/aosp_15_r20/external/libopus/dnn/torch/osce/utils/layers/ |
H A D | silk_upsampler.py | 131 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)
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H A D | pitch_auto_correlator.py | 63 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)
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H A D | limited_adaptive_comb1d.py | 184 idx = torch.repeat_interleave(idx, batch_size, 0) 185 idx = torch.repeat_interleave(idx, self.in_channels, 1)
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/aosp_15_r20/external/executorch/backends/vulkan/runtime/graph/ops/impl/ |
H A D | RepeatInterleave.cpp | 49 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);
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/aosp_15_r20/external/executorch/examples/models/llama/source_transformation/ |
H A D | sdpa.py | 140 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)
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/aosp_15_r20/external/pytorch/aten/src/ATen/native/mps/operations/ |
H A D | Repeat.mm | 89 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);
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/aosp_15_r20/external/pytorch/aten/src/ATen/native/ |
H A D | NegateFallback.cpp | 31 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()
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H A D | Repeat.cpp | 13 #include <ATen/ops/repeat_interleave.h> 119 … TORCH_CHECK(*output_size == calculated_size, "repeat_interleave: Invalid output_size, expected ", in repeat_interleave_symint()
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/aosp_15_r20/external/pytorch/aten/src/ATen/ |
H A D | ConjugateFallback.cpp | 32 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()
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/aosp_15_r20/external/pytorch/aten/src/ATen/functorch/ |
H A D | BatchRulesDecompositions.cpp | 228 …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()
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/aosp_15_r20/external/pytorch/torch/ao/ns/fx/ |
H A D | mappings.py | 274 # repeat_interleave 276 torch.repeat_interleave, 568 torch.repeat_interleave, 743 "repeat_interleave",
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/aosp_15_r20/external/pytorch/test/ |
H A D | test_proxy_tensor.py | 1078 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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/aosp_15_r20/external/libopus/dnn/torch/osce/models/ |
H A D | lace.py | 162 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)
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H A D | lavoce_400.py | 125 progression = torch.repeat_interleave(progression, batch_size, 0) 187 periods = torch.repeat_interleave(periods, self.upsamp_factor, 1)
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/aosp_15_r20/external/pytorch/torch/onnx/ |
H A D | symbolic_opset13.py | 582 @_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)
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/aosp_15_r20/external/executorch/examples/models/llama/ |
H A D | llama_transformer.py | 257 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)
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/aosp_15_r20/external/executorch/backends/vulkan/runtime/graph/ops/glsl/ |
H A D | repeat_interleave.yaml | 1 repeat_interleave: 10 - NAME: repeat_interleave
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/aosp_15_r20/external/libopus/dnn/torch/dnntools/dnntools/sparsification/ |
H A D | common.py | 82 mask = torch.repeat_interleave(mask, m1, dim=0) 83 mask = torch.repeat_interleave(mask, n1, dim=1)
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/aosp_15_r20/external/libopus/dnn/torch/lpcnet/utils/sparsification/ |
H A D | common.py | 80 mask = torch.repeat_interleave(mask, m1, dim=0) 81 mask = torch.repeat_interleave(mask, n1, dim=1)
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/aosp_15_r20/external/pytorch/torch/_higher_order_ops/ |
H A D | flex_attention.py | 239 value = torch.repeat_interleave(value, G, dim=1) 240 key = torch.repeat_interleave(key, G, dim=1) 744 key = torch.repeat_interleave(key, G, dim=1) 745 value = torch.repeat_interleave(value, G, dim=1)
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/aosp_15_r20/external/pytorch/test/export/ |
H A D | testing.py | 64 aten.repeat_interleave.self_Tensor, 65 aten.repeat_interleave.self_int,
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/aosp_15_r20/external/libopus/dnn/torch/fwgan/models/ |
H A D | fwgan500.py | 205 progression = torch.repeat_interleave(progression, batch_size, 0) 232 gain = torch.repeat_interleave(gain, 160, dim=-1)
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H A D | fwgan400.py | 240 progression = torch.repeat_interleave(progression, batch_size, 0) 267 gain = torch.repeat_interleave(gain, 160, dim=-1)
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/aosp_15_r20/external/pytorch/benchmarks/gpt_fast/ |
H A D | model.py | 234 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)
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H A D | mixtral_moe_model.py | 213 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)
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