| /external/tensorflow/tensorflow/compiler/xla/client/lib/ |
| D | math.cc | 135 XlaOp Reciprocal(XlaOp operand) { return ScalarLike(operand, 1.0) / operand; } in Reciprocal()
140 XlaOp poly = ScalarLike(x, 0.0); in EvaluatePolynomial()
142 poly = poly * x + ScalarLike(x, c); in EvaluatePolynomial()
177 XlaOp q = ScalarLike(x, 1) / abs_x; in ErfcImpl()
179 XlaOp p = Select(Lt(abs_x, ScalarLike(x, 2.0)), in ErfcImpl()
183 return Select(Lt(x, ScalarLike(x, 0)), ScalarLike(x, 2.0) - y, y); in ErfcImpl()
217 return Select(Gt(Abs(x), ScalarLike(x, 1)), ErfcImpl(x), in Erfc()
218 ScalarLike(x, 1) - ErfImpl(x)); in Erfc()
234 return Select(Lt(Abs(x), ScalarLike(x, 1)), ErfImpl(x), in Erf()
235 ScalarLike(x, 1) - ErfcImpl(x)); in Erf()
[all …]
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| D | svd.cc | 120 XlaOp zero = ScalarLike(i, 0); in HouseRow()
135 auto one = ScalarLike(v, 1.0); in HouseRow()
138 Sqrt(Reduce(Square(v), ScalarLike(v, 0.0), in HouseRow()
149 Le(x_0j, ScalarLike(x_0j, 0.0)), Sub(x_0j, mu), in HouseRow()
152 auto beta = Div(ScalarLike(v_0j, 2.0), in HouseRow()
186 XlaOp zero = ScalarLike(i, 0); in HouseCol()
201 auto one = ScalarLike(v, 1.0); in HouseCol()
204 Sqrt(Reduce(Square(v), ScalarLike(v, 0.0), in HouseCol()
216 Le(x_0i, ScalarLike(x_0i, 0.0)), Sub(x_0i, mu), in HouseCol()
219 auto beta = Div(ScalarLike(v_0i, 2.0), in HouseCol()
[all …]
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| D | self_adjoint_eig.cc | 82 auto zero = ScalarLike(a, 0.0); in SymmetricShurDecomposition2x2()
83 auto one = ScalarLike(a, 1.0); in SymmetricShurDecomposition2x2()
84 auto two = ScalarLike(a, 2.0); in SymmetricShurDecomposition2x2()
124 auto zero = ScalarLike(p, 0); in Update()
155 auto pq_zero = ScalarLike(jacobi_update.w, 0.0); in Update()
200 Sqrt(Reduce(Square(w), ScalarLike(w, 0.0), in ComputeFrobeniusNorms()
205 Reduce(Square(diag), ScalarLike(w, 0.0), in ComputeFrobeniusNorms()
212 Sqrt(Max(Square(frobenius_norm) - diag_square, ScalarLike(w, 0.0))); in ComputeFrobeniusNorms()
228 auto max_sweeps = ScalarLike(k, max_sweep_updates); in WhileLoopFn()
247 return Lt(p, ScalarLike(p, matrix_dimension - 1)); in WhileLoopFn()
[all …]
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| D | constants.h | 85 XlaOp ScalarLike(XlaOp prototype, T value) { in ScalarLike() function
104 return Broadcast(ScalarLike(prototype, value), shape.dimensions()); in FullLike()
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| D | constants_test.cc | 55 ScalarLike(ConstantR0<int32>(&builder, 42), -3); in XLA_TEST_F()
61 ScalarLike(ConstantR0<float>(&builder, 42.75), -3.2); in XLA_TEST_F()
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| D | matrix.cc | 75 return Reduce(Select(mask, x, Zeros(builder, shape)), ScalarLike(x, 0), in GetMatrixDiagonal()
79 ScalarLike(x, 0), reducer, {n_dims - 2}); in GetMatrixDiagonal()
84 ScalarLike(x, 0), reducer, {n_dims - 1}); in GetMatrixDiagonal()
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| D | math_test.cc | 133 &b, {Sqrt(x), Pow(x, ScalarLike(x, 0.5)), Pow(x, ScalarLike(x, 0.3))}, in TestSqrtPowInequivalence()
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| D | qr.cc | 85 XlaOp zero = ScalarLike(x, 0.0); in House()
86 XlaOp one = ScalarLike(x, 1.0); in House()
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| /external/tensorflow/tensorflow/compiler/tf2xla/lib/ |
| D | random.cc | 44 xla::XlaOp one = xla::ScalarLike(uniform, 1.0); in TruncatedNormal()
45 xla::XlaOp two = xla::ScalarLike(uniform, 2.0); in TruncatedNormal()
46 xla::XlaOp sqrt_2 = xla::ScalarLike(uniform, std::sqrt(2.0)); in TruncatedNormal()
47 xla::XlaOp z = xla::ScalarLike(uniform, kZ); in TruncatedNormal()
48 xla::XlaOp alpha_normal_cdf = xla::ScalarLike(uniform, kAlphaNormalCdf); in TruncatedNormal()
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | unary_ops.cc | 71 XLAJIT_MAKE_UNARY(Inv, xla::ScalarLike(x, 1.0) / x);
72 XLAJIT_MAKE_UNARY(Reciprocal, xla::ScalarLike(x, 1.0) / x);
87 auto half = xla::ScalarLike(x, 0.5); in Sigmoid()
105 XLAJIT_MAKE_UNARY(Softplus, xla::Max(x, xla::ScalarLike(x, 0.0)) +
109 XLAJIT_MAKE_UNARY(Softsign, x / (xla::Abs(x) + xla::ScalarLike(x, 1.0)));
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| D | relu_op.cc | 61 xla::Max(features, features * xla::ScalarLike(features, alpha_)); in Compile()
113 xla::Select(xla::Gt(features, xla::ScalarLike(features, 0)), gradients, in Compile()
114 gradients * xla::ScalarLike(gradients, alpha_)); in Compile()
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| D | batch_norm_op.cc | 85 variance, xla::ScalarLike(variance, epsilon_)))); in Compile()
160 xla::XlaOp one = xla::ScalarLike(var, 1.0f); in Compile()
161 xla::XlaOp epsilon = xla::ScalarLike(var, epsilon_); in Compile()
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| D | training_ops.cc | 62 xla::XlaOp one = xla::ScalarLike(lr, 1.0); in ProximalGradientDescentUpdate()
63 xla::XlaOp zero = xla::ScalarLike(lr, 0.0); in ProximalGradientDescentUpdate()
386 xla::XlaOp zero = xla::ScalarLike(lr, 0.0); in Compile()
545 xla::XlaOp one = xla::ScalarLike(lr, 1.0); in Compile()
634 xla::XlaOp one = xla::ScalarLike(ms, 1.0); in Compile()
904 m = m * beta + grad * (xla::ScalarLike(beta, 1.0) - beta); in Compile()
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| D | reverse_sequence_op.cc | 75 xla::XlaOp back = xla::Sub(seq_lens, xla::ScalarLike(seq_lens, 1)); in Compile()
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| D | stateless_random_ops.cc | 51 return xla::ScalarLike(uniform, std::sqrt(2.0)) * xla::ErfInv(uniform); in Uniform2NormalUsingSqrtErfinv()
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| D | stateful_random_ops.cc | 271 xla::ScalarLike(uniform, std::sqrt(2.0)) * xla::ErfInv(uniform); in Compile()
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| /external/tensorflow/tensorflow/compiler/xla/service/ |
| D | triangular_solve_expander.cc | 215 auto j = (lower) ? i : ScalarLike(i, block_size - 1) - i; in InvertDiagonalBlocks()
233 auto next_i = i + ScalarLike(i, 1); in InvertDiagonalBlocks()
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| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| D | exhaustive_op_test.cc | 539 Run([](XlaOp x) { return Pow(x, ScalarLike(x, 0.5)); }, in XLA_TEST_P()
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