/external/tensorflow/tensorflow/compiler/xla/client/lib/ |
D | math.cc | 36 XlaOp poly = ScalarLike(x, 0.0); in EvaluatePolynomial() 38 poly = poly * x + ScalarLike(x, c); in EvaluatePolynomial() 49 XlaOp b0 = ScalarLike(x, 0.0); in EvaluateChebyshevPolynomial() 50 XlaOp b1 = ScalarLike(x, 0.0); in EvaluateChebyshevPolynomial() 51 XlaOp b2 = ScalarLike(x, 0.0); in EvaluateChebyshevPolynomial() 55 b0 = x * b1 - b2 + ScalarLike(x, c); in EvaluateChebyshevPolynomial() 57 return ScalarLike(x, 0.5) * (b0 - b2); in EvaluateChebyshevPolynomial() 167 XlaOp Reciprocal(XlaOp operand) { return ScalarLike(operand, 1.0) / operand; } in Reciprocal() 191 XlaOp q = ScalarLike(x, 1) / abs_x; in ErfcImpl32() 193 XlaOp p = Select(Lt(abs_x, ScalarLike(x, 2.0)), in ErfcImpl32() [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 | svd.cc | 115 XlaOp zero = ScalarLike(i, 0); in HouseRow() 130 auto one = ScalarLike(v, 1.0); in HouseRow() 133 Sqrt(Reduce(Square(v), ScalarLike(v, 0.0), in HouseRow() 144 Le(x_0j, ScalarLike(x_0j, 0.0)), Sub(x_0j, mu), in HouseRow() 147 auto beta = Div(ScalarLike(v_0j, 2.0), in HouseRow() 180 XlaOp zero = ScalarLike(i, 0); in HouseCol() 195 auto one = ScalarLike(v, 1.0); in HouseCol() 198 Sqrt(Reduce(Square(v), ScalarLike(v, 0.0), in HouseCol() 210 Le(x_0i, ScalarLike(x_0i, 0.0)), Sub(x_0i, mu), in HouseCol() 213 auto beta = Div(ScalarLike(v_0i, 2.0), in HouseCol() [all …]
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D | logdet.cc | 50 auto is_zero = Eq(a, ScalarLike(a, 0)); in LogDet() 60 ScalarLike(num_triangle_rows, a_shape.dimensions(a_shape.rank() - 2)); in LogDet() 73 ScalarLike(num_triangle_rows, 2)), in LogDet() 75 ScalarLike(sign_diag, -1.0), ScalarLike(sign_diag, 1.0)); in LogDet()
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D | tridiagonal.cc | 193 auto one = ScalarLike(i_minus_one, 1); in ThomasSolver() 248 auto n = ScalarLike(j, num_eqs - 2); in ThomasSolver() 249 auto one = ScalarLike(j, 1); in ThomasSolver()
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D | constants.h | 91 XlaOp ScalarLike(XlaOp prototype, T value) { in ScalarLike() function 110 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 | prng.cc | 323 ConvertElementType(key0 >> ScalarLike(key0, 32), U32), in ScramblePhiloxKey() 325 ConvertElementType(key1 >> ScalarLike(key1, 32), U32), in ScramblePhiloxKey() 484 bits, ScalarLike(bits, num_float_bits - num_mantissa_bits)); in ConvertRandomBitsToUniformFloatingPoint() 492 values = values * ScalarLike(values, std::ldexp(1., -num_mantissa_bits)); in ConvertRandomBitsToUniformFloatingPoint() 519 XlaOp u1 = Max(x0, ScalarLike(x0, 1.0e-7f)); in BoxMullerTransform() 521 XlaOp v1 = ScalarLike(x1, 2.0f * M_PI) * x1; in BoxMullerTransform() 522 XlaOp u2 = Sqrt(ScalarLike(u1, -2.0f) * Log(u1)); in BoxMullerTransform()
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D | matrix.cc | 97 Select(mask, x, Zeros(builder, shape)), ScalarLike(x, 0), in GetMatrixDiagonal() 202 diag = Pad(diag, ScalarLike(diag, 0), padding_config); in SetMatrixDiagonal() 291 auto zero = ScalarLike(x, 0); in EinsumDiagonal() 500 x = Reduce(x, ScalarLike(x, 0), in Einsum() 506 y = Reduce(y, ScalarLike(y, 0), in Einsum() 693 return Einsum(ScalarLike(x, 1), x, absl::StrCat(",", einsum_config), in Einsum()
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D | matrix_test.cc | 102 GetMatrixDiagonal(SetMatrixDiagonal(a, b + ScalarLike(b, 1), kv.first), in TestSetMatrixDiagonal() 104 ScalarLike(b, 1); in TestSetMatrixDiagonal()
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D | math_test.cc | 140 &b, {Sqrt(x), Pow(x, ScalarLike(x, 0.5)), Pow(x, ScalarLike(x, 0.3))}, in TestSqrtPowInequivalence()
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/external/tensorflow/tensorflow/compiler/tf2xla/lib/ |
D | random.cc | 35 uniform, xla::ScalarLike(uniform, kMu), xla::ScalarLike(uniform, kSigma), in TruncatedNormal() 36 xla::ScalarLike(uniform, kA), xla::ScalarLike(uniform, kB)); in TruncatedNormal() 45 xla::XlaOp one = xla::ScalarLike(uniform, 1.0); in ParameterizedTruncatedNormal() 46 xla::XlaOp two = xla::ScalarLike(uniform, 2.0); in ParameterizedTruncatedNormal() 47 xla::XlaOp sqrt_2 = xla::ScalarLike(uniform, std::sqrt(2.0)); in ParameterizedTruncatedNormal()
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
D | relu_op.cc | 26 XlaOp Relu(XlaOp x) { return Max(ScalarLike(x, 0), x); } in Relu() 29 auto zero = ScalarLike(x, 0); in Relu6() 30 auto six = ScalarLike(x, 6); in Relu6() 65 auto prod_with_alpha = features * xla::ScalarLike(features, alpha_); in Compile() 66 auto gt_zero = xla::Gt(features, xla::ScalarLike(features, 0)); in Compile() 119 xla::Select(xla::Gt(features, xla::ScalarLike(features, 0)), gradients, in Compile() 120 gradients * xla::ScalarLike(gradients, alpha_)); in Compile()
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D | dequantize_op.cc | 73 full_range = ScalarLike(output, get_fullrange<qint8>()); in Compile() 75 (full_range + ScalarLike(output, 1.0f)) / ScalarLike(output, 2.0f); in Compile() 80 full_range = ScalarLike(output, get_fullrange<quint8>()); in Compile() 81 half_range = ScalarLike(output, 0.0f); in Compile()
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D | unary_ops.cc | 73 XLAJIT_MAKE_UNARY(Inv, xla::ScalarLike(x, 1.0) / x); 74 XLAJIT_MAKE_UNARY(Reciprocal, xla::ScalarLike(x, 1.0) / x); 99 Log(xla::Epsilon(b, shape.element_type())) + ScalarLike(features, 2.0); in Softplus() 116 XLAJIT_MAKE_UNARY(Softsign, x / (xla::Abs(x) + xla::ScalarLike(x, 1.0))); 128 XLAJIT_MAKE_UNARY(Ndtri, xla::ScalarLike(x, std::sqrt(2.0)) * 129 xla::ErfInv(xla::ScalarLike(x, 2.0) * x - 130 xla::ScalarLike(x, 1.0)));
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D | elu_op.cc | 29 const auto zero = ScalarLike(x, 0); in Elu() 36 const auto zero = ScalarLike(x, 0); in Selu() 37 const auto scale = ScalarLike(x, 1.0507009873554804934193349852946); in Selu() 38 const auto scale_alpha = ScalarLike(x, 1.7580993408473768599402175208123); in Selu()
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D | batch_norm_op.cc | 121 xla::Mul(variance, xla::ScalarLike(variance, factor)); in CompileImpl() 140 xla::ScalarLike(old_mean, 1.0f - exponential_avg_factor_); in CompileImpl() 141 xla::XlaOp beta = xla::ScalarLike(old_mean, exponential_avg_factor_); in CompileImpl() 169 variance, xla::ScalarLike(variance, epsilon_)))); in CompileImpl() 286 xla::XlaOp one = xla::ScalarLike(var, 1.0f); in Compile() 287 xla::XlaOp epsilon = xla::ScalarLike(var, epsilon_); in Compile()
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D | cast_op.cc | 167 xla::Mul(xla::ScalarLike(input, output_bit_width), iota); in Compile() 169 xla::ScalarLike(input, output_bit_width_mask)); in Compile() 189 xla::Mul(xla::ScalarLike(input, input_bit_width), in Compile()
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D | sequence_ops.cc | 164 (stop - start) / xla::ScalarLike(start, (num > 1 ? num - 1 : num)); in Compile() 170 xla::XlaOp eq = xla::Eq(mask, xla::ScalarLike(mask, num - 1)); in Compile()
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D | mirror_pad_op.cc | 145 reverse_lhs_pad, xla::ScalarLike(reverse_lhs_pad, 0), dimno, in DoMirrorPadGrad() 153 reverse_rhs_pad, xla::ScalarLike(reverse_rhs_pad, 0), dimno, in DoMirrorPadGrad()
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D | unary_ops_composition.cc | 59 "Inv", [](xla::XlaOp x) { return xla::ScalarLike(x, 1.0) / x; }); in PopulateXlaOpGeneratorMap()
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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 | 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() 449 xla::XlaOp zero = xla::ScalarLike(lr, 0.0); in Compile() 620 xla::XlaOp one = xla::ScalarLike(lr, 1.0); in Compile() 709 xla::XlaOp one = xla::ScalarLike(ms, 1.0); in Compile() 1003 m = m * beta + grad * (xla::ScalarLike(beta, 1.0) - beta); in Compile()
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/external/tensorflow/tensorflow/compiler/xla/service/ |
D | qr_expander.cc | 91 XlaOp zero = ScalarLike(x, 0.0); in House() 107 Reduce(x_squared, ScalarLike(x_squared, 0.0), in House() 114 sigma_is_zero = Eq(sigma, ScalarLike(sigma, 0)); in House() 115 sigma_is_zero = And(sigma_is_zero, Eq(Imag(alpha), ScalarLike(sigma, 0))); in House() 117 *beta = Select(Lt(Real(alpha), ScalarLike(sigma, 0)), ScalarLike(mu, 1), in House() 118 ScalarLike(mu, -1)) * in House() 131 XlaOp one = ScalarLike(x, 1.0); in House() 139 Select(sigma_is_zero, Broadcast(ScalarLike(alpha, 1), batch_dims), in House()
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/external/tensorflow/tensorflow/compiler/xla/tests/ |
D | exhaustive_unary_test_f64.cc | 71 Run([](XlaOp x) { return Pow(x, ScalarLike(x, 0.5)); }, in __anon5d9703520102()
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