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/aosp_15_r20/external/pytorch/torch/_decomp/
H A Ddecompositions.py106 def _unsqueeze_to_dim(x: Tensor, dim: int) -> Tensor:
115 def tanh_backward(out_grad: Tensor, y: Tensor):
122 def sigmoid_backward(out_grad: Tensor, y: Tensor):
129 def softplus_backward(out_grad: Tensor, x: Tensor, beta: float, threshold: float):
138 grad_output: Tensor,
143 self_or_result: Tensor,
168 def fill_tensor(self, value: Tensor):
179 def hardsigmoid(self: Tensor) -> Tensor:
186 def hardsigmoid_backward(grad_output: Tensor, self: Tensor):
197 grad_output: Tensor, self: Tensor, min_val: float, max_val: float
[all …]
H A Ddecompositions_for_jvp.py102 def trace(self: Tensor) -> Tensor:
107 def log_sigmoid_forward(self: Tensor) -> Tuple[Tensor, Tensor]:
118 input: Tensor, rstd: Tensor, inner_dim_indices: List[int], keepdim: bool
133 grad_out: Tensor,
134 input: Tensor,
136 mean: Tensor,
137 rstd: Tensor,
138 weight: Optional[Tensor],
139 bias: Optional[Tensor],
217 grad_out: Tensor,
[all …]
/aosp_15_r20/external/pytorch/test/inductor/
H A Dtest_b2b_gemm.py21 def f(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
25 def f_32(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
55 def f(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
59 def f_32(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
81 def f(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
84 def f_32(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
106 def f(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
109 def f_32(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
130 def f(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
151 def f(m1: torch.Tensor, m2: torch.Tensor, m3: torch.Tensor) -> torch.Tensor:
[all …]
H A Dtest_fused_attention.py111 query: torch.Tensor, key: torch.Tensor, value: torch.Tensor
139 query: torch.Tensor, key: torch.Tensor, value: torch.Tensor
250 query: torch.Tensor, key: torch.Tensor, value: torch.Tensor
271 query: torch.Tensor, key: torch.Tensor, value: torch.Tensor
286 query: torch.Tensor, key: torch.Tensor, value: torch.Tensor, training: bool
303 query: torch.Tensor,
304 key: torch.Tensor,
305 value: torch.Tensor,
581 query: torch.Tensor, key: torch.Tensor, value: torch.Tensor
598 query: torch.Tensor,
[all …]
/aosp_15_r20/external/pytorch/torch/nn/
H A Dfunctional.py437 input: Tensor,
442 _random_samples: Optional[Tensor] = None,
514 input: Tensor,
519 _random_samples: Optional[Tensor] = None,
549 input: Tensor,
554 _random_samples: Optional[Tensor] = None,
630 input: Tensor,
635 _random_samples: Optional[Tensor] = None,
665 input: Tensor,
718 input: Tensor,
[all …]
/aosp_15_r20/external/pytorch/torch/_inductor/
H A Ddecomposition.py126 def assert_async_msg_decomp(tensor: torch.Tensor, msg: str) -> None:
132 def functional_assert_async_msg_decomp(tensor: torch.Tensor, msg: str) -> None:
149 x: torch.Tensor,
191 grad_output: torch.Tensor,
192 input: torch.Tensor,
193 weight: torch.Tensor,
223 def round_dec(x: torch.Tensor, decimals: int = 0) -> torch.Tensor:
231 self: torch.Tensor,
232 batch2: torch.Tensor,
254 self: torch.Tensor,
[all …]
/aosp_15_r20/external/pytorch/torch/ao/quantization/fx/
H A D_decomposed.py52 input: torch.Tensor,
89 input: torch.Tensor,
114 input: torch.Tensor,
115 scale: torch.Tensor,
116 zero_point: torch.Tensor,
139 input: torch.Tensor,
140 scale: torch.Tensor,
141 zero_point: torch.Tensor,
171 input: torch.Tensor,
172 scale: torch.Tensor,
[all …]
/aosp_15_r20/external/executorch/backends/cadence/aot/
H A Dops_registrations.py264 input: torch.Tensor,
276 input: torch.Tensor,
288 src: torch.Tensor,
289 weight: torch.Tensor,
290 bias: torch.Tensor,
292 weight_zero_point: torch.Tensor,
293 out_multiplier: torch.Tensor,
294 out_shift: torch.Tensor,
296 offset: Optional[torch.Tensor],
310 src: torch.Tensor,
[all …]
/aosp_15_r20/external/pytorch/torch/distributed/_symmetric_memory/
H A D__init__.py137 shard: torch.Tensor,
138 shard_consumer: Callable[[torch.Tensor, int], None],
139 ag_out: torch.Tensor,
195 chunk_producer: Callable[[int, torch.Tensor], None],
196 output: torch.Tensor,
289 A_shard: torch.Tensor,
290 Bs: List[torch.Tensor],
319 def unflatten(t: torch.Tensor) -> torch.Tensor:
333 def shard_consumer(shard: torch.Tensor, rank: int) -> None:
348 A_shard: torch.Tensor,
[all …]
/aosp_15_r20/external/pytorch/torch/_higher_order_ops/
H A Dflex_attention.py49 def _permute_strides(out: torch.Tensor, query_strides: Tuple[int, ...]) -> torch.Tensor:
94 query: torch.Tensor,
95 key: torch.Tensor,
96 value: torch.Tensor,
131 query: torch.Tensor,
132 key: torch.Tensor,
133 value: torch.Tensor,
134 out: torch.Tensor,
135 logsumexp: torch.Tensor,
136 grad_out: torch.Tensor,
[all …]
/aosp_15_r20/external/pytorch/torch/masked/
H A D_ops.py400 def _reduction_identity(op_name: str, input: Tensor, *args):
485 def _sparse_coo_flatten_indices(indices: Tensor, shape: tuple):
494 def _any(input: Tensor, dim: tuple, keepdim: bool):
503 def _sparse_coo_where(mask: Tensor, input: Tensor, fill_value: Tensor) -> Tensor:
617 mask_input: Tensor,
737 mask_input: Tensor,
821 def _sparse_csr_where(mask: Tensor, input: Tensor, fill_value: Tensor) -> Tensor:
829 def _where(mask: Tensor, input: Tensor, fill_value: Tensor) -> Tensor:
865 def _input_mask(input: Union[Tensor, MaskedTensor], *args, **kwargs) -> Tensor:
950 def _output_mask(op, input: Tensor, *args, **kwargs) -> Tensor:
[all …]
/aosp_15_r20/external/pytorch/torch/distributed/tensor/experimental/
H A D_attention.py69 def _maybe_wait(tensor: torch.Tensor) -> torch.Tensor:
89 def _merge_one(self, block_out: torch.Tensor, block_lse: torch.Tensor) -> None:
103 def step(self, out: torch.Tensor, lse: torch.Tensor) -> None:
122 query: torch.Tensor,
123 key: torch.Tensor,
124 value: torch.Tensor,
148 query: torch.Tensor,
149 key: torch.Tensor,
150 value: torch.Tensor,
151 attn_bias: Optional[torch.Tensor] = None,
[all …]
/aosp_15_r20/external/pytorch/torch/nn/modules/
H A Dtransformer.py47 def _get_seq_len(src: Tensor, batch_first: bool) -> Optional[int]:
107 activation: Union[str, Callable[[Tensor], Tensor]] = F.relu, argument
174 src: Tensor,
175 tgt: Tensor,
176 src_mask: Optional[Tensor] = None,
177 tgt_mask: Optional[Tensor] = None,
178 memory_mask: Optional[Tensor] = None,
179 src_key_padding_mask: Optional[Tensor] = None,
180 tgt_key_padding_mask: Optional[Tensor] = None,
181 memory_key_padding_mask: Optional[Tensor] = None,
[all …]
H A Dloss.py52 weight: Optional[Tensor] = None,
127 def forward(self, input: Tensor, target: Tensor) -> Tensor:
241 weight: Optional[Tensor] = None,
250 def forward(self, input: Tensor, target: Tensor) -> Tensor:
269 weight: Optional[Tensor] = None,
353 def forward(self, log_input: Tensor, target: Tensor) -> Tensor:
441 def forward(self, input: Tensor, target: Tensor, var: Tensor) -> Tensor:
540 def forward(self, input: Tensor, target: Tensor) -> Tensor:
607 def forward(self, input: Tensor, target: Tensor) -> Tensor:
689 weight: Optional[Tensor] = None,
[all …]
/aosp_15_r20/external/pytorch/test/jit/
H A Dtest_module_interface.py26 def one(self, inp1: Tensor, inp2: Tensor) -> Tensor:
29 def two(self, input: Tensor) -> Tensor:
32 def forward(self, input: Tensor) -> Tensor:
37 def one(self, inp1: Tensor, inp2: Tensor) -> Tensor:
40 def forward(self, input: Tensor) -> Tensor:
48 def one(self, inp1: Tensor, inp2: Tensor) -> Tensor:
58 def forward(self, input: Tensor) -> Tensor:
69 def one(self, x: Tensor, y: Tensor) -> Tensor:
72 def two(self, x: Tensor) -> Tensor:
75 def forward(self, x: Tensor) -> Tensor:
[all …]
H A Dtest_await.py34 def fn(x: Tensor):
49 def fn(x: Tensor):
65 def __init__(self, a: Tensor, b: Tensor):
72 def fn(x: Tensor):
89 def __init__(self, a: Tensor, b: Tensor):
101 def fn(x: Tensor):
120 def __init__(self, a: Tensor, b: Tensor):
131 def fn(x: Tensor):
149 def __init__(self, a: Tensor, b: Tensor):
163 def fn(x: Tensor):
[all …]
/aosp_15_r20/external/pytorch/torch/optim/
H A Dadamw.py36 lr: Union[float, Tensor] = 1e-3, argument
318 params: List[Tensor],
319 grads: List[Tensor],
320 exp_avgs: List[Tensor],
321 exp_avg_sqs: List[Tensor],
322 max_exp_avg_sqs: List[Tensor],
323 state_steps: List[Tensor],
324 grad_scale: Optional[Tensor],
325 found_inf: Optional[Tensor],
330 lr: Union[Tensor, float],
[all …]
H A Dadam.py36 lr: Union[float, Tensor] = 1e-3, argument
321 params: List[Tensor],
322 grads: List[Tensor],
323 exp_avgs: List[Tensor],
324 exp_avg_sqs: List[Tensor],
325 max_exp_avg_sqs: List[Tensor],
326 state_steps: List[Tensor],
327 grad_scale: Optional[Tensor],
328 found_inf: Optional[Tensor],
440 params: List[Tensor],
[all …]
/aosp_15_r20/external/pytorch/torch/_inductor/fx_passes/
H A Dpad_mm.py63 def get_alignment_size(x: Tensor) -> int:
76 def check_device(a: Tensor, b: Tensor) -> bool:
80 def check_dtype(a: Tensor, b: Tensor) -> bool:
85 mat1: Tensor, mat2: Tensor, input: Optional[Tensor] = None
89 def valid_shape_and_stride(t: Optional[Tensor]) -> bool:
131 def pad_dim(x: Tensor, padded_length: int, dim: int) -> Tensor:
139 input: Tensor, mat1: Tensor, mat2: Tensor, beta: float, alpha: float
152 input: Optional[Tensor],
153 mat1: Tensor,
154 mat2: Tensor,
[all …]
/aosp_15_r20/external/pytorch/torch/ao/nn/quantized/dynamic/modules/
H A Drnn.py29 def _apply_permutation(tensor: Tensor, permutation: Tensor, dim: int = 1) -> Tensor:
37 def apply_permutation(tensor: Tensor, permutation: Tensor, dim: int = 1) -> Tensor:
239 def check_input(self, input: Tensor, batch_sizes: Optional[Tensor]) -> None:
251 self, input: Tensor, batch_sizes: Optional[Tensor]
267 hx: Tensor,
275 self, input: Tensor, hidden: Tensor, batch_sizes: Optional[Tensor]
283 def permute_hidden(self, hx: Tensor, permutation: Optional[Tensor]) -> Tensor:
536 input: Tensor,
537 hx: Optional[Tuple[Tensor, Tensor]], argument
538 batch_sizes: Optional[Tensor],
[all …]
/aosp_15_r20/external/pytorch/torch/
H A D_meta_registrations.py420 input: Tensor,
421 weight: Tensor,
422 _meta: Tensor,
423 bias: Optional[Tensor] = None,
454 mat1: Tensor,
455 mat1_meta: Tensor,
456 mat2: Tensor,
479 input: Tensor,
480 mat1: Tensor,
481 mat1_meta: Tensor,
[all …]
/aosp_15_r20/external/pytorch/torch/ao/nn/quantized/modules/
H A Dfunctional_modules.py51 def add(self, x: Tensor, y: Tensor) -> Tensor:
58 def add_scalar(self, x: Tensor, y: float) -> Tensor:
66 def mul(self, x: Tensor, y: Tensor) -> Tensor:
73 def mul_scalar(self, x: Tensor, y: float) -> Tensor:
81 def cat(self, x: List[Tensor], dim: int = 0) -> Tensor:
88 def add_relu(self, x: Tensor, y: Tensor) -> Tensor:
96 def matmul(self, x: Tensor, y: Tensor) -> Tensor:
123 def add(self, x: Tensor, y: Tensor) -> Tensor:
129 def add_scalar(self, x: Tensor, y: float) -> Tensor:
135 def mul(self, x: Tensor, y: Tensor) -> Tensor:
[all …]
/aosp_15_r20/external/pytorch/torch/nn/attention/
H A Dflex_attention.py123 score: Tensor,
124 batch: Tensor,
125 head: Tensor,
126 token_q: Tensor,
127 token_kv: Tensor,
133 batch: Tensor,
134 head: Tensor,
135 token_q: Tensor,
136 token_kv: Tensor,
146 def _ordered_to_dense(num_blocks_in_row: Tensor, col_indices: Tensor):
[all …]
/aosp_15_r20/external/pytorch/torch/ao/quantization/pt2e/
H A Dqat_utils.py88 x: torch.Tensor,
89 conv_weight: torch.Tensor,
90 conv_bias: torch.Tensor,
91 bn_weight: torch.Tensor,
92 bn_bias: torch.Tensor,
93 bn_running_mean: torch.Tensor,
94 bn_running_var: torch.Tensor,
108 x: torch.Tensor,
109 conv_weight: torch.Tensor,
110 conv_bias: torch.Tensor,
[all …]
/aosp_15_r20/external/executorch/examples/qualcomm/oss_scripts/llama2/model/
H A Dstatic_llama.py19 def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
34 x: torch.Tensor, freqs_cos: torch.Tensor, freqs_sin: torch.Tensor
102 hidden_states: torch.Tensor,
103 freqs_cos: torch.Tensor,
104 freqs_sin: torch.Tensor,
105 atten_mask: torch.Tensor,
106 k_caches: List[torch.Tensor],
107 v_caches: List[torch.Tensor],
138 hidden_states: torch.Tensor,
139 freqs_cos: torch.Tensor,
[all …]

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