/external/tensorflow/tensorflow/python/ops/parallel_for/ |
D | array_test.py | 42 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 …]
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D | control_flow_ops_test.py | 69 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 …]
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/external/tensorflow/tensorflow/core/util/ |
D | bcast.cc | 70 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()
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/external/bouncycastle/bcprov/src/main/java/org/bouncycastle/math/raw/ |
D | Nat192.java | 282 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 …]
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D | Nat256.java | 380 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 …]
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D | Nat224.java | 301 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 …]
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D | Nat.java | 380 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()
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/external/bouncycastle/repackaged/bcprov/src/main/java/com/android/org/bouncycastle/math/raw/ |
D | Nat192.java | 286 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 …]
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D | Nat256.java | 384 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 …]
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D | Nat224.java | 305 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 …]
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D | Nat.java | 384 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()
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/external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
D | conditional_transformed_distribution.py | 116 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)]
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/external/tensorflow/tensorflow/contrib/tensor_forest/ |
D | README.md | 57 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
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/external/libxaac/decoder/ |
D | ixheaacd_hbe_trans.c | 294 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 …]
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_ParallelDynamicStitch.pbtxt | 49 # Apply function (increments x_i) on elements for which a certain condition 50 # apply (x_i != -1 in this example).
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D | api_def_DynamicStitch.pbtxt | 50 # Apply function (increments x_i) on elements for which a certain condition 51 # apply (x_i != -1 in this example).
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D | api_def_SymbolicGradient.pbtxt | 45 to x_i.
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/external/tensorflow/tensorflow/contrib/factorization/g3doc/ |
D | kmeans.md | 3 Given a set of input $$x_i$$, K-means clustering finds a set C of cluster 5 C} (||x_i - \mu_j||^2) $$.
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/external/tensorflow/tensorflow/python/ops/distributions/ |
D | transformed_distribution.py | 435 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)]
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/external/lmfit/man/ |
D | lmfit.pod | 18 For fitting a data set {(x_i,y_i)|i=0,1,..} by a parametric curve f(x,t), see B<lmcurve>(3).
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | recurrent.py | 2193 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]) +
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D | convolutional_recurrent.py | 692 x_i = self.input_conv(inputs_i, kernel_i, bias_i, padding=self.padding) 701 i = self.recurrent_activation(x_i + h_i)
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/external/tensorflow/tensorflow/python/autograph/ |
D | STYLE_GUIDE.md | 80 `sum{ f(x[i]) : i=1...n }` better than `\sum_{i=1}^n f(x_i)` `int{sin(x) dx:
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/external/eigen/doc/ |
D | CoeffwiseMathFunctionsTable.dox | 460 …\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 \…
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/external/tensorflow/tensorflow/core/framework/ |
D | function.proto | 102 // to x_i.
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