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/aosp_15_r20/external/tensorflow/tensorflow/compiler/xla/service/
H A Dbatchnorm_expander.cc50 Status HandleBatchNormTraining(HloInstruction* batch_norm) override;
52 Status HandleBatchNormInference(HloInstruction* batch_norm) override;
54 Status HandleBatchNormGrad(HloInstruction* batch_norm) override;
152 HloInstruction* batch_norm) { in HandleBatchNormTraining() argument
160 added_inst->set_metadata(batch_norm->metadata()); in HandleBatchNormTraining()
171 HloInstruction* operand = batch_norm->mutable_operand(0); in HandleBatchNormTraining()
174 int64_t feature_index = batch_norm->feature_index(); in HandleBatchNormTraining()
176 HloInstruction* scale = batch_norm->mutable_operand(1); in HandleBatchNormTraining()
177 HloInstruction* offset = batch_norm->mutable_operand(2); in HandleBatchNormTraining()
184 auto epsilon_literal = LiteralUtil::CreateR0(batch_norm->epsilon()); in HandleBatchNormTraining()
[all …]
H A Dhlo_element_type_converter_test.cc112 ::testing::Matcher<const ::xla::HloInstruction*> batch_norm = in TEST_F()
115 op::Tuple(op::Convert(op::GetTupleElement(batch_norm, 0)), in TEST_F()
116 op::Convert(op::GetTupleElement(batch_norm, 1)), in TEST_F()
117 op::Convert(op::GetTupleElement(batch_norm, 2)))); in TEST_F()
/aosp_15_r20/external/tensorflow/tensorflow/compiler/mlir/tensorflow/transforms/
H A Dgpu_fusion.cc70 auto batch_norm = dyn_cast_or_null<FusedBatchNormV3Op>(relu_input); in matchAndRewrite() local
73 if (!batch_norm) { in matchAndRewrite()
79 batch_norm = in matchAndRewrite()
81 if (batch_norm) { in matchAndRewrite()
85 batch_norm = in matchAndRewrite()
87 if (!batch_norm) return failure(); in matchAndRewrite()
91 assert(batch_norm); in matchAndRewrite()
92 if (batch_norm.is_training()) return failure(); in matchAndRewrite()
93 if (!batch_norm.y().hasOneUse()) return failure(); in matchAndRewrite()
96 OperationState state(batch_norm.getLoc(), in matchAndRewrite()
[all …]
/aosp_15_r20/external/pytorch/torch/ao/nn/intrinsic/modules/
H A Dfused.py169 def __init__(self, batch_norm, relu): argument
171 type_before_parametrizations(batch_norm) == BatchNorm2d
173 …), f"Incorrect types for input modules{type_before_parametrizations(batch_norm)}{type_before_param…
174 super().__init__(batch_norm, relu)
181 def __init__(self, batch_norm, relu): argument
183 type_before_parametrizations(batch_norm) == BatchNorm3d
185 …), f"Incorrect types for input modules{type_before_parametrizations(batch_norm)}{type_before_param…
186 super().__init__(batch_norm, relu)
/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/functional/
H A Dbatchnorm.h13 inline Tensor batch_norm( in batch_norm() function
38 return torch::batch_norm( in batch_norm()
53 /// https://pytorch.org/docs/main/nn.functional.html#torch.nn.functional.batch_norm
62 /// F::batch_norm(input, mean, variance,
65 inline Tensor batch_norm(
70 return detail::batch_norm(
/aosp_15_r20/external/tensorflow/tensorflow/python/ops/
H A Dbatch_norm_benchmark.py47 # batch_norm = (tensor - mean) * tf.math.rsqrt(variance + 0.001)
49 # batch_norm *= gamma
50 # return batch_norm + beta
58 batch_norm = (tensor - mean) * math_ops.rsqrt(variance + 0.001)
60 batch_norm *= gamma
61 return batch_norm + beta
/aosp_15_r20/external/pytorch/torch/testing/_internal/
H A Djit_metaprogramming_utils.py169 ('batch_norm', (S, S),
172 ('batch_norm', (0, S, S, S),
176 ('batch_norm', (0, S, S, S),
180 ('batch_norm', (S, S),
184 ('batch_norm', (S, S), (non_differentiable(torch.randn(S)), non_differentiable(torch.ones(S)),
187 ('batch_norm', (S, S), (non_differentiable(torch.randn(S)), non_differentiable(torch.ones(S)),
190 ('batch_norm', (S, S), (non_differentiable(torch.randn(S)), non_differentiable(torch.ones(S)),
193 ('batch_norm', (S, S), (non_differentiable(torch.randn(S)), non_differentiable(torch.ones(S)),
196 ('batch_norm', (S, S), (non_differentiable(torch.randn(S)), non_differentiable(torch.ones(S)),
199 ('batch_norm', (S, S), (non_differentiable(torch.randn(S)), non_differentiable(torch.ones(S)),
/aosp_15_r20/external/pytorch/torch/onnx/
H A Dsymbolic_opset14.py34 "batch_norm",
67 @_onnx_symbolic("aten::batch_norm")
69 def batch_norm( function
97 symbolic_helper.check_training_mode(training, "batch_norm")
/aosp_15_r20/external/pytorch/benchmarks/functional_autograd_benchmark/
H A Dtorchaudio_models.py187 batch_norm=True, argument
193 self.batch_norm = (
194 SequenceWise(nn.BatchNorm1d(input_size)) if batch_norm else None
208 if self.batch_norm is not None:
209 x = self.batch_norm(x)
307 batch_norm=False,
/aosp_15_r20/external/pytorch/torch/csrc/jit/passes/
H A Ddecompose_ops.cpp36 …"aten::batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? runnin… in isDecomposableNorm()
121 …"aten::batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? runnin… in DecomposeOps()
140 toGraphFunction(decompose_funcs.get_function("batch_norm")).graph(); in DecomposeOps()
199 …def batch_norm(input : Tensor, running_mean : Optional[Tensor], running_var : Optional[Tensor], tr… in DecomposeOps()
/aosp_15_r20/external/tensorflow/tensorflow/tools/compatibility/
H A Dreorders_v2.py40 …'dropout', 'input_layer_partitioner', 'config', 'warm_start_from', 'loss_reduction', 'batch_norm'],
41 …ut_layer_partitioner', 'config', 'warm_start_from', 'loss_reduction', 'batch_norm', 'linear_sparse…
42 …ut_layer_partitioner', 'config', 'warm_start_from', 'loss_reduction', 'batch_norm', 'linear_sparse…
43 …'dropout', 'input_layer_partitioner', 'config', 'warm_start_from', 'loss_reduction', 'batch_norm'],
/aosp_15_r20/external/pytorch/torch/ao/quantization/pt2e/
H A Dutils.py174 torch.ops.aten.batch_norm.default,
283 if bn_node.target == torch.ops.aten.batch_norm.default:
284 # With the new training ir, instead of batch_norm + getitem,
285 # we only have the batch_norm node.
331 torch.ops.aten.batch_norm.default,
H A Dqat_utils.py97 x = F.batch_norm(
135 x = F.batch_norm(
175 x = F.batch_norm(
271 x = F.batch_norm(
325 x = F.batch_norm(
/aosp_15_r20/external/pytorch/functorch/op_analysis/
H A Dgen_data.py88 if "batch_norm" in op["name"]:
89 categorization["batch_norm"] += 1
90 op["meta"] = "batch_norm"
/aosp_15_r20/external/tensorflow/tensorflow/core/kernels/
H A Dconv_ops_benchmark_test.cc65 Node* batch_norm; member
71 Node* batch_norm; member
187 TF_CHECK_OK(NodeBuilder(graph->NewName("batch_norm"), "FusedBatchNorm") in Conv2DWithBatchNorm()
214 Node* batch_norm = conv_graph.batch_norm; in Conv2DWithBatchNormAndActivation() local
218 .Input(batch_norm) in Conv2DWithBatchNormAndActivation()
222 return {graph, conv2d, batch_norm, activation}; in Conv2DWithBatchNormAndActivation()
/aosp_15_r20/external/tensorflow/tensorflow/core/grappler/optimizers/
H A Dremapper_test.cc57 ops::FusedBatchNorm bn(s.WithOpName("batch_norm"), x, scale, offset, mean, in TEST_F()
62 item.fetch = {"batch_norm"}; in TEST_F()
94 ops::FusedBatchNorm bn(s.WithOpName("batch_norm").WithDevice("/device:GPU:0"), in TEST_F()
99 item.fetch = {"batch_norm"}; in TEST_F()
1744 auto batch_norm = ops::FusedBatchNorm(s.WithOpName("batch_norm"), conv, scale, in TEST_F() local
1746 auto fetch = ops::Identity(s.WithOpName("fetch"), batch_norm.y); in TEST_F()
1773 if (node.name() == "batch_norm") { in TEST_F()
1823 auto batch_norm = ops::FusedBatchNorm(s.WithOpName("batch_norm"), conv, in TEST_F() local
1833 return ops::Identity(fetch, ops::Relu(activate, batch_norm.y)); in TEST_F()
1835 return ops::Identity(fetch, ops::Relu6(activate, batch_norm.y)); in TEST_F()
[all …]
/aosp_15_r20/external/pytorch/test/jit/
H A Dtest_freezing.py2111 FileCheck().check("conv").check("aten::batch_norm").run(scripted_mod.graph)
2116 FileCheck().check("conv").check_not("aten::batch_norm").run(
2120 FileCheck().check("conv").check("aten::batch_norm").run(
2148 FileCheck().check("conv").check("aten::batch_norm").run(
2156 FileCheck().check("conv").check_not("aten::batch_norm").run(
2184 FileCheck().check("conv").check_not("aten::batch_norm").run(scripted_mod.graph)
2341 FileCheck().check("conv").check_not("aten::batch_norm").run(
2396 FileCheck().check("linear").check("aten::batch_norm").run(
2403 FileCheck().check("linear").check_not("aten::batch_norm").run(
2407 FileCheck().check("linear").check("aten::batch_norm").run(
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/vulkan/ops/
H A DBatchnorm.cpp74 Tensor batch_norm( in batch_norm() function
99 m.impl(TORCH_SELECTIVE_NAME("aten::batch_norm"), TORCH_FN(batch_norm)); in TORCH_LIBRARY_IMPL()
/aosp_15_r20/external/pytorch/torch/jit/
H A D_freeze.py165 assert "batch_norm" in str(frozen_mod.graph)
167 assert "batch_norm" not in str(frozen_mod.graph)
210 assert "batch_norm" not in str(frozen_mod.graph)
/aosp_15_r20/external/pytorch/torch/csrc/jit/passes/quantization/
H A Dquantization_patterns.h622 // quantized::batch_norm in quant_fusion_pattern_and_replacements()
623 std::string batch_norm = R"( in quant_fusion_pattern_and_replacements() local
626 … %r_bn = aten::batch_norm(%a_dequant, %weight, %bias, %mean, %var, %training, %eaf, %eps, %7) in quant_fusion_pattern_and_replacements()
631 … %r = quantized::batch_norm(%a_quant, %weight, %bias, %mean, %var, %eps, %scale, %zero_point) in quant_fusion_pattern_and_replacements()
637 … %bn_out = aten::batch_norm(%a_dequant, %weight, %bias, %mean, %var, %training, %eaf, %eps, %7) in quant_fusion_pattern_and_replacements()
644 … %bn_out = aten::batch_norm(%a_dequant, %weight, %bias, %mean, %var, %training, %eaf, %eps, %7) in quant_fusion_pattern_and_replacements()
1008 {"quantized::batch_norm", in quant_fusion_pattern_and_replacements()
1009 std::move(batch_norm), in quant_fusion_pattern_and_replacements()
H A Dhelper.cpp25 "batch_norm",
48 "batch_norm",
213 CallFuncArgs _observe_inputs_call_func = {{"batch_norm", 1}};
784 "__torch__.mobile_cv.arch.layers.batch_norm.NaiveSyncBatchNorm"); in is_batchnorm2d_module()
/aosp_15_r20/external/tensorflow/tensorflow/compiler/xla/service/gpu/
H A Dir_emitter.h92 Status HandleBatchNormInference(HloInstruction* batch_norm) override;
93 Status HandleBatchNormTraining(HloInstruction* batch_norm) override;
94 Status HandleBatchNormGrad(HloInstruction* batch_norm) override;
/aosp_15_r20/external/pytorch/torch/_functorch/
H A Dtop_operators_github_usage.py296 ("nn.functional.batch_norm", 413),
405 ("nn.BatchNorm2d", 233265, "nn.functional.batch_norm"),
416 ("nn.BatchNorm1d", 65374, "nn.functional.batch_norm"),
437 ("nn.BatchNorm3d", 16378, "nn.functional.batch_norm"),
/aosp_15_r20/external/executorch/backends/cadence/aot/
H A Dfuse_ops.py193 # We want to discover a chain of conv1d -> batch_norm.
202 # The single user of conv op must be batch_norm. If not, bail.
301 # quantized::batch_norm. Only proceed if the current node is a
313 # The single user of conv op must be batch_norm. If not, bail.
365 # Assert that we have discovered the batch_norm op's tensors
/aosp_15_r20/external/pytorch/benchmarks/tensorexpr/
H A Dpt_engine.py33 def batch_norm(self, data, mean, var, training): member in TorchTensorEngine
34 return torch.nn.functional.batch_norm(data, mean, var, training=training)

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