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/external/executorch/backends/vulkan/runtime/graph/ops/impl/
DRepeatInterleave.cpp49 std::string kernel_name = "repeat_interleave"; in add_repeat_interleave_node()
77 void repeat_interleave(ComputeGraph& graph, const std::vector<ValueRef>& args) { in repeat_interleave() function
92 VK_REGISTER_OP(aten.repeat_interleave.self_int, repeat_interleave);
/external/libopus/dnn/torch/osce/utils/layers/
Dsilk_upsampler.py131 weight_even = torch.repeat_interleave(self.hq_2x_up_even, num_channels, 0)
132 weight_odd = torch.repeat_interleave(self.hq_2x_up_odd , num_channels, 0)
146 weight_01_24 = torch.repeat_interleave(self.frac_01_24, num_channels, 0)
147 weight_17_24 = torch.repeat_interleave(self.frac_17_24, num_channels, 0)
148 weight_09_24 = torch.repeat_interleave(self.frac_09_24, num_channels, 0)
Dpitch_auto_correlator.py63 p_up = torch.repeat_interleave(periods, self.frame_size, 1)
70 x_ext = torch.repeat_interleave(x_pad.unsqueeze(-1), 2 * self.radius + 1, -1)
Dlimited_adaptive_comb1d.py184 idx = torch.repeat_interleave(idx, batch_size, 0)
185 idx = torch.repeat_interleave(idx, self.in_channels, 1)
/external/pytorch/aten/src/ATen/native/
DNegateFallback.cpp31 m.impl("repeat_interleave.Tensor", torch::CppFunction::makeFallthrough()); in TORCH_LIBRARY_IMPL()
32 m.impl("repeat_interleave.self_Tensor", torch::CppFunction::makeFallthrough()); in TORCH_LIBRARY_IMPL()
33 m.impl("repeat_interleave.self_int", torch::CppFunction::makeFallthrough()); in TORCH_LIBRARY_IMPL()
DRepeat.cpp13 #include <ATen/ops/repeat_interleave.h>
119 … TORCH_CHECK(*output_size == calculated_size, "repeat_interleave: Invalid output_size, expected ", in repeat_interleave_symint()
DRepeat.h22 repeats.dim() == 1, "repeat_interleave only accept 1D vector as repeat"); in repeat_interleave_common()
/external/executorch/backends/vulkan/runtime/graph/ops/glsl/
Drepeat_interleave.yaml1 repeat_interleave:
10 - NAME: repeat_interleave
/external/pytorch/aten/src/ATen/
DConjugateFallback.cpp32 m.impl("repeat_interleave.Tensor", torch::CppFunction::makeFallthrough()); in TORCH_LIBRARY_IMPL()
33 m.impl("repeat_interleave.self_Tensor", torch::CppFunction::makeFallthrough()); in TORCH_LIBRARY_IMPL()
34 m.impl("repeat_interleave.self_int", torch::CppFunction::makeFallthrough()); in TORCH_LIBRARY_IMPL()
/external/pytorch/aten/src/ATen/native/mps/operations/
DRepeat.mm89 kernel void repeat_interleave(constant {0} * repeat_ptr [[buffer(0)]],
121 TORCH_CHECK(false, "repeat_interleave: unsupported indexing data type");
128 …id<MTLComputePipelineState> pipelineState = lib.getPipelineStateForFunc("repeat_interleave", {scal…
131 getMPSProfiler().beginProfileKernel(pipelineState, "repeat_interleave:" + scalar_type, false);
/external/executorch/examples/models/llama/source_transformation/
Dsdpa.py140 k = k.repeat_interleave(self.n_rep, dim=1)
141 v = v.repeat_interleave(self.n_rep, dim=1)
153 …This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go f…
287 k = k.repeat_interleave(self.n_rep, dim=1)
288 v = v.repeat_interleave(self.n_rep, dim=1)
/external/libopus/dnn/torch/osce/models/
Dlace.py162 features = torch.repeat_interleave(features.unsqueeze(0), batch_size, 0)
163 periods = torch.repeat_interleave(periods.unsqueeze(0), batch_size, 0)
164 numbits = torch.repeat_interleave(numbits.unsqueeze(0), batch_size, 0)
Dlavoce_400.py125 progression = torch.repeat_interleave(progression, batch_size, 0)
187 periods = torch.repeat_interleave(periods, self.upsamp_factor, 1)
/external/libopus/dnn/torch/dnntools/dnntools/sparsification/
Dcommon.py82 mask = torch.repeat_interleave(mask, m1, dim=0)
83 mask = torch.repeat_interleave(mask, n1, dim=1)
/external/libopus/dnn/torch/lpcnet/utils/sparsification/
Dcommon.py80 mask = torch.repeat_interleave(mask, m1, dim=0)
81 mask = torch.repeat_interleave(mask, n1, dim=1)
/external/pytorch/aten/src/ATen/functorch/
DBatchRulesDecompositions.cpp228 …m.impl("repeat_interleave.self_int", static_cast<decltype(&ATEN_FN2(repeat_interleave, self_int))>… in TORCH_LIBRARY_IMPL()
229 …m.impl("repeat_interleave.self_Tensor", static_cast<decltype(&ATEN_FN2(repeat_interleave, self_Ten… in TORCH_LIBRARY_IMPL()
/external/pytorch/torch/ao/ns/fx/
Dmappings.py274 # repeat_interleave
276 torch.repeat_interleave,
568 torch.repeat_interleave,
743 "repeat_interleave",
/external/pytorch/test/export/
Dtesting.py64 aten.repeat_interleave.self_Tensor,
65 aten.repeat_interleave.self_int,
/external/executorch/examples/models/llama/
Dllama_transformer.py257 k = k.repeat_interleave(self.n_rep, dim=1)
258 v = v.repeat_interleave(self.n_rep, dim=1)
347 k = k.repeat_interleave(self.n_rep, dim=1)
348 v = v.repeat_interleave(self.n_rep, dim=1)
/external/libopus/dnn/torch/lpcnet/utils/
Dmisc.py52 p = torch.flatten(torch.repeat_interleave(torch.cat((x, 1 - x), dim=-1), repeats, dim=-1), -2)
/external/libopus/dnn/torch/fwgan/models/
Dfwgan500.py205 progression = torch.repeat_interleave(progression, batch_size, 0)
232 gain = torch.repeat_interleave(gain, 160, dim=-1)
/external/pytorch/benchmarks/gpt_fast/
Dmodel.py234 k = k.repeat_interleave(self.n_head // self.n_local_heads, dim=1)
235 v = v.repeat_interleave(self.n_head // self.n_local_heads, dim=1)
Dmixtral_moe_model.py213 k = k.repeat_interleave(self.n_head // self.n_local_heads, dim=1)
214 v = v.repeat_interleave(self.n_head // self.n_local_heads, dim=1)
/external/pytorch/torch/onnx/
Dsymbolic_opset13.py582 @_onnx_symbolic("aten::repeat_interleave")
583 def repeat_interleave( function
591 "Unsupported: ONNX export of repeat_interleave for unknown repeats rank.",
596 "Unsupported: ONNX export of repeat_interleave for unknown repeats size.",
601 "Unsupported: ONNX export of repeat_interleave for unknown input size.",
655 return opset9.repeat_interleave(g, self, repeats, final_dim)
/external/pytorch/test/
Dtest_proxy_tensor.py1078 return src_tokens.repeat_interleave(beam_size_src.size(0), 0)
1100 return y.repeat_interleave(x, dim=1)
1107 repeat_interleave = torch.ops.aten.repeat_interleave.Tensor(x_1); x_1 = None
1108 …_select = torch.ops.aten.index_select.default(y_1, 1, repeat_interleave); y_1 = repeat_interleave…
1162 return y.repeat_interleave(x, dim=0, output_size=s)
1170 …repeat_interleave = torch.ops.aten.repeat_interleave.Tensor(x_1, output_size = _local_scalar_dense…
1171 …_select = torch.ops.aten.index_select.default(y_1, 0, repeat_interleave); y_1 = repeat_interleave…
1196 tokens[:, :start_step] = src_tokens.repeat_interleave(beam_size, 0)

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