/external/tensorflow/tensorflow/python/kernel_tests/ |
D | gather_op_test.py | 256 batch_dims=0, 261 batch_dims=0, 266 batch_dims=0, 275 batch_dims=1, 280 batch_dims=2, 285 batch_dims=-1, 290 batch_dims=-1, 297 batch_dims=1, 302 batch_dims=1, 309 batch_dims=2, [all …]
|
D | matrix_triangular_solve_op_test.py | 32 def _verifySolveAllWays(self, x, y, dtypes, batch_dims=None): argument 41 batch_dims=batch_dims, 45 def _verifySolveAllWaysReal(self, x, y, batch_dims=None): argument 46 self._verifySolveAllWays(x, y, (np.float32, np.float64), batch_dims) 48 def _verifySolveAllWaysComplex(self, x, y, batch_dims=None): argument 49 self._verifySolveAllWays(x, y, (np.complex64, np.complex128), batch_dims) 56 batch_dims=None, argument 73 if batch_dims is not None: 74 a = np.tile(a, batch_dims + [1, 1]) 75 a_np = np.tile(a_np, batch_dims + [1, 1]) [all …]
|
D | matrix_solve_op_test.py | 39 def _verifySolve(self, x, y, batch_dims=None): argument 53 if batch_dims is not None: 54 a = np.tile(a, batch_dims + [1, 1]) 55 a_np = np.tile(a_np, batch_dims + [1, 1]) 56 b = np.tile(b, batch_dims + [1, 1]) 93 for batch_dims in [[2], [2, 2], [7, 4]]: 94 self._verifySolve(matrix, rhs, batch_dims=batch_dims)
|
D | resource_variable_ops_test.py | 1099 batch_dims=0, 1104 batch_dims=0, 1109 batch_dims=0, 1118 batch_dims=1, 1123 batch_dims=2, 1128 batch_dims=1, 1133 batch_dims=2, 1140 batch_dims=1, 1145 batch_dims=1, 1152 batch_dims=2, [all …]
|
D | matrix_logarithm_op_test.py | 112 for batch_dims in [(), (1,), (3,), (2, 2)]: 114 shape = batch_dims + (size, size) 123 for batch_dims in [(), (1,), (3,), (2, 2)]: 125 shape = batch_dims + (size, size)
|
D | qr_op_test.py | 208 for batch_dims in [(), (3,)] + [(3, 2)] * (max(rows, cols) < 10): 211 shape = batch_dims + (rows, cols) 229 for batch_dims in [(), (3,)] + [(3, 2)] * (max(rows, cols) < 10): 230 shape = batch_dims + (rows, cols)
|
D | svd_op_test.py | 318 for batch_dims in [(), (3,)] + [(3, 2)] * (max(rows, cols) < 10): 319 shape = batch_dims + (rows, cols) 337 for batch_dims in [(), (3,)]: 338 shape = batch_dims + mat_shape
|
D | batch_matmul_op_test.py | 38 batch_dims = x.shape[:-2] 39 num = np.prod(batch_dims) 40 z = np.empty(list(batch_dims) + [d0, d2], dtype=x.dtype)
|
D | matrix_inverse_op_test.py | 135 for batch_dims in [(), (1,), (3,), (2, 2)]: 137 shape = batch_dims + (size, size)
|
D | self_adjoint_eig_op_test.py | 247 for batch_dims in [(), (3,)] + [(3, 2)] * (max(size, size) < 10): 248 shape = batch_dims + (size, size)
|
D | matrix_exponential_op_test.py | 218 def _TestRandomSmall(dtype, batch_dims, size): argument 222 shape = batch_dims + (size, size)
|
/external/tensorflow/tensorflow/compiler/xla/client/lib/ |
D | qr.cc | 75 Status House(XlaOp x, XlaOp k, absl::Span<const int64> batch_dims, in House() argument 81 std::vector<int64> batch_dim_ids(batch_dims.size()); in House() 83 const int64 minor_dim = batch_dims.size(); in House() 89 XlaOp alpha = Reshape(DynamicSliceInMinorDims(x, {k}, {1}), batch_dims); in House() 105 *tau = Select(sigma_is_zero, Broadcast(zero, batch_dims), in House() 108 Select(sigma_is_zero, Broadcast(one, batch_dims), alpha - *beta); in House() 111 std::vector<int64>(batch_dims.size(), 1)); in House() 168 std::vector<int64> batch_dims(num_batch_dims); in QRBlock() local 170 batch_dims[i] = ShapeUtil::GetDimension(a_shape, i); in QRBlock() 186 batch_dims, m, &v, &tau, &beta)); in QRBlock() [all …]
|
D | svd.cc | 124 std::vector<int64> batch_dims(num_batch_dims); in HouseRow() local 126 batch_dims[k] = ShapeUtil::GetDimension(a_shape, k); in HouseRow() 190 std::vector<int64> batch_dims(num_batch_dims); in HouseCol() local 192 batch_dims[k] = ShapeUtil::GetDimension(a_shape, k); in HouseCol() 264 std::vector<int64> batch_dims(num_batch_dims); in HouseHolderBidiagonalization() local 266 batch_dims[i] = ShapeUtil::GetDimension(a_shape, i); in HouseHolderBidiagonalization() 271 IdentityMatrix(builder, a_shape.element_type(), m, m), batch_dims); in HouseHolderBidiagonalization() 273 IdentityMatrix(builder, a_shape.element_type(), n, n), batch_dims); in HouseHolderBidiagonalization() 469 std::vector<int64> batch_dims(num_batch_dims); in OneSidedJacobiUpdate() local 471 batch_dims[i] = ShapeUtil::GetDimension(d_shape, i); in OneSidedJacobiUpdate() [all …]
|
D | self_adjoint_eig.cc | 120 const std::vector<int64> batch_dims(w_shape.dimensions().begin(), in Update() local 152 std::vector<int64> pq_dims(batch_dims.begin(), batch_dims.end()); in Update() 165 std::vector<int64> broadcast_dims(batch_dims.size()); in Update() 430 std::vector<int64> batch_dims(num_batch_dims); in SelfAdjointEig() local 432 batch_dims[i] = ShapeUtil::GetDimension(a_shape, i); in SelfAdjointEig() 437 auto v_init = Broadcast(IdentityMatrix(builder, type, m, m), batch_dims); in SelfAdjointEig()
|
/external/tensorflow/tensorflow/python/ops/ |
D | array_ops.py | 3293 batch_dims=0): argument 3360 if batch_dims != 0: 3362 return _batch_gather(params, indices, batch_dims, axis) 3364 axis = batch_dims 3381 batch_dims=0, name=None): argument 3383 axis=axis, batch_dims=batch_dims) 3402 return _batch_gather(params, indices, batch_dims=indices.shape.ndims - 1) 3405 def _batch_gather(params, indices, batch_dims, axis=None): argument 3431 if batch_dims is not None and not isinstance(batch_dims, int): 3432 raise TypeError("batch_dims must be an int; got %r" % batch_dims) [all …]
|
/external/tensorflow/tensorflow/core/ops/ |
D | resource_variable_ops.cc | 270 int32 batch_dims; in __anon3f9cfa090402() local 271 TF_RETURN_IF_ERROR(c->GetAttr("batch_dims", &batch_dims)); in __anon3f9cfa090402() 272 if (batch_dims < 0) in __anon3f9cfa090402() 273 return errors::InvalidArgument("batch_dims is negative (", batch_dims, in __anon3f9cfa090402() 277 batch_dims + 1, &unused)); in __anon3f9cfa090402() 280 c->WithRankAtLeast(indices_shape, batch_dims, &unused)); in __anon3f9cfa090402() 284 batch_dims, ¶ms_subshape1)); in __anon3f9cfa090402() 288 batch_dims + 1, ¶ms_subshape2)); in __anon3f9cfa090402() 292 c->Subshape(indices_shape, batch_dims, &indices_subshape)); in __anon3f9cfa090402()
|
D | math_ops.cc | 144 ShapeHandle batch_dims; in __anonb22bfa860202() local 147 TF_RETURN_IF_ERROR(c->Merge(a_batch_dims, b_batch_dims, &batch_dims)); in __anonb22bfa860202() 156 batch_dims, c->Matrix(output_rows, output_cols), &out)); in __anonb22bfa860202()
|
/external/tensorflow/tensorflow/compiler/tests/ |
D | svd_op_test.py | 74 for batch_dims in [(), (3,)] + [(3, 2)] * (n < 10): 75 self._testSvdCorrectness(dtype, batch_dims + (n, n)) 76 self._testSvdCorrectness(dtype, batch_dims + (2 * n, n)) 77 self._testSvdCorrectness(dtype, batch_dims + (n, 2 * n))
|
D | self_adjoint_eig_op_test.py | 57 for batch_dims in [(), (3,)] + [(3, 2)] * (n < 10): 58 self._test(dtype, batch_dims + (n, n))
|
D | qr_op_test.py | 107 for batch_dims in [(), (3,)] + [(3, 2)] * (max(rows, cols) < 10): 108 self._test(dtype, batch_dims + (rows, cols), full_matrices)
|
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
D | softmax_op.cc | 47 std::vector<int64> batch_dims(logits_shape.dims() - 1); in Compile() local 48 std::iota(batch_dims.begin(), batch_dims.end(), 0); in Compile() 63 auto shifted_logits = xla::Sub(logits, logits_max, batch_dims); in Compile() 78 ? xla::Sub(shifted_logits, xla::Log(sum), batch_dims) in Compile() 80 : xla::Div(exp_shifted, sum, batch_dims); in Compile()
|
/external/tensorflow/tensorflow/python/ops/ragged/ |
D | ragged_gather_ops.py | 36 def gather(params, indices, validate_indices=None, axis=0, batch_dims=0, argument 92 if not isinstance(batch_dims, int) or batch_dims != 0:
|
D | ragged_dispatch.py | 407 axis=0, batch_dims=0): argument 413 batch_dims=batch_dims,
|
/external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
D | test_util.py | 89 batch_dims = array_ops.shape(dist.batch_shape_tensor())[0] 90 edges_expanded_shape = 1 + array_ops.pad([-2], paddings=[[0, batch_dims]])
|
/external/tensorflow/tensorflow/compiler/xla/service/ |
D | indexed_array_analysis.cc | 977 absl::Span<const int64> batch_dims) { in GetOnlyNonContractingNonBatchDim() argument 981 !absl::c_linear_search(batch_dims, dim)) { in GetOnlyNonContractingNonBatchDim() 1002 absl::Span<const int64> batch_dims) { in CanFoldDotIntoIndexedArray() argument 1005 contracting_dims, batch_dims); in CanFoldDotIntoIndexedArray()
|