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/aosp_15_r20/external/tensorflow/tensorflow/python/kernel_tests/sparse_ops/
H A Dsparse_cross_op_test.py81 self._sparse_tensor([['batch1-FC1-F1'],
83 self._sparse_tensor([['batch1-FC2-F1'],
86 expected_out = self._sparse_tensor([['batch1-FC1-F1_X_batch1-FC2-F1'], [
97 constant_op.constant([['batch1-FC1-F1', 'batch1-FC1-F2'],
100 constant_op.constant([['batch1-FC2-F1', 'batch1-FC2-F2'],
105 'batch1-FC1-F1_X_batch1-FC2-F1', 'batch1-FC1-F1_X_batch1-FC2-F2',
106 'batch1-FC1-F2_X_batch1-FC2-F1', 'batch1-FC1-F2_X_batch1-FC2-F2'
119 self._sparse_tensor([['batch1-FC2-F1'],
134 constant_op.constant([['batch1-FC2-F1', 'batch1-FC2-F2'],
152 self._sparse_tensor([['batch1-FC1-F1'],
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/mkldnn/xpu/
H A DBlas.cpp171 // result = beta * input + alpha * (batch1 @ batch2)
174 const Tensor& batch1, in baddbmm_out() argument
179 checkBackend("baddbmm_out", {input, batch1, batch2}, Backend::XPU); in baddbmm_out()
180 TORCH_CHECK(batch1.dim() == 3, "expected 3D tensor"); in baddbmm_out()
184 batch1.size(0), batch1.size(1), batch2.size(2)}; in baddbmm_out()
188 } else if (batch1.size(2) == 0){ in baddbmm_out()
205 if (batch1.is_complex() || batch2.scalar_type() == ScalarType::Double) { in baddbmm_out()
229 onednn::matmul(result, batch1, batch2, at::Tensor(), true, attr); in baddbmm_out()
235 const Tensor& batch1, in baddbmm_() argument
239 …TORCH_CHECK(self.dtype() == batch1.dtype(), "Input dtypes must be the same, got: input ", self.dty… in baddbmm_()
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/mps/operations/
H A DLinearAlgebra.mm303 const Tensor& batch1,
312 TORCH_CHECK(batch1.is_mps());
316 TORCH_CHECK(supportedFloatingOrComplexType(batch1),
319 TORCH_CHECK(batch1.dim() == 3, "batch1 must be a 3D tensor");
321 TORCH_CHECK(batch1.size(0) == batch2.size(0),
322 "batch1 and batch2 must have same number of batches, got ",
323 batch1.size(0),
326 TORCH_CHECK(batch1.size(2) == batch2.size(1),
328 batch1.size(1),
330 batch1.size(2),
[all …]
/aosp_15_r20/external/pytorch/tools/autograd/
H A Ddeprecated.yaml13 - name: addbmm(Scalar beta, Tensor self, Scalar alpha, Tensor batch1, Tensor batch2) -> Tensor
14 aten: addbmm(self, batch1, batch2, beta, alpha)
16 - name: addbmm_(Scalar beta, Tensor(a!) self, Scalar alpha, Tensor batch1, Tensor batch2) -> Tensor…
17 aten: addbmm_(self, batch1, batch2, beta, alpha)
19 - name: addbmm(Scalar beta, Tensor self, Scalar alpha, Tensor batch1, Tensor batch2, *, Tensor(a!) …
20 aten: addbmm_out(out, self, batch1, batch2, beta, alpha)
22 - name: addbmm(Scalar beta, Tensor self, Tensor batch1, Tensor batch2) -> Tensor
23 aten: addbmm(self, batch1, batch2, beta, 1)
25 - name: addbmm_(Scalar beta, Tensor(a!) self, Tensor batch1, Tensor batch2) -> Tensor(a!)
26 aten: addbmm_(self, batch1, batch2, beta, 1)
[all …]
H A Dderivatives.yaml238 - name: addbmm(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tens…
240 …batch1: maybe_multiply(grad.unsqueeze(0).expand_symint({ batch1.sym_size(0), batch1.sym_size(1), b…
241 …batch2: maybe_multiply(batch1.transpose(1, 2).conj().bmm(grad.unsqueeze(0).expand_symint({ batch1.…
358 - name: baddbmm(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Ten…
360 batch1: maybe_multiply(grad.bmm(batch2.transpose(1, 2).conj()), alpha.conj())
361 batch2: maybe_multiply(batch1.transpose(1, 2).conj().bmm(grad), alpha.conj())
/aosp_15_r20/external/sdk-platform-java/gax-java/gax/src/test/java/com/google/api/gax/rpc/
H A DBatchTest.java65 Batch<LabeledIntList, List<Integer>> batch1 = createBatch(request1); in testMerge() local
70 batch1.merge(batch2); in testMerge()
72 Truth.assertThat(batch1.getByteCount()).isEqualTo(3); in testMerge()
78 Batch<LabeledIntList, List<Integer>> batch1 = createBatch(request1, null); in testMergeStartEmpty() local
79 Truth.assertThat(batch1.getCallable()).isNull(); in testMergeStartEmpty()
84 batch1.merge(batch2); in testMergeStartEmpty()
86 Truth.assertThat(batch1.getByteCount()).isEqualTo(2); in testMergeStartEmpty()
87 Truth.assertThat(batch1.getCallable()).isNotNull(); in testMergeStartEmpty()
88 Truth.assertThat(batch1.getCallable()).isSameInstanceAs(batch2.getCallable()); in testMergeStartEmpty()
113 Batch<LabeledIntList, List<Integer>> batch1 = createBatch(request1); in testBatchMergerImpl() local
[all …]
/aosp_15_r20/external/tensorflow/tensorflow/python/ops/ragged/
H A Dragged_cross_op_test.py245 ragged_const([['batch1-FC1-F1']]),
246 ragged_const([['batch1-FC2-F1']]),
247 ragged_const([['batch1-FC3-F1']])
253 ragged_const([['batch1-FC1-F1']]),
254 ragged_const([['batch1-FC2-F1']]),
255 ragged_const([['batch1-FC3-F1']])
262 ragged_const([['batch1-FC1-F1']]),
263 ragged_const([['batch1-FC2-F1']]),
264 ragged_const([['batch1-FC3-F1']])
271 ragged_const([['batch1-FC1-F1']]),
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/
H A DLinearAlgebra.cpp284 void common_checks_baddbmm_bmm(Meta& meta, const Tensor& batch1, const Tensor& batch2, const Scalar… in common_checks_baddbmm_bmm() argument
285 TORCH_CHECK(batch1.dim() == 3, "batch1 must be a 3D tensor"); in common_checks_baddbmm_bmm()
288 const auto batch1_sizes = batch1.sizes(); in common_checks_baddbmm_bmm()
318 outnames = namedinference::compute_baddbmm_outnames(result, batch1, batch2, self); in common_checks_baddbmm_bmm()
321 outnames = namedinference::compute_bmm_outnames(result, batch1, batch2); in common_checks_baddbmm_bmm()
334 TORCH_META_FUNC(baddbmm)(const Tensor& self, const Tensor& batch1, const Tensor& batch2, const Scal… in TORCH_META_FUNC()
335 auto self_ = expand_size(self, {batch1.size(0), batch1.size(1), batch2.size(2)}, "baddbmm"); in TORCH_META_FUNC()
336 …TORCH_CHECK(self.dtype() == batch1.dtype(), "Input dtypes must be the same, got: input ", self.dty… in TORCH_META_FUNC()
337 common_checks_baddbmm_bmm(*this, batch1, batch2, beta, alpha, false, *self_); in TORCH_META_FUNC()
1549 …Tensor &result, const Tensor &self, const Tensor &batch1, const Tensor &batch2, const Scalar& beta… in addbmm_impl_() argument
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/aosp_15_r20/external/tensorflow/tensorflow/python/data/experimental/kernel_tests/
H A Dmake_batched_features_dataset_test.py129 batch1 = self._run_actual_batch(outputs1)
131 for i in range(len(batch1)):
132 self.assertAllEqual(batch1[i], batch2[i])
158 batch1 = self._run_actual_batch(outputs1)
160 for i in range(len(batch1)):
161 all_equal = all_equal and np.array_equal(batch1[i], batch2[i])
H A Dmake_csv_dataset_test.py728 batch1 = nest.flatten(self.evaluate(next1()))
730 for i in range(len(batch1)):
731 self.assertAllEqual(batch1[i], batch2[i])
758 batch1 = nest.flatten(self.evaluate(next1()))
760 for i in range(len(batch1)):
761 all_equal = all_equal and np.array_equal(batch1[i], batch2[i])
/aosp_15_r20/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/tests/Dialect/lhlo/
H A Dlhlo-legalize-to-affine.mlir251 // CHECK-NEXT: affine.for %[[batch1:.*]] = 0 to 128 {
254 // CHECK-NEXT: %[[a:.*]] = affine.load %[[START_INDICES]][%[[batch0]], %[[batch1]]] : memre…
259 // CHECK-NEXT: %[[prev_value:.*]] = affine.load %[[temp_output]][%[[batch0]], %[[batch1]], …
261 // CHECK-NEXT: affine.store %[[final_value]], %[[temp_output]][%[[batch0]], %[[batch1]], %[…
353 // CHECK-NEXT: affine.for %[[batch1:.*]] = 0 to 5 {
358 // CHECK-NEXT: %[[a:.*]] = affine.load %[[START_INDICES]][%[[batch0]], %c0, %[[batch1]]…
360 // CHECK-NEXT: %[[b:.*]] = affine.load %[[START_INDICES]][%[[batch0]], %c1, %[[batch1]]…
369 // CHECK-NEXT: %[[prev_value:.*]] = affine.load %[[temp_output]][%[[batch0]], %[[batch1…
371 // CHECK-NEXT: affine.store %[[final_value]], %[[temp_output]][%[[batch0]], %[[batch1]]…
407 // CHECK-NEXT: affine.for %[[batch1:.*]] = 0 to 4 {
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/aosp_15_r20/external/pytorch/benchmarks/operator_benchmark/pt/
H A Dbmm_test.py12 "batch1": torch.rand(
28 def forward(self, batch1, batch2): argument
29 return self.op(batch1, batch2)
H A Dadd_test.py119 "batch1": torch.rand(
134 def forward(self, input_one, batch1, batch2): argument
135 return torch.addbmm(input_one, batch1, batch2)
/aosp_15_r20/external/pytorch/aten/src/ATen/native/cuda/
H A DBlas.cpp511 const Tensor& baddbmm_out_cuda_impl(const Tensor& result, const Tensor& self, const Tensor& batch1,… in baddbmm_out_cuda_impl() argument
515 } else if (batch1.size(2) == 0) { in baddbmm_out_cuda_impl()
543 int64_t k = (transpose_result ? batch2 : batch1).sizes()[leading_dim]; in baddbmm_out_cuda_impl()
547 …auto batch1_ = prepare_batch_matrix_for_cublas(transpose_result ? batch2 : batch1, transpose_batch… in baddbmm_out_cuda_impl()
548 …auto batch2_ = prepare_batch_matrix_for_cublas(transpose_result ? batch1 : batch2, transpose_batch… in baddbmm_out_cuda_impl()
607 TORCH_IMPL_FUNC(baddbmm_out_cuda)(const Tensor& self, const Tensor& batch1, const Tensor& batch2, c… in TORCH_IMPL_FUNC()
610 baddbmm_out_cuda_impl(result, self, batch1, batch2, beta, alpha); in TORCH_IMPL_FUNC()
614 TORCH_IMPL_FUNC(bmm_out_cuda)(const Tensor& batch1, const Tensor& batch2, const Tensor &result) { in TORCH_IMPL_FUNC()
619 baddbmm_out_cuda_impl(result, result, batch1, batch2, beta, alpha); in TORCH_IMPL_FUNC()
/aosp_15_r20/packages/modules/Bluetooth/android/app/tests/unit/src/com/android/bluetooth/opp/
DBluetoothOppServiceTest.java169 // batch1 will be removed in deleteShare_deleteShareAndCorrespondingBatch()
170 BluetoothOppBatch batch1 = new BluetoothOppBatch(mService, shareInfo); in deleteShare_deleteShareAndCorrespondingBatch() local
174 mService.mBatches.add(batch1); in deleteShare_deleteShareAndCorrespondingBatch()
/aosp_15_r20/external/pytorch/torch/
H A D_meta_registrations.py2020 def meta_baddbmm(self, batch1, batch2, *, beta=1, alpha=1): argument
2021 dim1 = batch1.size(0)
2022 dim2 = batch1.size(1)
2025 torch._check(batch1.dim() == 3, lambda: "batch1 must be a 3D tensor")
2028 self.dtype == batch1.dtype == batch2.dtype,
2029 …lambda: f"Input dtypes must be the same, got: input: {self.dtype}, batch1: {batch1.dtype}, batch2:…
2031 batch1_sizes = batch1.shape
3129 def meta_addbmm(self, batch1, batch2, *, beta=1, alpha=1): argument
3130 dim1 = batch1.size(1)
3133 torch._check(batch1.dim() == 3, lambda: "batch1 must be a 3D tensor")
[all …]
/aosp_15_r20/external/pytorch/test/distributed/fsdp/
H A Dtest_fsdp_grad_acc.py154 for batch1, batch2 in itertools.combinations(batches, r=2):
155 for t1, t2 in zip(batch1, batch2):
/aosp_15_r20/external/pytorch/aten/src/ATen/functorch/
H A DBatchRulesLinearAlgebra.cpp126 …const Tensor& input, const Tensor& batch1, const Tensor& batch2, const Scalar& beta, const Scalar&… in addbmm_decomp() argument
127 Tensor out = at::bmm(batch1, batch2).sum(0); in addbmm_decomp()
138 …const Tensor& input, const Tensor& batch1, const Tensor& batch2, const Scalar& beta, const Scalar&… in baddbmm_decomp() argument
139 Tensor out = at::bmm(batch1, batch2); in baddbmm_decomp()
/aosp_15_r20/packages/modules/NeuralNetworks/common/cpu_operations/
DLayerNormLSTMTest.cpp381 { // Batch1: 3 (input_sequence_size) * 5 (n_input) in TEST()
395 // Batch1: 3 (input_sequence_size) * 3 (n_output) in TEST()
/aosp_15_r20/external/tensorflow/tensorflow/compiler/tests/
H A Dimage_ops_test.py55 batch1 = image_ops.rgb_to_hsv(batch0)
56 batch2 = image_ops.hsv_to_rgb(batch1)
63 batch1, batch2, join1, join2 = sess.run([batch1, batch2, join1, join2],
67 self.assertAllCloseAccordingToType(batch1, join1, half_rtol=0.000002)
/aosp_15_r20/external/perfetto/ui/src/trace_processor/
H A Dquery_result_unittest.ts241 const batch1 = protos.QueryResult.create({ constant
264 qr.appendResultBatch(protos.QueryResult.encode(batch1).finish());
/aosp_15_r20/external/tensorflow/tensorflow/python/ops/
H A Dimage_ops_test.py73 batch1 = image_ops.rgb_to_hsv(batch0)
74 batch2 = image_ops.hsv_to_rgb(batch1)
80 batch1, batch2, join1, join2 = self.evaluate(
81 [batch1, batch2, join1, join2])
84 self.assertAllClose(batch1, join1)
129 batch1 = image_ops.rgb_to_yiq(batch0)
130 batch2 = image_ops.yiq_to_rgb(batch1)
136 batch1, batch2, join1, join2 = self.evaluate(
137 [batch1, batch2, join1, join2])
140 self.assertAllClose(batch1, join1, rtol=1e-4, atol=1e-4)
[all …]
/aosp_15_r20/external/pytorch/test/xpu/
H A Dtest_gemm.py751 batch1 = torch.rand((1, 2, 2), dtype=torch.float32, device=device)
756 y = torch.baddbmm(input_tensor, batch1, batch2, beta=0.0)
759 y_ref = torch.bmm(batch1, batch2)
760 y = torch.baddbmm(input_tensor, batch1, batch2, beta=0.0, out=out)
/aosp_15_r20/external/tensorflow/tensorflow/compiler/mlir/tfr/tests/
H A Dend2end.mlir213 %batch1 = "tfr.cast"(%batch) : (tensor<i64>) -> !tfr.tensor
218 …%ret = tfr.call @tf__map_and_batch_dataset_v0(%input_dataset, %batch1, %calls1, %drop1, %other_arg…
/aosp_15_r20/external/rust/android-crates-io/crates/quiche/deps/boringssl/src/tool/
Dspeed.cc1382 !SpeedTrustToken("TrustToken-Exp1-Batch1", TRUST_TOKEN_experiment_v1(), 1, in Speed()
1386 !SpeedTrustToken("TrustToken-Exp2VOPRF-Batch1", in Speed()
1390 !SpeedTrustToken("TrustToken-Exp2PMB-Batch1", in Speed()

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