/aosp_15_r20/packages/modules/NeuralNetworks/runtime/test/generated/spec_V1_2/ |
D | log_softmax.example.cpp | 1 // Generated from log_softmax.mod.py 7 namespace generated_tests::log_softmax { namespace 54 .type = TestOperationType::LOG_SOFTMAX, in get_test_model() 70 const auto dummy_test_model = TestModelManager::get().add("log_softmax", get_test_model()); 72 } // namespace generated_tests::log_softmax 74 namespace generated_tests::log_softmax { namespace 121 .type = TestOperationType::LOG_SOFTMAX, in get_test_model_relaxed() 139 } // namespace generated_tests::log_softmax 141 namespace generated_tests::log_softmax { namespace 188 .type = TestOperationType::LOG_SOFTMAX, in get_test_model_float16() [all …]
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/aosp_15_r20/external/ComputeLibrary/src/core/CL/cl_kernels/common/ |
H A D | softmax_layer.cl | 78 #if defined(LOG_SOFTMAX) 81 #else // defined(LOG_SOFTMAX) 83 #endif // defined(LOG_SOFTMAX) 189 #ifdef LOG_SOFTMAX 194 #else /* LOG_SOFTMAX */ 199 #endif /* LOG_SOFTMAX */ 211 #ifdef LOG_SOFTMAX 215 #else /* LOG_SOFTMAX */ 219 #endif /* LOG_SOFTMAX */ 407 #ifdef LOG_SOFTMAX [all …]
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/aosp_15_r20/external/executorch/backends/vulkan/runtime/graph/ops/impl/ |
H A D | Softmax.cpp | 37 bool log_softmax) { in add_softmax_node() argument 63 if (log_softmax) { in add_softmax_node() 110 graph, args[0], args[1], args[3], /* log_softmax = */ false); in softmax() 113 void log_softmax(ComputeGraph& graph, const std::vector<ValueRef>& args) { in log_softmax() function 116 graph, args[0], args[1], args[3], /* log_softmax = */ true); in log_softmax() 121 VK_REGISTER_OP(aten._log_softmax.default, log_softmax);
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/aosp_15_r20/packages/modules/NeuralNetworks/common/cpu_operations/ |
D | LogSoftmax.cpp | 31 namespace log_softmax { namespace 88 } // namespace log_softmax 90 NN_REGISTER_OPERATION_DEFAULT_VALIDATION(LOG_SOFTMAX, log_softmax::prepare, log_softmax::execute);
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/aosp_15_r20/external/pytorch/torch/csrc/jit/tensorexpr/operators/ |
H A D | softmax.cpp | 11 bool log_softmax) { in computeSoftmax() argument 27 // log_softmax(vi) = log(softmax(vi)) in computeSoftmax() 31 // log_softmax(vi) = vi - max(vi) - log(sum(exp(vi - max(vi)))) in computeSoftmax() 39 // - Final loop computes the log_softmax for every element in v. in computeSoftmax() 129 if (!log_softmax) { in computeSoftmax()
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/aosp_15_r20/packages/modules/NeuralNetworks/common/types/operations/src/ |
D | LogSoftmax.cpp | 24 namespace log_softmax { namespace 46 } // namespace log_softmax 48 NN_DEFINE_VALIDATION_FUNCTION(LOG_SOFTMAX, log_softmax::validate);
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/aosp_15_r20/external/tensorflow/tensorflow/lite/testing/op_tests/ |
H A D | log_softmax.py | 15 """Test configs for log_softmax.""" 24 """Make a set of tests to do log_softmax.""" 32 """Build the log_softmax op testing graph.""" 38 out = tf.nn.log_softmax(input_tensor)
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/aosp_15_r20/external/executorch/backends/arm/_passes/ |
H A D | decompose_softmaxes_pass.py | 14 torch_softmax = (torch.ops.aten.softmax.int, torch.ops.aten.log_softmax.int) 22 log_softmax = (torch.ops.aten.log_softmax.int, exir_ops.edge.aten._log_softmax.default) variable 74 if op in log_softmax:
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/aosp_15_r20/packages/modules/NeuralNetworks/common/types/operations/include/ |
D | LogSoftmax.h | 22 namespace android::nn::log_softmax { 24 constexpr char kOperationName[] = "LOG_SOFTMAX"; 34 } // namespace android::nn::log_softmax
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/aosp_15_r20/external/pytorch/torch/csrc/api/src/nn/modules/ |
H A D | adaptive.cpp | 137 const Tensor cluster_logprob = F::log_softmax(cluster_output, 1); in forward() 159 const Tensor head_logprob = F::log_softmax(head_output, 1); in forward() 174 const Tensor head_logprob = F::log_softmax(head_output, 1); in _get_full_log_prob() 184 const Tensor cluster_logprob = F::log_softmax(cluster_output, 1); in _get_full_log_prob()
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/aosp_15_r20/external/tensorflow/tensorflow/dtensor/mlir/expansions/ |
H A D | softmax_spmd_expander.cc | 159 auto log_softmax = builder.create<mlir::TF::SubOp>( in ComputeLogSoftmax() local 161 return log_softmax.getResult(); in ComputeLogSoftmax() 169 bool log_softmax) { in ComputeShardedSoftmax() argument 177 if (log_softmax) { in ComputeShardedSoftmax() 574 // softmax is 1 and log_softmax is 0. in ExpandOp() 579 const mlir::Value log_softmax = in ExpandOp() local 599 features_zero, log_softmax) in ExpandOp()
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/aosp_15_r20/external/pytorch/torch/nn/modules/ |
H A D | adaptive.py | 238 cluster_logprob = F.log_softmax(cluster_output, dim=1) 252 head_logprob = F.log_softmax(head_output, dim=1) 264 head_logprob = F.log_softmax(head_output, dim=1) 270 cluster_logprob = F.log_softmax(cluster_output, dim=1)
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H A D | loss.py | 212 >>> log_softmax = nn.LogSoftmax(dim=1) 218 >>> loss = loss_fn(log_softmax(input), target) 227 >>> log_softmax = nn.LogSoftmax(dim=1) 229 >>> output = log_softmax(conv(data)) 519 >>> input = F.log_softmax(torch.randn(3, 5, requires_grad=True), dim=1) 525 >>> log_target = F.log_softmax(torch.rand(3, 5), dim=1) 1855 :func:`torch.nn.functional.log_softmax`). 1895 >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 1913 >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 1930 >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_()
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/aosp_15_r20/external/executorch/backends/arm/test/ops/ |
H A D | test_logsoftmax.py | 52 .check(["torch.ops.aten.log_softmax.int"]) 73 .check_not(["torch.ops.aten.log_softmax.int"]) 97 .check_not(["torch.ops.aten.log_softmax.int"])
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/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/functional/ |
H A D | activation.h | 307 inline Tensor log_softmax( in log_softmax() function 314 ret = input.log_softmax(dim); in log_softmax() 316 ret = input.log_softmax(dim, dtype); in log_softmax() 325 /// https://pytorch.org/docs/main/nn.functional.html#torch.nn.functional.log_softmax 334 /// F::log_softmax(input, LogSoftmaxFuncOptions(1)); 336 inline Tensor log_softmax( in log_softmax() function 339 return detail::log_softmax(input, options.dim(), options.dtype()); in log_softmax()
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/aosp_15_r20/external/pytorch/test/cpp/tensorexpr/ |
H A D | test_kernel.cpp | 1083 for (auto log_softmax : {false, true}) { in TEST_F() 1088 log_softmax ? a.log_softmax(softmax_dim) : a.softmax(softmax_dim); in TEST_F() 1091 env.s("op", log_softmax ? "log_softmax" : "softmax"); in TEST_F() 1156 for (auto log_softmax : {false, true}) { in TEST_F() 1166 log_softmax ? a.log_softmax(softmax_dim) : a.softmax(softmax_dim); in TEST_F() 1170 env.s("op", log_softmax ? "log_softmax" : "softmax"); in TEST_F() 1237 for (auto log_softmax : {false, true}) { in TEST_F() 1247 log_softmax ? a.log_softmax(softmax_dim) : a.softmax(softmax_dim); in TEST_F() 1251 env.s("op", log_softmax ? "log_softmax" : "softmax"); in TEST_F()
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/aosp_15_r20/external/pytorch/torch/_refs/special/ |
H A D | __init__.py | 37 "log_softmax", 206 def log_softmax( function 211 return torch.log_softmax(a=a, dim=dim, dtype=dtype) # type: ignore[call-overload]
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/aosp_15_r20/external/pytorch/aten/src/ATen/native/ |
H A D | SoftMax.cpp | 27 #include <ATen/ops/log_softmax.h> 499 Tensor log_softmax(const Tensor& input_, const int64_t dim_, std::optional<ScalarType> dtype) { in log_softmax() function 551 return at::log_softmax(input, dim, dtype); in special_log_softmax() 568 Tensor log_softmax(const Tensor& self, Dimname dim, std::optional<ScalarType> dtype) { in log_softmax() function 569 return at::log_softmax(self, dimname_to_position(self, dim), dtype); in log_softmax()
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H A D | LossNLL.cpp | 20 #include <ATen/ops/log_softmax.h> 506 auto input = at::log_softmax(self, class_dim, self.scalar_type()); in cross_entropy_loss_prob_target() 566 auto input = at::log_softmax(self, class_dim, self.scalar_type()); in cross_entropy_loss_label_smoothing() 652 at::log_softmax(self, class_dim, self.scalar_type()), in cross_entropy_loss_symint()
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/aosp_15_r20/out/soong/.intermediates/hardware/interfaces/neuralnetworks/aidl/android.hardware.neuralnetworks-V4-ndk-source/gen/include/aidl/android/hardware/neuralnetworks/ |
D | OperationType.h | 91 LOG_SOFTMAX = 64, enumerator 273 case OperationType::LOG_SOFTMAX: in toString() 274 return "LOG_SOFTMAX"; in toString() 435 aidl::android::hardware::neuralnetworks::OperationType::LOG_SOFTMAX,
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/aosp_15_r20/external/pytorch/torch/masked/ |
H A D | _ops.py | 189 log_softmax=(("dim__as_int",), ("dtype=None", "mask=None")), 237 log_softmax="""\ 276 log_softmax="log_softmax", 969 "log_softmax", 1733 def log_softmax( function 1745 return torch.nn.functional.log_softmax(mask_input, dim_, dtype=dtype) 1748 f"masked log_softmax expects strided tensor (got {mask_input.layout} tensor)"
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H A D | __init__.py | 15 log_softmax, 42 "log_softmax",
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/aosp_15_r20/external/tensorflow/tensorflow/python/ops/distributions/ |
H A D | categorical.py | 317 nn_ops.log_softmax(self.logits) * self.probs, axis=-1) 342 delta_log_probs1 = (nn_ops.log_softmax(a.logits) - 343 nn_ops.log_softmax(b.logits))
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/aosp_15_r20/external/executorch/kernels/portable/cpu/ |
H A D | op_log_softmax.cpp | 53 // calculate max in log_softmax dim. During log_softmax in log_softmax_out()
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/aosp_15_r20/external/executorch/exir/tests/ |
H A D | test_op_convert.py | 64 aten.log_softmax.int: aten.log_softmax.int_out,
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