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/external/tensorflow/tensorflow/python/ops/parallel_for/
Darray_test.py42 x_i = array_ops.gather(x, i)
43 for y in [x, x_i]:
59 x_i = array_ops.gather(x, i)
60 return array_ops.shape(x_i), array_ops.shape(x_i, out_type=dtypes.int64)
68 x_i = array_ops.gather(x, i)
69 return array_ops.size(x_i), array_ops.size(x_i, out_type=dtypes.int64)
77 x_i = array_ops.gather(x, i)
78 return array_ops.rank(x_i)
87 x_i = array_ops.gather(x, i)
89 return array_ops.shape_n([x_i, x, y, y_i]), array_ops.shape_n(
[all …]
Dcontrol_flow_ops_test.py69 x_i = array_ops.gather(x, i)
70 return nn.top_k(x_i)
112 x_i = array_ops.gather(x, i)
113 vectorized_value = pfor_config.reduce_concat(x_i)
115 return x_i - mean_value
126 x_i = array_ops.gather(x, i)
127 return x_i - pfor_config.reduce_mean(x_i)
138 x_i = array_ops.gather(x, i)
139 return x_i - pfor_config.reduce_sum(x_i)
155 x_i = array_ops.gather(x, i)
[all …]
/external/tensorflow/tensorflow/core/util/
Dbcast.cc70 const int64 x_i = x[i]; // i-th dimension of x. in BCast() local
77 if (x_i == y_i) { in BCast()
79 o_i = x_i; in BCast()
83 } else if (x_i == 1) { in BCast()
92 o_i = x_i; in BCast()
94 by_i = x_i; in BCast()
105 if (curr == SAME && x_i == 1) { in BCast()
111 x_reshape_.push_back(x_i); in BCast()
122 x_reshape_.back() *= x_i; in BCast()
128 x_reshape_.push_back(x_i); in BCast()
/external/bouncycastle/bcprov/src/main/java/org/bouncycastle/math/raw/
DNat192.java282 int x_i = x[i] ^ Integer.MIN_VALUE; in gte() local
284 if (x_i < y_i) in gte()
286 if (x_i > y_i) in gte()
296 int x_i = x[xOff + i] ^ Integer.MIN_VALUE; in gte() local
298 if (x_i < y_i) in gte()
300 if (x_i > y_i) in gte()
396 long c = 0, x_i = x[i] & M; in mul() local
397 c += x_i * y_0 + (zz[i + 0] & M); in mul()
400 c += x_i * y_1 + (zz[i + 1] & M); in mul()
403 c += x_i * y_2 + (zz[i + 2] & M); in mul()
[all …]
DNat256.java380 int x_i = x[i] ^ Integer.MIN_VALUE; in gte() local
382 if (x_i < y_i) in gte()
384 if (x_i > y_i) in gte()
394 int x_i = x[xOff + i] ^ Integer.MIN_VALUE; in gte() local
396 if (x_i < y_i) in gte()
398 if (x_i > y_i) in gte()
502 long c = 0, x_i = x[i] & M; in mul() local
503 c += x_i * y_0 + (zz[i + 0] & M); in mul()
506 c += x_i * y_1 + (zz[i + 1] & M); in mul()
509 c += x_i * y_2 + (zz[i + 2] & M); in mul()
[all …]
DNat224.java301 int x_i = x[i] ^ Integer.MIN_VALUE; in gte() local
303 if (x_i < y_i) in gte()
305 if (x_i > y_i) in gte()
315 int x_i = x[xOff + i] ^ Integer.MIN_VALUE; in gte() local
317 if (x_i < y_i) in gte()
319 if (x_i > y_i) in gte()
391 long c = 0, x_i = x[i] & M; in mul() local
392 c += x_i * y_0 + (zz[i + 0] & M); in mul()
395 c += x_i * y_1 + (zz[i + 1] & M); in mul()
398 c += x_i * y_2 + (zz[i + 2] & M); in mul()
[all …]
DNat.java380 int x_i = x[i] ^ Integer.MIN_VALUE; in gte() local
382 if (x_i < y_i) in gte()
384 if (x_i > y_i) in gte()
1125 int x_i = x[i]; in toBigInteger() local
1126 if (x_i != 0) in toBigInteger()
1128 Pack.intToBigEndian(x_i, bs, (len - 1 - i) << 2); in toBigInteger()
/external/bouncycastle/repackaged/bcprov/src/main/java/com/android/org/bouncycastle/math/raw/
DNat192.java286 int x_i = x[i] ^ Integer.MIN_VALUE; in gte() local
288 if (x_i < y_i) in gte()
290 if (x_i > y_i) in gte()
300 int x_i = x[xOff + i] ^ Integer.MIN_VALUE; in gte() local
302 if (x_i < y_i) in gte()
304 if (x_i > y_i) in gte()
400 long c = 0, x_i = x[i] & M; in mul() local
401 c += x_i * y_0 + (zz[i + 0] & M); in mul()
404 c += x_i * y_1 + (zz[i + 1] & M); in mul()
407 c += x_i * y_2 + (zz[i + 2] & M); in mul()
[all …]
DNat256.java384 int x_i = x[i] ^ Integer.MIN_VALUE; in gte() local
386 if (x_i < y_i) in gte()
388 if (x_i > y_i) in gte()
398 int x_i = x[xOff + i] ^ Integer.MIN_VALUE; in gte() local
400 if (x_i < y_i) in gte()
402 if (x_i > y_i) in gte()
506 long c = 0, x_i = x[i] & M; in mul() local
507 c += x_i * y_0 + (zz[i + 0] & M); in mul()
510 c += x_i * y_1 + (zz[i + 1] & M); in mul()
513 c += x_i * y_2 + (zz[i + 2] & M); in mul()
[all …]
DNat224.java305 int x_i = x[i] ^ Integer.MIN_VALUE; in gte() local
307 if (x_i < y_i) in gte()
309 if (x_i > y_i) in gte()
319 int x_i = x[xOff + i] ^ Integer.MIN_VALUE; in gte() local
321 if (x_i < y_i) in gte()
323 if (x_i > y_i) in gte()
395 long c = 0, x_i = x[i] & M; in mul() local
396 c += x_i * y_0 + (zz[i + 0] & M); in mul()
399 c += x_i * y_1 + (zz[i + 1] & M); in mul()
402 c += x_i * y_2 + (zz[i + 2] & M); in mul()
[all …]
DNat.java384 int x_i = x[i] ^ Integer.MIN_VALUE; in gte() local
386 if (x_i < y_i) in gte()
388 if (x_i > y_i) in gte()
1129 int x_i = x[i]; in toBigInteger() local
1130 if (x_i != 0) in toBigInteger()
1132 Pack.intToBigEndian(x_i, bs, (len - 1 - i) << 2); in toBigInteger()
/external/tensorflow/tensorflow/contrib/distributions/python/ops/
Dconditional_transformed_distribution.py116 self._finish_log_prob_for_one_fiber(y, x_i, ildj_i, distribution_kwargs)
117 for x_i, ildj_i in zip(x, ildj)]
140 self._finish_prob_for_one_fiber(y, x_i, ildj_i, distribution_kwargs)
141 for x_i, ildj_i in zip(x, ildj)]
/external/tensorflow/tensorflow/contrib/tensor_forest/
DREADME.md57 each batch `{(x_i, y_i)}` of training data, the following steps are performed:
59 1. Given the current tree structure, each `x_i` is used to find the leaf
65 `num_splits_to_consider` splits, `x_i` is used to generate another split.
66 Specifically, a random feature value is chosen, and `x_i`'s value at that
69 4. Otherwise, `(x_i, y_i)` is used to update the statistics of every
/external/libxaac/decoder/
Dixheaacd_hbe_trans.c294 FLOAT32 x_r, x_i, temp; in ixheaacd_norm_qmf_in_buf_4() local
297 x_i = in_buf[1]; in ixheaacd_norm_qmf_in_buf_4()
301 temp = x_i * x_i; in ixheaacd_norm_qmf_in_buf_4()
310 x_i *= mag_scaling_fac; in ixheaacd_norm_qmf_in_buf_4()
313 norm_buf[1] = x_i; in ixheaacd_norm_qmf_in_buf_4()
333 FLOAT32 x_r, x_i, temp; in ixheaacd_norm_qmf_in_buf_2() local
336 x_i = in_buf[1]; in ixheaacd_norm_qmf_in_buf_2()
340 temp = x_i * x_i; in ixheaacd_norm_qmf_in_buf_2()
341 base = base + x_i * x_i; in ixheaacd_norm_qmf_in_buf_2()
347 x_i *= mag_scaling_fac; in ixheaacd_norm_qmf_in_buf_2()
[all …]
/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_ParallelDynamicStitch.pbtxt49 # Apply function (increments x_i) on elements for which a certain condition
50 # apply (x_i != -1 in this example).
Dapi_def_DynamicStitch.pbtxt50 # Apply function (increments x_i) on elements for which a certain condition
51 # apply (x_i != -1 in this example).
Dapi_def_SymbolicGradient.pbtxt45 to x_i.
/external/tensorflow/tensorflow/contrib/factorization/g3doc/
Dkmeans.md3 Given a set of input $$x_i$$, K-means clustering finds a set C of cluster
5 C} (||x_i - \mu_j||^2) $$.
/external/tensorflow/tensorflow/python/ops/distributions/
Dtransformed_distribution.py435 self._finish_log_prob_for_one_fiber(y, x_i, ildj_i, event_ndims)
436 for x_i, ildj_i in zip(x, ildj)]
461 self._finish_prob_for_one_fiber(y, x_i, ildj_i, event_ndims)
462 for x_i, ildj_i in zip(x, ildj)]
/external/lmfit/man/
Dlmfit.pod18 For fitting a data set {(x_i,y_i)|i=0,1,..} by a parametric curve f(x,t), see B<lmcurve>(3).
/external/tensorflow/tensorflow/python/keras/layers/
Drecurrent.py2193 x_i, x_f, x_c, x_o = x
2196 x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))
2235 x_i = K.dot(inputs_i, k_i)
2242 x_i = K.bias_add(x_i, b_i)
2257 x = (x_i, x_f, x_c, x_o)
2373 x_i, x_f, x_c, x_o = x
2376 x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]) +
Dconvolutional_recurrent.py692 x_i = self.input_conv(inputs_i, kernel_i, bias_i, padding=self.padding)
701 i = self.recurrent_activation(x_i + h_i)
/external/tensorflow/tensorflow/python/autograph/
DSTYLE_GUIDE.md80 `sum{ f(x[i]) : i=1...n }` better than `\sum_{i=1}^n f(x_i)` `int{sin(x) dx:
/external/eigen/doc/
DCoeffwiseMathFunctionsTable.dox460 …\n \f$ \gamma(a_i,x_i)= \frac{1}{|a_i|} \int_{0}^{x_i}e^{\text{-}t} t^{a_i-1} \mathrm{d} t \f$</td>
472 …\n \f$ \Gamma(a_i,x_i) = \frac{1}{|a_i|} \int_{x_i}^{\infty}e^{\text{-}t} t^{a_i-1} \mathrm{d} t \…
/external/tensorflow/tensorflow/core/framework/
Dfunction.proto102 // to x_i.

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