| /aosp_15_r20/external/pytorch/aten/src/ATen/native/cuda/ |
| H A D | Normalization.cu | 435 …l train, double momentum, double epsilon, Tensor& output, Tensor& save_mean, Tensor& save_invstd) { in batch_norm_cuda_out() argument
441 batch_norm_mean_var(self, save_mean, save_invstd); in batch_norm_cuda_out()
445 save_mean, save_invstd, *running_mean_opt, *running_var_opt, in batch_norm_cuda_out()
448 batch_norm_calc_invstd(save_invstd, save_invstd, epsilon); in batch_norm_cuda_out()
454 batch_norm_calc_invstd(save_invstd, running_var_opt.value(), epsilon); in batch_norm_cuda_out()
457 batch_norm_elementwise(output, self, weight_opt, bias_opt, save_mean, save_invstd); in batch_norm_cuda_out()
458 return std::tuple<Tensor&, Tensor&, Tensor&>(output, save_mean, save_invstd); in batch_norm_cuda_out()
467 auto save_invstd = at::empty({n_input}, options); in batch_norm_cuda() local
480 save_invstd); in batch_norm_cuda()
481 return std::make_tuple(output, save_mean, save_invstd); in batch_norm_cuda()
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| H A D | Normalization.cuh | 366 …onst GenericPackedTensorAccessor<const stat_accscalar_t, 1, DefaultPtrTraits, index_t> save_invstd, in batch_norm_backward_kernel() argument
376 invstd = save_invstd[plane]; in batch_norm_backward_kernel()
644 auto save_invstd = packed_accessor_or_dummy< in batch_norm_backward_cuda_template() local
645 const accscalar_t, 1, DefaultPtrTraits, index_t>(save_invstd_, "save_invstd"); in batch_norm_backward_cuda_template()
654 save_mean, save_invstd, train, epsilon); in batch_norm_backward_cuda_template()
764 auto save_invstd = get_packed_accessor< in batch_norm_gather_stats_cuda_template() local
765 accscalar_t, 1, RestrictPtrTraits, index_t>(save_invstd_, "save_invstd"); in batch_norm_gather_stats_cuda_template()
771 (mean, invstd, save_mean, save_invstd, running_mean, running_var, epsilon, momentum, counts); in batch_norm_gather_stats_cuda_template()
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| /aosp_15_r20/external/pytorch/aten/src/ATen/native/cpu/ |
| H A D | batch_norm_kernel.cpp | 34 const Tensor& save_mean, const Tensor& save_invstd, in batch_norm_cpu_collect_linear_and_constant_terms() argument
41 auto save_invstd_a = conditional_accessor_1d<const param_t>(save_invstd); in batch_norm_cpu_collect_linear_and_constant_terms()
76 const Tensor& weight, const Tensor& bias, const Tensor& save_mean, const Tensor& save_invstd, in batch_norm_cpu_contiguous_impl() argument
91 save_mean, save_invstd, running_mean, running_var, train, eps); in batch_norm_cpu_contiguous_impl()
128 const Tensor& weight, const Tensor& bias, const Tensor& save_mean, const Tensor& save_invstd, in batch_norm_cpu_channels_last_impl() argument
143 save_mean, save_invstd, running_mean, running_var, train, eps); in batch_norm_cpu_channels_last_impl()
407 …ensor& running_mean, const Tensor& running_var, const Tensor& save_mean, const Tensor& save_invstd, in batch_norm_cpu_backward_contiguous_impl() argument
431 auto save_invstd_a = conditional_accessor_1d<const scalar_t>(save_invstd); in batch_norm_cpu_backward_contiguous_impl()
530 …ensor& running_mean, const Tensor& running_var, const Tensor& save_mean, const Tensor& save_invstd, in batch_norm_cpu_backward_channels_last_impl() argument
548 scalar_t* save_invstd_data = conditional_data_ptr<scalar_t>(save_invstd); in batch_norm_cpu_backward_channels_last_impl()
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| /aosp_15_r20/external/pytorch/aten/src/ATen/native/ |
| H A D | Normalization.cpp | 137 const Tensor& save_mean /* optional */, const Tensor& save_invstd /* optional */, in batch_norm_cpu_transform_input_template() argument
152 save_mean, save_invstd, running_mean, running_var, train, eps); in batch_norm_cpu_transform_input_template()
154 return std::make_tuple(output, save_mean, save_invstd); in batch_norm_cpu_transform_input_template()
171 return save_invstd; in batch_norm_cpu_transform_input_template()
196 return std::make_tuple(output, save_mean, save_invstd); in batch_norm_cpu_transform_input_template()
305 …ensor& running_mean, const Tensor& running_var, const Tensor& save_mean, const Tensor& save_invstd, in batch_norm_backward_cpu_template() argument
337 grad_out_, input, weight, running_mean, running_var, save_mean, save_invstd, train, eps); in batch_norm_backward_cpu_template()
349 auto save_invstd_a = conditional_accessor_1d<const param_t>(save_invstd); in batch_norm_backward_cpu_template()
557 auto save_invstd = at::empty_symint(c10::SymIntArrayRef({std::move(num_features)}), options); in _batch_norm_impl_index() local
564 out, save_mean, save_invstd, reserve, 0); in _batch_norm_impl_index()
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| H A D | native_functions.yaml | 4296 …mentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!)…
4321 …mentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!)…
4335 …mentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!)…
4365 … Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, fl…
6590 …mentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd, Tensor(g!) res…
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| /aosp_15_r20/external/pytorch/torch/_decomp/ |
| H A D | decompositions_for_jvp.py | 223 save_invstd: Optional[Tensor],
235 invstd = save_invstd
238 save_mean is not None and save_invstd is not None
239 ), "when train=True, save_mean and save_invstd are required"
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| H A D | decompositions.py | 1875 @out_wrapper("out", "save_mean", "save_invstd")
2251 save_invstd: Optional[Tensor],
2264 save_invstd,
2279 save_invstd: Optional[Tensor],
2307 save_invstd,
2380 save_invstd: Optional[Tensor],
2396 save_invstd,
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| /aosp_15_r20/external/pytorch/aten/src/ATen/native/mkldnn/ |
| H A D | Normalization.cpp | 257 const Tensor& save_invstd = c10::value_or_else(save_invstd_opt, [] {return Tensor();}); in mkldnn_batch_norm_backward() local
264 ideep::tensor& v = itensor_from_mkldnn(save_invstd); in mkldnn_batch_norm_backward()
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| /aosp_15_r20/external/pytorch/torch/csrc/autograd/ |
| H A D | FunctionsManual.h | 719 const std::optional<Tensor>& save_invstd,
813 const Tensor& save_invstd,
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| H A D | FunctionsManual.cpp | 4662 const std::optional<Tensor>& save_invstd, in batchnorm_double_backward() argument
4686 // for half inputs, save_mean, save_invstd are float (ideally, we would cast in batchnorm_double_backward()
4694 training ? toNonOptTensor(save_invstd).to(input.scalar_type()) in batchnorm_double_backward()
4813 auto save_invstd = save_invstd_t.reshape({M, 1}); in layer_norm_double_backward() local
4836 // for half inputs, save_mean, save_invstd are float in layer_norm_double_backward()
4840 auto sigma2_eps_neg_1_2 = save_invstd.to(input.scalar_type()); in layer_norm_double_backward()
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| /aosp_15_r20/external/pytorch/torch/csrc/utils/ |
| H A D | schema_info.cpp | 288 …mentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!)… in getTrainingOps()
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| /aosp_15_r20/external/pytorch/torch/csrc/lazy/core/ |
| H A D | shape_inference.h | 64 …:optional<at::Tensor> & save_mean, const ::std::optional<at::Tensor> & save_invstd, bool train, do…
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| H A D | shape_inference.cpp | 577 const ::std::optional<at::Tensor>& save_invstd, in compute_shape_native_batch_norm_backward()
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| /aosp_15_r20/external/pytorch/test/ |
| H A D | test_meta.py | 1497 …save_invstd = torch.zeros((sample.input.shape[1], ), device=device, dtype=dtype) if train else None
1500 save_mean, save_invstd, train, sample.kwargs.get("eps", 1e-5)]
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| /aosp_15_r20/external/pytorch/tools/autograd/ |
| H A D | derivatives.yaml | 1219 … Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, fl…
1220 … grads[2], grad_out, running_mean, running_var, train, eps, save_mean, save_invstd, grad_input_mas…
1222 save_invstd: not_implemented("native_batch_norm_backward save_invstd")
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| /aosp_15_r20/external/pytorch/test/cpp/jit/ |
| H A D | test_misc.cpp | 277 // save_invstd, bool train, float eps, bool[3] output_mask) -> (Tensor, in TEST()
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