| /external/pytorch/torch/csrc/autograd/ |
| D | FunctionsManual.h | 34 TORCH_API Tensor toNonOptFwGrad(const std::optional<Tensor>& t);
35 TORCH_API Tensor toNonOptPrimal(const std::optional<Tensor>& t);
36 TORCH_API Tensor toNonOptTensor(const std::optional<Tensor>& t);
38 TORCH_API inline std::optional<Tensor> wrap_opt_if( in wrap_opt_if()
39 const Tensor& t, in wrap_opt_if()
41 using OptTensor = std::optional<Tensor>; in wrap_opt_if()
45 TORCH_API Tensor
46 apply_loss_reduction(const Tensor& unreduced, int64_t reduction);
51 const at::Tensor& t);
55 at::ArrayRef<at::Tensor> t);
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| /external/pytorch/torch/csrc/api/include/torch/ |
| D | special.h | 17 inline Tensor gammaln(const Tensor& self) { in gammaln()
21 inline Tensor& gammaln_out(Tensor& result, const Tensor& self) { in gammaln_out()
34 inline Tensor gammainc(const Tensor& self, const Tensor& other) { in gammainc()
38 inline Tensor& gammainc_out( in gammainc_out()
39 Tensor& result, in gammainc_out()
40 const Tensor& self, in gammainc_out()
41 const Tensor& other) { in gammainc_out()
54 inline Tensor gammaincc(const Tensor& self, const Tensor& other) { in gammaincc()
58 inline Tensor& gammaincc_out( in gammaincc_out()
59 Tensor& result, in gammaincc_out()
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| D | linalg.h | 11 inline Tensor cholesky(const Tensor& self) { in cholesky()
15 inline Tensor cholesky_out(Tensor& result, const Tensor& self) { in cholesky_out()
19 inline Tensor det(const Tensor& self) { in det()
23 inline std::tuple<Tensor, Tensor> slogdet(const Tensor& input) { in slogdet()
27 inline std::tuple<Tensor&, Tensor&> slogdet_out( in slogdet_out()
28 Tensor& sign, in slogdet_out()
29 Tensor& logabsdet, in slogdet_out()
30 const Tensor& input) { in slogdet_out()
34 inline std::tuple<Tensor, Tensor> eig(const Tensor& self) { in eig()
38 inline std::tuple<Tensor&, Tensor&> eig_out( in eig_out()
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| /external/pytorch/docs/source/ |
| D | tensors.rst | 5 torch.Tensor
8 A :class:`torch.Tensor` is a multi-dimensional matrix containing elements of
85 :class:`torch.Tensor` constructor is an alias for the default tensor type
105 :func:`torch.tensor` always copies :attr:`data`. If you have a Tensor
107 :meth:`~torch.Tensor.requires_grad_` or
108 :meth:`~torch.Tensor.detach` to avoid a copy.
142 Use :meth:`torch.Tensor.item` to get a Python number from a tensor containing a
181 :class:`torch.layout` attributes of a :class:`torch.Tensor`, see
192 :meth:`~torch.Tensor.to` method on the tensor.
195 Current implementation of :class:`torch.Tensor` introduces memory overhead,
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| /external/pytorch/aten/src/ATen/native/ |
| D | BinaryOps.cpp | 151 TORCH_META_FUNC2(add, Tensor) ( in TORCH_META_FUNC2() argument
152 const Tensor& self, const Tensor& other, const Scalar& alpha in TORCH_META_FUNC2()
158 TORCH_META_FUNC2(sub, Tensor) ( in TORCH_META_FUNC2() argument
159 const Tensor& self, const Tensor& other, const Scalar& alpha in TORCH_META_FUNC2()
166 TORCH_META_FUNC2(mul, Tensor) ( in TORCH_META_FUNC2() argument
167 const Tensor& self, const Tensor& other in TORCH_META_FUNC2()
172 TORCH_META_FUNC2(div, Tensor) (const Tensor& self, const Tensor& other) { in TORCH_META_FUNC2() argument
176 TORCH_META_FUNC2(div, Tensor_mode) (const Tensor& self, const Tensor& other, std::optional<c10::str… in TORCH_META_FUNC2()
191 TORCH_META_FUNC(special_xlog1py) (const Tensor& self, const Tensor& other) { in TORCH_META_FUNC()
195 TORCH_META_FUNC(special_zeta) (const Tensor& self, const Tensor& other) { in TORCH_META_FUNC()
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| D | UnaryOps.cpp | 179 TORCH_META_FUNC(func) (const Tensor& self) { \
233 TORCH_META_FUNC(polygamma)(int64_t n, const Tensor& self) { in CREATE_UNARY_FLOAT_META_FUNC()
240 TORCH_META_FUNC(func) (const Tensor& self) { \
248 TORCH_META_FUNC2(round, decimals)(const Tensor& self, int64_t decimals){ in CREATE_UNARY_META_FUNC()
252 TORCH_META_FUNC(neg)(const Tensor& self) { in TORCH_META_FUNC()
259 TORCH_META_FUNC(trunc) (const Tensor& self) { in TORCH_META_FUNC()
266 TORCH_META_FUNC(floor) (const Tensor& self) { in TORCH_META_FUNC()
273 TORCH_META_FUNC(sign) (const Tensor& self) { in TORCH_META_FUNC()
279 TORCH_META_FUNC(signbit) (const Tensor& self) { in TORCH_META_FUNC()
286 TORCH_META_FUNC(ceil) (const Tensor& self) { in TORCH_META_FUNC()
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| D | Activation.cpp | 86 TORCH_META_FUNC(threshold)(const Tensor& self, const Scalar& threshold, const Scalar& value) { in TORCH_META_FUNC()
87 const Tensor& result = maybe_get_output(); in TORCH_META_FUNC()
100 TORCH_META_FUNC(threshold_backward)(const Tensor& grad, const Tensor& self, const Scalar& threshold… in TORCH_META_FUNC()
101 const Tensor& gradInput = maybe_get_output(); in TORCH_META_FUNC()
114 const Tensor& self, const Scalar& alpha, const Scalar& scale, const Scalar& input_scale in TORCH_META_FUNC()
120 const Tensor& grad_output, in TORCH_META_FUNC()
125 const Tensor& self_or_result in TORCH_META_FUNC()
136 TORCH_META_FUNC(silu) (const Tensor& self) { in TORCH_META_FUNC()
141 const Tensor& grad_output, const Tensor& input in TORCH_META_FUNC()
146 TORCH_META_FUNC(mish) (const Tensor& self) { in TORCH_META_FUNC()
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| D | Normalization.cpp | 69 TORCH_META_FUNC(renorm)(const Tensor& self, const Scalar& p, int64_t dim, const Scalar& maxnorm) { in TORCH_META_FUNC()
95 static inline Tensor repeat_if_defined(const Tensor& t, const SymInt& repeat) { in repeat_if_defined()
121 static inline bool is_contiguous(const Tensor& t) { in is_contiguous()
128 static inline MemoryFormat suggest_memory_format_contig(const Tensor& t) { in suggest_memory_format_contig()
135 std::tuple<Tensor,Tensor,Tensor> batch_norm_cpu_transform_input_template( in batch_norm_cpu_transform_input_template()
136 const Tensor& input, const Tensor& weight, const Tensor& bias, in batch_norm_cpu_transform_input_template()
137 const Tensor& save_mean /* optional */, const Tensor& save_invstd /* optional */, in batch_norm_cpu_transform_input_template()
138 const Tensor& running_mean /* optional */, const Tensor& running_var /* optional */, in batch_norm_cpu_transform_input_template()
139 bool train, double eps, Tensor& output) { in batch_norm_cpu_transform_input_template()
161 auto as_nd = [&](const Tensor& t) { in batch_norm_cpu_transform_input_template()
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| /external/executorch/exir/dialects/edge/op/ |
| D | sample_input.py | 18 InArg(ArgType.Tensor),
23 Return(ArgType.Tensor),
28 InArg(ArgType.Tensor, size=[2, 3, 4, 5]),
31 InArg(ArgType.Tensor, size=[3]),
32 InArg(ArgType.Tensor, size=[3]),
37 Return(ArgType.Tensor, argname="__ret0", size=[2, 3, 4, 5]),
38 Return(ArgType.Tensor, argname="__ret1", size=[0]),
39 Return(ArgType.Tensor, argname="__ret2", size=[0]),
44 InArg(ArgType.Tensor),
49 Return(ArgType.Tensor),
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| /external/pytorch/aten/src/ATen/ |
| D | ExpandUtils.h | 77 std::initializer_list<std::reference_wrapper<const Tensor>> tensors, in check_defined()
99 inline c10::MaybeOwned<Tensor> expand_inplace( in expand_inplace()
100 const Tensor& tensor, in expand_inplace()
101 const Tensor& to_expand) { in expand_inplace()
103 return c10::MaybeOwned<Tensor>::borrowed(to_expand); in expand_inplace()
105 return c10::MaybeOwned<Tensor>::owned( in expand_inplace()
109 inline c10::MaybeOwned<Tensor> expand_inplace(
110 const Tensor& tensor,
111 Tensor&& to_expand) = delete;
113 inline c10::MaybeOwned<Tensor> expand_inplace( in expand_inplace()
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| D | FunctionalInverses.cpp | 15 static Tensor permute_inverse(const Tensor& self, IntArrayRef dims, InverseReturnMode inverse_retur… in permute_inverse()
29 static Tensor unsqueeze_copy_to(const Tensor & self, c10::SymIntArrayRef sizes, InverseReturnMode i… in unsqueeze_copy_to()
48 static Tensor unsqueeze_copy_to(const Tensor & self, IntArrayRef dim, c10::SymIntArrayRef sizes, In… in unsqueeze_copy_to()
51 Tensor result = self; in unsqueeze_copy_to()
106 Tensor FunctionalInverses::_fw_primal_inverse(const at::Tensor& base, const at::Tensor& mutated_vie… in _fw_primal_inverse()
108 return Tensor(); in _fw_primal_inverse()
111 Tensor FunctionalInverses::_make_dual_inverse(const at::Tensor& base, const at::Tensor& mutated_vie… in _make_dual_inverse()
113 return Tensor(); in _make_dual_inverse()
116 Tensor FunctionalInverses::view_as_real_inverse(const Tensor& base, const Tensor& mutated_view, Inv… in view_as_real_inverse()
124 Tensor FunctionalInverses::view_as_complex_inverse(const Tensor& base, const Tensor& mutated_view, … in view_as_complex_inverse()
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| /external/tensorflow/tensorflow/java/src/main/java/org/tensorflow/ |
| D | Tensors.java | 29 public static Tensor<String> create(String data) { in create()
30 return Tensor.create(data.getBytes(UTF_8), String.class); in create()
39 public static Tensor<String> create(String data, java.nio.charset.Charset charset) { in create()
40 return Tensor.create(data.getBytes(charset), String.class); in create()
48 public static Tensor<Float> create(float data) { in create()
49 return Tensor.create(data, Float.class); in create()
58 public static Tensor<Float> create(float[] data) { in create()
59 return Tensor.create(data, Float.class); in create()
68 public static Tensor<Float> create(float[][] data) { in create()
69 return Tensor.create(data, Float.class); in create()
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| /external/pytorch/torch/nn/ |
| D | functional.pyi.in | 17 from torch import Tensor
53 input: Tensor,
58 _random_samples: Optional[Tensor] = ...,
59 ) -> Tuple[Tensor, Tensor]: ...
61 input: Tensor,
66 _random_samples: Optional[Tensor] = ...,
67 ) -> Tuple[Tensor, Tensor]: ...
69 input: Tensor,
76 ) -> Tuple[Tensor, Tensor]: ...
78 input: Tensor,
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| /external/pytorch/aten/src/ATen/native/transformers/cuda/flash_attn/ |
| D | flash_api.h | 10 std::tuple<at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::…
11 mha_fwd(const at::Tensor &q, // batch_size x seqlen_q x num_heads x head_size
12 const at::Tensor &k, // batch_size x seqlen_k x num_heads_k x head_size
13 const at::Tensor &v, // batch_size x seqlen_k x num_heads_k x head_size
14 … std::optional<at::Tensor> &out_, // batch_size x seqlen_q x num_heads x head_size
15 std::optional<at::Tensor> &alibi_slopes_, // num_heads or batch_size x num_heads
24 std::tuple<at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::…
25 mha_varlen_fwd(const at::Tensor &q, // total_q x num_heads x head_size, total_q := \sum_{i=0}^{b} …
26 … const at::Tensor &k, // total_k x num_heads_k x head_size, total_k := \sum_{i=0}^{b} s_i
27 … const at::Tensor &v, // total_k x num_heads_k x head_size, total_k := \sum_{i=0}^{b} s_i
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| /external/pytorch/aten/src/ATen/native/mkldnn/ |
| D | Normalization.cpp | 24 std::tuple<Tensor, Tensor, Tensor> mkldnn_batch_norm( in mkldnn_batch_norm()
25 …Tensor& self, const std::optional<Tensor>& weight_opt, const std::optional<Tensor>& bias_opt, cons… in mkldnn_batch_norm()
32 std::tuple<Tensor, Tensor, Tensor> mkldnn_batch_norm_backward( in mkldnn_batch_norm_backward()
33 const Tensor& grad_output, in mkldnn_batch_norm_backward()
34 …Tensor& input, const std::optional<Tensor>& weight_opt, const std::optional<Tensor>& running_mean_… in mkldnn_batch_norm_backward()
41 std::tuple<Tensor, Tensor, Tensor> mkldnn_layer_norm_last_index_weight_bias_f32( in mkldnn_layer_norm_last_index_weight_bias_f32()
42 const Tensor& input, in mkldnn_layer_norm_last_index_weight_bias_f32()
43 IntArrayRef normalized_shape, const Tensor& weight, const Tensor& bias, in mkldnn_layer_norm_last_index_weight_bias_f32()
48 std::tuple<Tensor, Tensor, Tensor> _mkldnn_batch_norm_legit( in _mkldnn_batch_norm_legit()
49 …const Tensor& input, const std::optional<Tensor>& weight_opt, const std::optional<Tensor>& bias_op… in _mkldnn_batch_norm_legit()
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| /external/pytorch/aten/src/ATen/native/cuda/linalg/ |
| D | BatchLinearAlgebraLib.h | 42 void geqrf_batched_cublas(const Tensor& input, const Tensor& tau);
43 void triangular_solve_cublas(const Tensor& A, const Tensor& B, bool left, bool upper, TransposeType…
44 void triangular_solve_batched_cublas(const Tensor& A, const Tensor& B, bool left, bool upper, Trans…
45 void gels_batched_cublas(const Tensor& a, Tensor& b, Tensor& infos);
47 const Tensor& LD,
48 const Tensor& pivots,
49 const Tensor& info,
53 const Tensor& LD,
54 const Tensor& pivots,
55 const Tensor& B,
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| /external/pytorch/aten/src/ATen/native/quantized/ |
| D | AffineQuantizer.h | 11 Tensor& quantize_tensor_per_tensor_affine(
12 const Tensor& rtensor,
13 Tensor& qtensor,
16 Tensor& quantize_tensor_per_channel_affine(
17 const Tensor& rtensor,
18 Tensor& qtensor,
19 const Tensor& scales,
20 Tensor zero_points,
23 Tensor& quantize_tensor_per_channel_float_qparams(
24 const Tensor& rtensor,
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| /external/pytorch/functorch/dim/ |
| D | op_properties.py | 62 *(getattr(torch.Tensor, m) for m in pointwise_methods),
65 torch.Tensor.abs,
67 torch.Tensor.acos,
69 torch.Tensor.acosh,
71 torch.Tensor.add,
73 torch.Tensor.addcdiv,
75 torch.Tensor.addcmul,
77 torch.Tensor.addr,
79 torch.Tensor.angle,
81 torch.Tensor.asin,
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| /external/pytorch/torch/csrc/api/include/torch/nn/functional/ |
| D | loss.h | 13 inline Tensor l1_loss( in l1_loss()
14 const Tensor& input, in l1_loss()
15 const Tensor& target, in l1_loss()
34 inline Tensor l1_loss(
35 const Tensor& input,
36 const Tensor& target,
45 inline Tensor kl_div(
46 const Tensor& input,
47 const Tensor& target,
92 inline Tensor kl_div(
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| /external/executorch/kernels/test/ |
| D | op_native_batch_norm_test.cpp | 22 ::std::tuple<exec_aten::Tensor&, exec_aten::Tensor&, exec_aten::Tensor&>
24 const exec_aten::Tensor& input, in op_native_batch_norm_legit_no_training_out()
25 const exec_aten::optional<exec_aten::Tensor>& weight, in op_native_batch_norm_legit_no_training_out()
26 const exec_aten::optional<exec_aten::Tensor>& bias, in op_native_batch_norm_legit_no_training_out()
27 const exec_aten::Tensor& running_mean, in op_native_batch_norm_legit_no_training_out()
28 const exec_aten::Tensor& running_var, in op_native_batch_norm_legit_no_training_out()
31 exec_aten::Tensor& out0, in op_native_batch_norm_legit_no_training_out()
32 exec_aten::Tensor& out1, in op_native_batch_norm_legit_no_training_out()
33 exec_aten::Tensor& out2) { in op_native_batch_norm_legit_no_training_out()
51 ::std::tuple<exec_aten::Tensor&, exec_aten::Tensor&, exec_aten::Tensor&>
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| D | op_index_test.cpp | 24 using exec_aten::Tensor;
27 using OptTensorArrayRef = ArrayRef<optional<Tensor>>;
31 Tensor& op_index_tensor_out( in op_index_tensor_out()
32 const Tensor& input, in op_index_tensor_out()
34 Tensor& out) { in op_index_tensor_out()
36 c10::List<std::optional<at::Tensor>> indices_list(indices); in op_index_tensor_out()
55 Tensor x = tf.make( in test_dtype()
75 optional<Tensor> indices[] = { in test_dtype()
76 optional<Tensor>(tfl.make({2}, {0, 1})), in test_dtype()
77 optional<Tensor>(tfl.make({2}, {1, 0})), in test_dtype()
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| D | op_index_put_test.cpp | 23 using exec_aten::Tensor;
26 using OptTensorArrayRef = ArrayRef<optional<Tensor>>;
30 Tensor& op_index_put_out( in op_index_put_out()
31 const Tensor& input, in op_index_put_out()
33 const Tensor& values, in op_index_put_out()
35 Tensor& out) { in op_index_put_out()
37 c10::List<std::optional<at::Tensor>> indices_list(indices); in op_index_put_out()
55 Tensor x = tf.make( in test_dtype()
75 optional<Tensor> indices[] = { in test_dtype()
76 optional<Tensor>(tfl.make({1, 3}, {0, 1, 2})), in test_dtype()
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| /external/pytorch/torch/csrc/api/include/torch/nn/modules/ |
| D | rnn.h | 54 std::vector<Tensor> all_weights() const;
66 void check_input(const Tensor& input, const Tensor& batch_sizes) const;
69 const Tensor& input,
70 const Tensor& batch_sizes) const;
73 const Tensor& hx,
77 void check_forward_args(Tensor input, Tensor hidden, Tensor batch_sizes)
80 Tensor permute_hidden(Tensor hx, const Tensor& permutation) const;
87 std::vector<Tensor> flat_weights_;
111 std::tuple<Tensor, Tensor> forward(const Tensor& input, Tensor hx = {});
114 FORWARD_HAS_DEFAULT_ARGS({1, AnyValue(Tensor())})
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| /external/pytorch/aten/src/ATen/native/transformers/ |
| D | attention.h | 11 using fused_sdp_choice_fn = int64_t (*)(const Tensor& query_, const Tensor& key, const Tensor& valu…
12 …const std::optional<Tensor>& attn_mask_, double dropout_p, bool is_causal, std::optional<double> s…
16 TORCH_API Tensor bmm_nt(const Tensor& a, const Tensor& b);
17 TORCH_API Tensor masked_softmax(
18 Tensor& attn_scores,
19 std::optional<Tensor> attn_mask,
20 const Tensor& query,
35 TORCH_API Tensor transform0213_gemm_nt_bias(
36 const Tensor& a,
37 const Tensor& b,
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| /external/pytorch/aten/src/ATen/native/cuda/ |
| D | Normalization.cu | 46 ScalarType first_type(const Tensor& arg, const Args&... parameters) { in first_type()
52 bool is_mixed_type(const Tensor& input, const Args&... parameters) { in is_mixed_type()
58 inline bool batch_norm_use_channels_last_kernels(const at::Tensor& self) { in batch_norm_use_channels_last_kernels()
72 inline Impl batch_norm_choose_impl(const Tensor& self) { in batch_norm_choose_impl()
88 inline Impl batch_norm_choose_impl(const Tensor& in1, const Tensor& in2) { in batch_norm_choose_impl()
98 const Tensor& out, const Tensor& self, const std::optional<Tensor>& weight_opt, in batch_norm_elementwise()
99 const std::optional<Tensor>& bias_opt, const Tensor& mean_, const Tensor& invstd_) { in batch_norm_elementwise()
102 c10::MaybeOwned<Tensor> weight = at::borrow_from_optional_tensor(weight_opt); in batch_norm_elementwise()
103 c10::MaybeOwned<Tensor> bias = at::borrow_from_optional_tensor(bias_opt); in batch_norm_elementwise()
142 auto as_nd = [&](const Tensor& t) { in batch_norm_elementwise()
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