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/aosp_15_r20/external/pytorch/torch/distributed/_shard/sharding_spec/chunk_sharding_spec_ops/
H A Dembedding_bag.py102 per_sample_weights = kwargs.get("per_sample_weights")
123 per_sample_weights,
139 per_sample_weights,
168 per_sample_weights = kwargs.get("per_sample_weights")
180 if per_sample_weights is not None and not isinstance(
181 per_sample_weights, torch.Tensor
183 raise TypeError("per_sample_weights need to be torch.Tensor")
207 if per_sample_weights is not None and per_sample_weights.size() != input.size():
209 … f"per_sample_weights size {per_sample_weights.size()} not equal to input size {input.size()}"
245 per_sample_weights, argument
[all …]
H A D_common.py116 gathered_per_sample_weights: per_sample_weights across all ranks.
136 per_sample_weights=gathered_per_sample_weights[i]
/aosp_15_r20/external/pytorch/test/nn/
H A Dtest_embedding.py656 per_sample_weights = indices.ne(padding_idx).to(dtype).unsqueeze(-1)
657 res = embedding.mul(per_sample_weights).sum(dim=reduction_dim)
660 weights_sum = per_sample_weights.sum(dim=reduction_dim)
800 per_sample_weights = (
805 per_sample_weights = (None,)
807 for p_s_weights, idx in itertools.product(per_sample_weights, (idx1, idx2)):
813 per_sample_weights=p_s_weights,
880 # Failure 1: mismatched embeddings / per_sample_weights dtype
884 per_sample_weights = torch.randn_like(input, dtype=torch.double, device=device)
887 es(input, offsets, per_sample_weights)
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/
H A DEmbeddingBag.cpp493 // mul (scaling by per_sample_weights)
875 const std::optional<Tensor>& per_sample_weights, in check_arguments() argument
899 if (per_sample_weights.has_value() && per_sample_weights.value().defined()) { in check_arguments()
902 "embedding_bag: per_sample_weights only supported with mode='sum'"); in check_arguments()
904 per_sample_weights.value(),"per_sample_weights", 1); in check_arguments()
906 TORCH_CHECK(per_sample_weights.value().dim() == 1); in check_arguments()
907 TORCH_CHECK(per_sample_weights.value().numel() == indices.numel()); in check_arguments()
972 const std::optional<Tensor>& per_sample_weights, in make_offset2bag_out() argument
976 bool fast_path_sum = is_fast_path(weight, per_sample_weights, output, padding_idx); in make_offset2bag_out()
1028 const std::optional<Tensor>& per_sample_weights, in make_offset2bag() argument
[all …]
H A DEmbeddingBag.h30 const std::optional<Tensor>& per_sample_weights,
57 const std::optional<Tensor>& per_sample_weights,
132 const std::optional<Tensor>& per_sample_weights = std::nullopt,
148 const std::optional<at::Tensor>& per_sample_weights,
H A DNonSymbolicBC.h19 …freq, int64_t mode, bool sparse, const std::optional<at::Tensor> & per_sample_weights, int64_t pad…
20 …cale_grad_by_freq, int64_t mode, const std::optional<at::Tensor> & per_sample_weights, int64_t pad…
/aosp_15_r20/external/pytorch/aten/src/ATen/native/cuda/
H A DEmbeddingBag.cu60 // per_sample_weights are contiguous.
110 // per_sample_weights are contiguous.
117 const scalar_t* per_sample_weights, int64_t per_sample_weights_stride, in EmbeddingBag_updateOutputKernel_sum_mean() argument
144 if (per_sample_weights) { in EmbeddingBag_updateOutputKernel_sum_mean()
146 per_sample_weights[emb * per_sample_weights_stride]); in EmbeddingBag_updateOutputKernel_sum_mean()
175 const Tensor& per_sample_weights, in embedding_bag_backward_cuda_sum_avg() argument
236 bag_size, per_sample_weights); in embedding_bag_backward_cuda_sum_avg()
316 const Tensor& per_sample_weights = *per_sample_weights_maybe_owned; in _embedding_bag_forward_only_cuda() local
325 per_sample_weights, in _embedding_bag_forward_only_cuda()
350 const Tensor& per_sample_weights = *per_sample_weights_maybe_owned; in _embedding_bag_cuda() local
[all …]
H A DEmbeddingBackwardKernel.cu85 const scalar_t* per_sample_weights, int64_t per_sample_weights_stride, in compute_grad_weight_bags() argument
110 if (per_sample_weights) { in compute_grad_weight_bags()
111 scale *= per_sample_weights[origRow * per_sample_weights_stride]; in compute_grad_weight_bags()
222 const Tensor &per_sample_weights) { in embedding_backward_cuda_kernel() argument
327 per_sample_weights.defined() ? per_sample_weights.const_data_ptr<scalar_t>() : NULL, in embedding_backward_cuda_kernel()
328 per_sample_weights.defined() ? per_sample_weights.stride(0) : 0, in embedding_backward_cuda_kernel()
/aosp_15_r20/external/pytorch/benchmarks/operator_benchmark/pt/
H A Dqembedding_bag_lookups_test.py146 self.per_sample_weights = (
169 "per_sample_weights": self.per_sample_weights,
183 per_sample_weights: Optional[torch.Tensor],
193 per_sample_weights=per_sample_weights,
258 self.per_sample_weights = (
281 "per_sample_weights": self.per_sample_weights,
295 per_sample_weights: Optional[torch.Tensor],
305 per_sample_weights=per_sample_weights,
/aosp_15_r20/external/pytorch/test/distributed/_shard/sharded_tensor/ops/
H A Dtest_embedding_bag.py77 per_sample_weights = None
79 per_sample_weights = torch.rand(*input_size).cuda(self.rank)
109 per_sample_weights=per_sample_weights,
116 per_sample_weights=per_sample_weights,
141 per_sample_weights=per_sample_weights,
152 per_sample_weights=per_sample_weights,
/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/functional/
H A Dembedding.h98 const Tensor& per_sample_weights, in embedding_bag() argument
103 auto per_sample_weights_ = per_sample_weights; in embedding_bag()
107 "embedding_bag: If per_sample_weights (", in embedding_bag()
159 "embedding_bag: per_sample_weights was not null. ", in embedding_bag()
160 "per_sample_weights is only supported for mode='kSum' (got mode='", in embedding_bag()
204 options.per_sample_weights(),
/aosp_15_r20/external/pytorch/torch/nn/modules/
H A Dsparse.py272 …For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx…
284 reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the
286 :attr:`per_sample_weights`.
298 … ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights`
431 per_sample_weights: Optional[Tensor] = None,
439 per_sample_weights (Tensor, optional): a tensor of float / double weights, or None
440 … to indicate all weights should be taken to be ``1``. If specified, :attr:`per_sample_weights`
472 per_sample_weights,
/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/options/
H A Dembedding.h131 /// bag. ``"kSum"`` computes the weighted sum, taking `per_sample_weights`
172 /// bag. ``"kSum"`` computes the weighted sum, taking `per_sample_weights`
216 /// bag. ``"kSum"`` computes the weighted sum, taking `per_sample_weights`
224 /// be taken to be 1. If specified, `per_sample_weights` must have exactly the
227 TORCH_ARG(torch::Tensor, per_sample_weights) = Tensor();
/aosp_15_r20/external/pytorch/torch/csrc/jit/runtime/static/
H A Dpasses.cpp452 …l scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool i… in TORCH_LIBRARY_FRAGMENT()
455 …r offsets, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, bool includ… in TORCH_LIBRARY_FRAGMENT()
1306 …graph(%weight, %indices, %offsets, %scale_grad_by_freq, %mode, %sparse, %per_sample_weights, %incl… in RemoveUnnecessaryEmbeddingBagOutputs()
1307 …%weight, %indices, %offsets, %scale_grad_by_freq, %mode, %sparse, %per_sample_weights, %include_la… in RemoveUnnecessaryEmbeddingBagOutputs()
1310 …graph(%weight, %indices, %offsets, %scale_grad_by_freq, %mode, %sparse, %per_sample_weights, %incl… in RemoveUnnecessaryEmbeddingBagOutputs()
1311 …%weight, %indices, %offsets, %scale_grad_by_freq, %mode, %sparse, %per_sample_weights, %include_la… in RemoveUnnecessaryEmbeddingBagOutputs()
1318 …graph(%weight, %indices, %offsets, %scale_grad_by_freq, %mode, %sparse, %per_sample_weights, %incl… in RemoveUnnecessaryEmbeddingBagOutputs()
1319 …%weight, %indices, %offsets, %scale_grad_by_freq, %mode, %sparse, %per_sample_weights, %include_la… in RemoveUnnecessaryEmbeddingBagOutputs()
1322 …graph(%weight, %indices, %offsets, %scale_grad_by_freq, %mode, %sparse, %per_sample_weights, %incl… in RemoveUnnecessaryEmbeddingBagOutputs()
1323 …%weight, %indices, %offsets, %scale_grad_by_freq, %mode, %sparse, %per_sample_weights, %include_la… in RemoveUnnecessaryEmbeddingBagOutputs()
/aosp_15_r20/external/pytorch/torch/ao/nn/quantized/modules/
H A Dembedding_ops.py310 per_sample_weights: Optional[Tensor] = None,
321 per_sample_weights,
333 per_sample_weights,
/aosp_15_r20/external/pytorch/torch/ao/nn/quantized/reference/modules/
H A Dsparse.py129 per_sample_weights: Optional[Tensor] = None,
141 per_sample_weights,
/aosp_15_r20/external/pytorch/torch/
H A D_meta_registrations.py3356 per_sample_weights=None, argument
3384 if per_sample_weights is not None:
3387 lambda: "embedding_bag: per_sample_weights only supported with mode='sum'",
3390 per_sample_weights.dtype == weight.dtype,
3391 …lambda: f"expected weight ({weight.dtype}) and per_sample_weights ({per_sample_weights.dtype}) to …
3394 per_sample_weights.ndim == 1,
3395 lambda: f"expected per_sample_weights to be 1D tensor, got {per_sample_weights.ndim}D",
3398 per_sample_weights.numel() == indices.numel(),
3400 f"expected per_sample_weights.numel() ({per_sample_weights.numel()} "
3432 fast_path_sum = is_fast_path(weight, per_sample_weights, output, padding_idx)
[all …]
/aosp_15_r20/external/pytorch/torch/csrc/inductor/aoti_torch/generated/
H A Dc_shim_cpu.h22 …cale_grad_by_freq, int64_t mode, int32_t sparse, AtenTensorHandle* per_sample_weights, int32_t inc…
23 …ights, int32_t scale_grad_by_freq, int64_t mode, AtenTensorHandle* per_sample_weights, int64_t pad…
24 …cale_grad_by_freq, int64_t mode, int32_t sparse, AtenTensorHandle* per_sample_weights, int32_t inc…
H A Dc_shim_cuda.h25 …cale_grad_by_freq, int64_t mode, int32_t sparse, AtenTensorHandle* per_sample_weights, int32_t inc…
26 …ights, int32_t scale_grad_by_freq, int64_t mode, AtenTensorHandle* per_sample_weights, int64_t pad…
27 …cale_grad_by_freq, int64_t mode, int32_t sparse, AtenTensorHandle* per_sample_weights, int32_t inc…
/aosp_15_r20/external/pytorch/torch/nn/
H A Dfunctional.py2563 per_sample_weights: Optional[Tensor] = None,
2594 per_sample_weights (Tensor, optional): a tensor of float / double weights, or None
2595 … to indicate all weights should be taken to be 1. If specified, :attr:`per_sample_weights`
2622 - :attr:`per_sample_weights` (Tensor, optional). Has the same shape as :attr:`input`.
2646 if has_torch_function_variadic(input, weight, offsets, per_sample_weights):
2649 (input, weight, offsets, per_sample_weights),
2658 per_sample_weights=per_sample_weights,
2673 if per_sample_weights is not None and input.size() != per_sample_weights.size():
2675 f"embedding_bag: If per_sample_weights ({per_sample_weights.shape}) is not None, "
2701 if per_sample_weights is not None:
[all …]
/aosp_15_r20/external/pytorch/test/
H A Dtest_meta.py1598 per_sample_weights=None,
1618 per_sample_weights = None
1623 …weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offse…
1630 scale_grad_by_freq, mode, per_sample_weights, padding_idx
1635 scale_grad_by_freq, mode, per_sample_weights, padding_idx
1646 per_sample_weights = torch.randn(5, requires_grad=True)
1651 …weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offse…
/aosp_15_r20/external/pytorch/aten/src/ATen/native/quantized/
H A Dlibrary.cpp136 …grad_by_freq=False, int mode=0, bool pruned_weights=False, Tensor? per_sample_weights=None, Tensor… in TORCH_LIBRARY()
137 …grad_by_freq=False, int mode=0, bool pruned_weights=False, Tensor? per_sample_weights=None, Tensor… in TORCH_LIBRARY()
138 …grad_by_freq=False, int mode=0, bool pruned_weights=False, Tensor? per_sample_weights=None, Tensor… in TORCH_LIBRARY()
139 …grad_by_freq=False, int mode=0, bool pruned_weights=False, Tensor? per_sample_weights=None, Tensor… in TORCH_LIBRARY()
140 …grad_by_freq=False, int mode=0, bool pruned_weights=False, Tensor? per_sample_weights=None, Tensor… in TORCH_LIBRARY()
/aosp_15_r20/external/pytorch/torch/ao/nn/qat/modules/
H A Dembedding_ops.py180 def forward(self, input, offsets=None, per_sample_weights=None) -> Tensor: argument
190 per_sample_weights,
/aosp_15_r20/external/pytorch/torch/csrc/api/src/nn/modules/
H A Dembedding.cpp138 const Tensor& per_sample_weights) { in forward() argument
148 per_sample_weights, in forward()
/aosp_15_r20/external/pytorch/torch/onnx/
H A Dsymbolic_opset18.py237 per_sample_weights, argument
249 per_sample_weights,

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