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/aosp_15_r20/external/executorch/backends/vulkan/runtime/graph/ops/impl/
H A DBatchNorm.cpp29 "native_batch_norm requires ", in check_and_prepack_arg()
101 void native_batch_norm(ComputeGraph& graph, const std::vector<ValueRef>& args) { in native_batch_norm() function
109 aten._native_batch_norm_legit_no_training.default, native_batch_norm);
/aosp_15_r20/external/executorch/backends/transforms/
H A Dfuse_batch_norm_with_conv.py47 bn.target != exir_ops.edge.aten.native_batch_norm.default
66 bn.target == exir_ops.edge.aten.native_batch_norm.default
82 # args[7] for native_batch_norm, but args[6] for
/aosp_15_r20/external/executorch/backends/xnnpack/_passes/
H A Dfuse_batch_norm_with_conv.py45 bn.target != exir_ops.edge.aten.native_batch_norm.default
64 bn.target == exir_ops.edge.aten.native_batch_norm.default
80 # args[7] for native_batch_norm, but args[6] for
/aosp_15_r20/external/pytorch/test/lazy/
H A Dtest_reuse_ir.py116 # so we call `torch.ops.aten.native_batch_norm` to bypass the checks.
117 z, _, _ = torch.ops.aten.native_batch_norm(
129 z_lazy, _, _ = torch.ops.aten.native_batch_norm(
/aosp_15_r20/external/pytorch/aten/src/ATen/functorch/
H A DBatchRulesNorm.cpp848 …OT good. In the ideal world, we do NOT want to convert the new legit op back into native_batch_norm
849 // as native_batch_norm has a problematic schema--it promises it is functional when it is not. Howe…
851 // make native_batch_norm composite implicit within a few weeks and we can fix this before vmap wor…
855 …return at::native_batch_norm(self, weight_opt, bias_opt, running_mean, running_var, train, momentu… in _native_batch_norm_legit_batch()
861 …return at::native_batch_norm(self, weight_opt, bias_opt, Tensor(), Tensor(), train, momentum, eps); in _native_batch_norm_legit_no_stats_batch()
865 VMAP_SUPPORT(native_batch_norm, NATIVE_BATCH_NORM_BATCH_RULE(native_batch_norm)); in TORCH_LIBRARY_IMPL()
/aosp_15_r20/external/executorch/exir/tests/
H A Ddynamic_shape_models.py14 batch_norm_op = torch.ops.aten.native_batch_norm.default
40 if nd.target == torch.ops.aten.native_batch_norm.out
/aosp_15_r20/external/pytorch/torch/jit/
H A D_shape_functions.py1135 def native_batch_norm( function
1435 …"aten::native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor?…
1436 native_batch_norm,
1440 native_batch_norm,
1444 native_batch_norm,
/aosp_15_r20/external/pytorch/test/
H A Dtest_decomp.py194 (torch.bfloat16, torch.ops.aten.native_batch_norm.default): 1e-5,
195 (torch.float16, torch.ops.aten.native_batch_norm.default): 1e-5,
411 # native_batch_norm is only implicit when python dispatcher is on (and noncomposite otherwise)
412 (None, None, "native_batch_norm"),
716 res = torch._decomp.decompositions.native_batch_norm(
H A Dtest_meta.py738 torch.native_batch_norm: {bf16, f16},
755 torch.native_batch_norm: {f32, f64},
881 aten.native_batch_norm.default: {bf16, f16},
908 aten.native_batch_norm.default: {f32, f64},
916 aten.native_batch_norm.out: {bf16, f16, f32, f64}
/aosp_15_r20/external/pytorch/aten/src/ATen/native/
H A Dgroup_norm.cpp15 #include <ATen/ops/native_batch_norm.h>
230 auto outputs = at::native_batch_norm( in math_group_norm()
H A Dlayer_norm.cpp18 #include <ATen/ops/native_batch_norm.h>
240 auto outputs = at::native_batch_norm( in math_native_layer_norm()
H A Dts_native_functions.yaml87 - native_batch_norm
/aosp_15_r20/external/pytorch/test/functorch/
H A Dtest_ops.py563 "native_batch_norm"
1037 xfail("native_batch_norm"),
1152 skip("native_batch_norm"),
1314 xfail("native_batch_norm"),
1561 xfail("native_batch_norm"),
1676 xfail("native_batch_norm"),
2060 xfail("native_batch_norm"),
/aosp_15_r20/external/pytorch/torchgen/
H A Dmodel.py2503 # (native_batch_norm is a good example, although this isn't the case today).
2510 # native_batch_norm (mutable variant)
2511 # native_batch_norm.functional (functional variant)
2516 # native_batch_norm.mutable (mutable variant)
2517 # native_batch_norm (functional variant)
2558 # for now on ops that have a functional + mutable variant (like native_batch_norm).
/aosp_15_r20/external/pytorch/test/quantization/eager/
H A Dtest_fuse_eager.py92 …with self.assertRaisesRegex(RuntimeError, "Could not run 'aten::native_batch_norm' with arguments …
101 …with self.assertRaisesRegex(RuntimeError, "Could not run 'aten::native_batch_norm' with arguments …
/aosp_15_r20/external/pytorch/torch/csrc/utils/
H A Dschema_info.cpp286 …{"aten::native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor… in getTrainingOps()
288 …{"aten::native_batch_norm.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Te… in getTrainingOps()
/aosp_15_r20/external/pytorch/torch/_decomp/
H A Ddecompositions.py1874 @register_decomposition(aten.native_batch_norm)
1876 def native_batch_norm( function
1892 # TODO: this decomposition is NOT here to stay. We would much prefer replacing native_batch_norm
1900 …In two weeks or so, we should remove this decomposition and phase out the current native_batch_norm
1902 @aten.native_batch_norm.default.py_impl(DispatchKey.Autograd)
1903 @aten.native_batch_norm.default.py_impl(DispatchKey.CompositeImplicitAutograd)
2201 # native_batch_norm needs to decompose into other ops before autograd.
2215 a, b, c = aten.native_batch_norm(
/aosp_15_r20/external/pytorch/functorch/op_analysis/
H A Dpublic_api437 native_batch_norm
/aosp_15_r20/external/executorch/kernels/aten/
H A Dfunctions.yaml274 - op: native_batch_norm.out
/aosp_15_r20/external/pytorch/torch/_inductor/
H A Ddecomposition.py74 aten.native_batch_norm,
763 a, b, c = aten.native_batch_norm(
/aosp_15_r20/external/pytorch/benchmarks/dynamo/microbenchmarks/operator_inp_logs/timm_train/
H A Dconvmixer_768_32_training.txt32 Operator: aten.native_batch_norm.default
/aosp_15_r20/external/pytorch/test/edge/
H A Dselected_operators.yaml266 aten::native_batch_norm.out:
/aosp_15_r20/external/pytorch/benchmarks/dynamo/microbenchmarks/operator_inp_logs/torchbench_train/
H A Ddcgan_training.txt29 Operator: aten.native_batch_norm.default
/aosp_15_r20/external/pytorch/torch/csrc/jit/runtime/
H A Dserialized_shape_function_registry.cpp3001 def native_batch_norm(input: List[int],
3324 …native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? runnin… in GetShapeFunctionMappings()
3325 …_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)", "native_batch_norm"}, in GetShapeFunctionMappings()
3326 …_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)", "native_batch_norm"}, in GetShapeFunctionMappings()
H A Dautodiff.cpp44 …"aten::native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor?… in isDifferentiable()
256 …"aten::native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor?… in buildSymbolicGradient()

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