/external/tensorflow/tensorflow/python/kernel_tests/ |
D | matrix_square_root_op_test.py | 52 def _makeBatch(self, matrix1, matrix2): argument 54 [np.expand_dims(matrix1, 0), 59 def _testMatrices(self, matrix1, matrix2): argument 61 self._verifySquareRootReal(matrix1) 63 self._verifySquareRootReal(self._makeBatch(matrix1, matrix2)) 64 matrix1 = matrix1.astype(np.complex64) 66 matrix1 += 1j * matrix1 68 self._verifySquareRootComplex(matrix1) 70 self._verifySquareRootComplex(self._makeBatch(matrix1, matrix2)) 73 matrix1 = np.array([[2., 1.], [1., 2.]]) [all …]
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D | matrix_inverse_op_test.py | 61 def _makeBatch(self, matrix1, matrix2): argument 63 [np.expand_dims(matrix1, 0), 70 matrix1 = np.array([[1., 2.], [3., 4.]]) 72 self._verifyInverseReal(matrix1) 75 self._verifyInverseReal(self._makeBatch(matrix1, matrix2)) 76 matrix1 = matrix1.astype(np.complex64) 77 matrix1 += 1j * matrix1 80 self._verifyInverseComplex(matrix1) 83 self._verifyInverseComplex(self._makeBatch(matrix1, matrix2)) 87 matrix1 = np.array([[2., 1.], [1., 2.]]) [all …]
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D | matrix_exponential_op_test.py | 76 def _makeBatch(self, matrix1, matrix2): argument 78 [np.expand_dims(matrix1, 0), 85 matrix1 = np.array([[1., 2.], [3., 4.]]) 87 self._verifyExponentialReal(matrix1) 90 self._verifyExponentialReal(self._makeBatch(matrix1, matrix2)) 94 matrix1 = np.array([[1., 2.], [3., 4.]]) 96 matrix1 = matrix1.astype(np.complex64) 97 matrix1 += 1j * matrix1 100 self._verifyExponentialComplex(matrix1) 103 self._verifyExponentialComplex(self._makeBatch(matrix1, matrix2)) [all …]
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D | matrix_logarithm_op_test.py | 54 def _makeBatch(self, matrix1, matrix2): argument 56 [np.expand_dims(matrix1, 0), 64 matrix1 = np.array([[1., 2.], [3., 4.]]) 66 matrix1 = matrix1.astype(np.complex64) 67 matrix1 += 1j * matrix1 70 self._verifyLogarithmComplex(matrix1) 73 self._verifyLogarithmComplex(self._makeBatch(matrix1, matrix2)) 78 matrix1 = np.array([[2., 1.], [1., 2.]]) 80 matrix1 = matrix1.astype(np.complex64) 81 matrix1 += 1j * matrix1 [all …]
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D | cholesky_op_test.py | 187 matrix1 = stateless_random_ops.stateless_random_normal(matrix_shape, seed) 189 matrix1 = math_ops.matmul(matrix1, matrix1, adjoint_a=True) 191 c1 = linalg_ops.cholesky(matrix1)
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D | self_adjoint_eig_op_test.py | 60 matrix1 = random_ops.random_normal([5, 5], seed=42) 63 e1, v1 = linalg_ops.self_adjoint_eig(matrix1) 67 e1 = linalg_ops.self_adjoint_eigvals(matrix1)
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D | eig_op_test.py | 60 matrix1 = random_ops.random_normal([5, 5], seed=42) 63 e1, v1 = linalg_ops.eig(matrix1) 67 e1 = linalg_ops.eigvals(matrix1)
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D | qr_op_test.py | 69 matrix1 = stateless_random_ops.stateless_random_normal( 73 self.assertAllEqual(matrix1, matrix2) 74 q1, r1 = linalg_ops.qr(matrix1, full_matrices=full_matrices_)
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D | lu_op_test.py | 226 matrix1 = stateless_random_ops.stateless_random_normal( 230 self.assertAllEqual(matrix1, matrix2) 231 lu1, p1 = linalg_ops.lu(matrix1)
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D | svd_op_test.py | 70 matrix1 = stateless_random_ops.stateless_random_normal(shape, seed) 72 self.assertAllEqual(matrix1, matrix2) 75 matrix1, compute_uv=compute_uv_, full_matrices=full_matrices_) 81 matrix1, compute_uv=compute_uv_, full_matrices=full_matrices_)
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D | basic_gpu_test.py | 213 matrix1 = variables.Variable( 217 x1 = math_ops.multiply(data, matrix1, name='x1') 218 x3 = math_ops.matmul(x1, math_ops.matmul(matrix2, matrix1))
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D | determinant_op_test.py | 158 matrix1 = random_ops.random_normal([5, 5], seed=42) 160 det1 = linalg_ops.matrix_determinant(matrix1)
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/external/robolectric-shadows/robolectric/src/test/java/org/robolectric/shadows/ |
D | ShadowMatrixTest.java | 85 final Matrix matrix1 = new Matrix(); in set_shouldOverrideValues() local 86 matrix1.setScale(1, 2); in set_shouldOverrideValues() 90 matrix2.set(matrix1); in set_shouldOverrideValues() 98 final Matrix matrix1 = new Matrix(); in set_whenNull_shouldReset() local 99 matrix1.setScale(1, 2); in set_whenNull_shouldReset() 102 matrix2.set(matrix1); in set_whenNull_shouldReset() 179 final Matrix matrix1 = new Matrix(); in testSet() local 180 matrix1.postScale(2.0f, 2.0f); in testSet() 181 matrix1.postTranslate(1.0f, 2.0f); in testSet() 182 matrix1.postRotate(45.0f); in testSet() [all …]
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D | ShadowOpenGLMatrixTest.java | 336 float[] matrix1 = new float[]{ in testMultiplyMM() local 356 Matrix.multiplyMM(output, 0, matrix1, 0, matrix2, 0); in testMultiplyMM()
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/external/eigen/demos/mix_eigen_and_c/ |
D | example.c | 15 struct C_MatrixXd *matrix1, *matrix2, *result; in demo_MatrixXd() local 18 matrix1 = MatrixXd_new(3, 3); in demo_MatrixXd() 19 MatrixXd_set_zero(matrix1); in demo_MatrixXd() 20 MatrixXd_set_coeff(matrix1, 0, 1, 2.5); in demo_MatrixXd() 21 MatrixXd_set_coeff(matrix1, 1, 0, 1.4); in demo_MatrixXd() 23 MatrixXd_print(matrix1); in demo_MatrixXd() 26 MatrixXd_multiply(matrix1, matrix1, matrix2); in demo_MatrixXd() 30 MatrixXd_delete(matrix1); in demo_MatrixXd()
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/external/tensorflow/tensorflow/python/kernel_tests/linalg/ |
D | linear_operator_adjoint_test.py | 122 matrix1 = np.random.randn(4, 4) 124 full_matrix1 = linalg.LinearOperatorFullMatrix(matrix1) 128 np.matmul(matrix1, matrix2.T), 133 np.matmul(matrix1.T, matrix2), 138 np.matmul(matrix1.T, matrix2.T), 144 matrix1 = np.random.randn(4, 4) + 1j * np.random.randn(4, 4) 146 full_matrix1 = linalg.LinearOperatorFullMatrix(matrix1) 150 np.matmul(matrix1, matrix2.conj().T), 155 np.matmul(matrix1.conj().T, matrix2), 160 np.matmul(matrix1.conj().T, matrix2.conj().T), [all …]
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D | linear_operator_test.py | 285 matrix1 = array_ops.placeholder_with_default( 288 matrix1, 330 matrix1 = array_ops.placeholder_with_default( 337 operator1 = LinearOperatorMatmulSolve(matrix1, is_square=False)
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/external/tensorflow/tensorflow/compiler/tests/ |
D | matrix_inverse_op_test.py | 55 def _makeBatch(self, matrix1, matrix2): argument 57 [np.expand_dims(matrix1, 0), 64 matrix1 = np.array([[1., 2.], [3., 4.]]) 66 self._verifyInverseReal(matrix1) 69 self._verifyInverseReal(self._makeBatch(matrix1, matrix2)) 73 matrix1 = np.array([[2., 1.], [1., 2.]]) 75 self._verifyInverseReal(matrix1) 78 self._verifyInverseReal(self._makeBatch(matrix1, matrix2))
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/external/webrtc/modules/audio_coding/codecs/isac/fix/source/ |
D | entropy_coding.h | 102 const int32_t matrix1[], 113 const int32_t matrix1[], 122 const int32_t matrix1[], 133 const int32_t matrix1[], 140 const int32_t matrix1[], 151 const int32_t matrix1[], 159 const int32_t matrix1[], 171 const int32_t matrix1[],
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D | entropy_coding_mips.c | 18 const int32_t matrix1[], in WebRtcIsacfix_MatrixProduct1MIPS() argument 39 const int32_t* matrix1_start = matrix1; in WebRtcIsacfix_MatrixProduct1MIPS() 91 : [product_step] "r" (product_step), [matrix1] "r" (matrix1), in WebRtcIsacfix_MatrixProduct1MIPS() 109 const int32_t* matrix1_start = matrix1; in WebRtcIsacfix_MatrixProduct1MIPS() 175 const int32_t matrix1[], in WebRtcIsacfix_MatrixProduct2MIPS() argument 245 [matrix1] "r" (matrix1), [matrix0_step] "r" (matrix0_step), in WebRtcIsacfix_MatrixProduct2MIPS()
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D | entropy_coding_neon.c | 25 const int32_t matrix1[], in WebRtcIsacfix_MatrixProduct1Neon() argument 62 vshlq_s32(vld1q_s32(&matrix1[matrix1_index]), shift32x4); in WebRtcIsacfix_MatrixProduct1Neon() 80 vshl_s32(vld1_s32(&matrix1[matrix1_index]), shift32x2); in WebRtcIsacfix_MatrixProduct1Neon() 101 int32x4_t matrix1_32x4 = vdupq_n_s32(matrix1[matrix1_index] << shift); in WebRtcIsacfix_MatrixProduct1Neon() 117 int32x2_t matrix1_32x2 = vdup_n_s32(matrix1[matrix1_index] << shift); in WebRtcIsacfix_MatrixProduct1Neon() 146 vshlq_s32(vld1q_s32(&matrix1[matrix1_index]), shift32x4); in WebRtcIsacfix_MatrixProduct1Neon() 157 vshl_s32(vld1_s32(&matrix1[matrix1_index]), shift32x2); in WebRtcIsacfix_MatrixProduct1Neon() 181 matrix1[matrix1_index] << shift)); in WebRtcIsacfix_MatrixProduct1Neon() 193 const int32_t matrix1[], in WebRtcIsacfix_MatrixProduct2Neon() argument 207 int32x2_t matrix1_32x2 = vld1_s32(&matrix1[matrix1_index]); in WebRtcIsacfix_MatrixProduct2Neon()
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/external/libchrome/ui/gfx/geometry/ |
D | matrix3_unittest.cc | 164 Matrix3F matrix1 = Matrix3F::Zeros(); in TEST() local 165 matrix1.set(1, 2, 3, 4, 5, 6, 7, 8, 9); in TEST() 166 EXPECT_EQ(matrix1 + Matrix3F::Zeros(), matrix1); in TEST() 170 EXPECT_EQ(matrix1 + matrix2, Matrix3F::Zeros()); in TEST() 172 EXPECT_EQ(Matrix3F::Zeros() - matrix1, matrix2); in TEST() 176 EXPECT_EQ(matrix1 - matrix2, result); in TEST() 178 EXPECT_EQ(matrix2 - matrix1, result); in TEST()
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/external/eigen/doc/ |
D | TopicLazyEvaluation.dox | 27 \code matrix1 = matrix2 + matrix3; \endcode 31 \code matrix1 = (matrix2 + matrix3).eval(); \endcode 35 \code matrix1 = -matrix2 + matrix3 + 5 * matrix4; \endcode 47 \code matrix1.noalias() = matrix2 * matrix2; \endcode 49 Here, since we know that matrix2 is not the same matrix as matrix1, we know that lazy evaluation is… 53 \code matrix1 = matrix2 + matrix3 * matrix4; \endcode 59 \code matrix1 = matrix2 * (matrix3 + matrix4); \endcode
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/external/pdfium/core/fxge/agg/ |
D | fx_agg_driver.cpp | 1374 CFX_Matrix matrix1; in DrawPath() local 1377 matrix1.a = std::max(fabs(pObject2Device->a), fabs(pObject2Device->b)); in DrawPath() 1378 matrix1.d = matrix1.a; in DrawPath() 1380 pObject2Device->a / matrix1.a, pObject2Device->b / matrix1.a, in DrawPath() 1381 pObject2Device->c / matrix1.d, pObject2Device->d / matrix1.d, 0, 0); in DrawPath() 1383 matrix1 = *pObject2Device * matrix2.GetInverse(); in DrawPath() 1387 path_data.BuildPath(pPathData, &matrix1); in DrawPath() 1393 matrix1.a, !!(fill_mode & FX_STROKE_TEXT_MODE)); in DrawPath()
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/external/llvm-project/flang/test/Semantics/ |
D | final02.f90 | 50 type(t1) :: matrix1(2,2) local
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