 307 def reduce_any(input, axis: nil, keepdims: false, dtype: nil) axis ||= reduction_dims(input, dtype: dtype) RawOps.any(input, axis, keep_dims: keepdims) end
reduce_max(input, axis: nil, keepdims: false, dtype: nil)
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def reduce_logsumexp end
# File lib/tensorflow/ops/math.rb, line 318 def reduce_max(input, axis: nil, keepdims: false, dtype: nil) axis ||= reduction_dims(input, dtype: dtype) RawOps.max(input, axis, keep_dims: keepdims, typeT: dtype) end
reduce_mean(input, axis: nil, keepdims: false, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 323 def reduce_mean(input, axis: nil, keepdims: false, dtype: nil) axis ||= reduction_dims(input, dtype: dtype) RawOps.mean(input, axis, keep_dims: keepdims, typeT: dtype) end
reduce_min(input, axis: nil, keepdims: false, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 328 def reduce_min(input, axis: nil, keepdims: false, dtype: nil) axis ||= reduction_dims(input, dtype: dtype) RawOps.min(input, axis, keep_dims: keepdims, typeT: dtype) end
reduce_prod(input, axis: nil, keepdims: false, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 333 def reduce_prod(input, axis: nil, keepdims: false, dtype: nil) axis ||= reduction_dims(input, dtype: dtype) RawOps.prod(input, axis, keep_dims: keepdims, typeT: dtype) end
reduce_std(input, axis: nil, keepdims: false, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 338 def reduce_std(input, axis: nil, keepdims: false, dtype: nil) variance = reduce_variance(input, axis: axis, keepdims: keepdims, dtype: dtype) sqrt(variance, dtype: dtype) end
reduce_sum(input, axis: nil, keepdims: false, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 343 def reduce_sum(input, axis: nil, keepdims: false, dtype: nil) axis ||= reduction_dims(input, dtype: dtype) RawOps.sum(input, axis, keep_dims: keepdims, typeT: dtype) end
reduce_variance(input, axis: nil, keepdims: false, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 348 def reduce_variance(input, axis: nil, keepdims: false, dtype: nil) means = reduce_mean(input, axis: axis, keepdims: true, dtype: dtype) squared_deviations = RawOps.square(input - means, typeT: dtype) reduce_mean(squared_deviations, axis: axis, keepdims: keepdims, dtype: dtype) end
rint(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 354 def rint(x, dtype: nil) RawOps.rint(x, typeT: dtype) end
round(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 358 def round(x, dtype: nil) RawOps.round(x, typeT: dtype) end
rsqrt(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 362 def rsqrt(x, dtype: nil) RawOps.rsqrt(x, typeT: dtype) end
segment_max(data, segment_ids, dtype: nil)
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def scalar_mul end
# File lib/tensorflow/ops/math.rb, line 369 def segment_max(data, segment_ids, dtype: nil) RawOps.segment_max(data, segment_ids, typeT: dtype) end
segment_mean(data, segment_ids, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 373 def segment_mean(data, segment_ids, dtype: nil) RawOps.segment_mean(data, segment_ids, typeT: dtype) end
segment_min(data, segment_ids, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 377 def segment_min(data, segment_ids, dtype: nil) RawOps.segment_min(data, segment_ids, typeT: dtype) end
segment_prod(data, segment_ids, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 381 def segment_prod(data, segment_ids, dtype: nil) RawOps.segment_prod(data, segment_ids, typeT: dtype) end
segment_sum(data, segment_ids, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 385 def segment_sum(data, segment_ids, dtype: nil) RawOps.segment_sum(data, segment_ids, typeT: dtype) end
sigmoid(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 389 def sigmoid(x, dtype: nil) RawOps.sigmoid(x, typeT: dtype) end
sign(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 393 def sign(x, dtype: nil) RawOps.sign(x, typeT: dtype) end
sin(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 397 def sin(x, dtype: nil) RawOps.sin(x, typeT: dtype) end
sinh(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 401 def sinh(x, dtype: nil) RawOps.sinh(x, typeT: dtype) end
softmax(logits, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 405 def softmax(logits, dtype: nil) RawOps.softmax(logits: logits, typeT: dtype) end
softplus(features, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 409 def softplus(features, dtype: nil) RawOps.softplus(features: features, typeT: dtype) end
softsign(features, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 413 def softsign(features, dtype: nil) RawOps.softsign(features: features, typeT: dtype) end
sqrt(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 417 def sqrt(x, dtype: nil) RawOps.sqrt(x, typeT: dtype) end
square(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 421 def square(x, dtype: nil) RawOps.square(x, typeT: dtype) end
squared_difference(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 425 def squared_difference(x, y, dtype: nil) RawOps.squared_difference(x, y, typeT: dtype) end
subtract(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 429 def subtract(x, y, dtype: nil) RawOps.sub(x, y, typeT: dtype) end
tan(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 433 def tan(x, dtype: nil) RawOps.tan(x, typeT: dtype) end
tanh(x, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 437 def tanh(x, dtype: nil) RawOps.tanh(x, typeT: dtype) end
top_k(input, k: nil, sorted: nil, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 441 def top_k(input, k: nil, sorted: nil, dtype: nil) RawOps.top_k(input, k: k, sorted: sorted, typeT: dtype) end
unsorted_segment_max(data, segment_ids, num_segments, dtype: nil)
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def truediv end
# File lib/tensorflow/ops/math.rb, line 448 def unsorted_segment_max(data, segment_ids, num_segments, dtype: nil) RawOps.unsorted_segment_max(data, segment_ids, num_segments: num_segments, typeT: dtype) end
unsorted_segment_min(data, segment_ids, num_segments, dtype: nil)
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def unsorted_segment_mean end
# File lib/tensorflow/ops/math.rb, line 455 def unsorted_segment_min(data, segment_ids, num_segments, dtype: nil) RawOps.unsorted_segment_min(data, segment_ids, num_segments: num_segments, typeT: dtype) end
unsorted_segment_prod(data, segment_ids, num_segments, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 459 def unsorted_segment_prod(data, segment_ids, num_segments, dtype: nil) RawOps.unsorted_segment_prod(data, segment_ids, num_segments: num_segments, typeT: dtype) end
unsorted_segment_sum(data, segment_ids, num_segments, dtype: nil)
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def unsorted_segment_sqrt_n end
# File lib/tensorflow/ops/math.rb, line 466 def unsorted_segment_sum(data, segment_ids, num_segments, dtype: nil) RawOps.unsorted_segment_sum(data, segment_ids, num_segments: num_segments, typeT: dtype) end
xdivy(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 470 def xdivy(x, y, dtype: nil) RawOps.xdivy(x, y, typeT: dtype) end
xlogy(x, y, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 474 def xlogy(x, y, dtype: nil) RawOps.xlogy(x, y, typeT: dtype) end
zeta(x, q, dtype: nil)
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def zero_fraction end
# File lib/tensorflow/ops/math.rb, line 481 def zeta(x, q, dtype: nil) RawOps.zeta(x, q, typeT: dtype) end
Private Class Methods
reduction_dims(input, dtype: nil)
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# File lib/tensorflow/ops/math.rb, line 487 def reduction_dims(input, dtype: nil) rank = Tensorflow.rank(input, typeT: dtype) range = Tensorflow.range(0, rank) end