| /external/pytorch/test/onnx/ |
| D | test_onnxscript_no_runtime.py | 27 # 1. Register Selu onnxscript function as custom Op
31 def Selu(X): function
43 return g.onnxscript_op(Selu, X).setType(X.type())
46 symbolic_name="aten::selu",
88 model_selu = torch.nn.SELU()
106 self.assertEqual(selu_proto.functions[0].name, "Selu")
115 self.selu = torch.nn.SELU()
122 y = self.selu(x)
135 def Selu(X): function
150 return g.onnxscript_op(Selu, X).setType(X.type())
[all …]
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| D | test_onnxscript_runtime.py | 24 model = torch.nn.SELU()
31 def Selu( function
45 return g.onnxscript_op(Selu, X).setType(X.type())
48 symbolic_name="aten::selu",
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SeluGrad.pbtxt | 7 The backpropagated gradients to the corresponding Selu operation.
13 The outputs of the corresponding Selu operation.
23 summary: "Computes gradients for the scaled exponential linear (Selu) operation."
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| D | api_def_Selu.pbtxt | 2 graph_op_name: "Selu"
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| /external/tensorflow/tensorflow/core/kernels/mlir_generated/ |
| D | gpu_op_selu.cc | 21 GENERATE_AND_REGISTER_UNARY_GPU_KERNEL(Selu, DT_HALF);
22 GENERATE_AND_REGISTER_UNARY_GPU_KERNEL(Selu, DT_FLOAT);
23 GENERATE_AND_REGISTER_UNARY_GPU_KERNEL(Selu, DT_DOUBLE);
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| /external/tensorflow/tensorflow/core/api_def/python_api/ |
| D | api_def_Selu.pbtxt | 2 graph_op_name: "Selu"
4 name: "nn.selu"
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| /external/tensorflow/tensorflow/core/api_def/java_api/ |
| D | api_def_Selu.pbtxt | 2 graph_op_name: "Selu"
4 name: "nn.Selu"
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| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_grad_test.py | 228 selu = gen_nn_ops.selu(inputs)
229 selu_grad = gradients_impl.gradients(selu, inputs, grad_ys=dummy)[0]
245 selu = gen_nn_ops.selu(inputs)
246 selu_grad = gradients_impl.gradients(selu, inputs, grad_ys=dummy)[0]
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | Selu.pbtxt | 2 name: "Selu"
24 name: "Selu"
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
| D | Selu.pbtxt | 2 name: "Selu"
24 name: "Selu"
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | relu_op_functor.h | 174 struct Selu { struct
175 // Computes Selu activation.
198 // gradients: gradients backpropagated to the Selu op. argument
199 // activations: outputs of the Selu op.
200 // backprops: gradients to backpropagate to the Selu inputs.
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| D | relu_op.cc | 75 Name("Selu").Device(DEVICE_CPU).TypeConstraint<type>("T"), \
81 // Elu and Selu only make sense with float or double.
104 void Selu<GPUDevice, T>::operator()( \
107 extern template struct Selu<GPUDevice, T>;
120 Name("Selu").Device(DEVICE_GPU).TypeConstraint<type>("T"), \
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| D | unary_ops_composition.cc | 171 // Register compute function for the Relu/Relu6/Elu/Selu.
204 auto selu = functor::Selu<Eigen::DefaultDevice, T>(); \
205 selu(Eigen::DefaultDevice(), in, *out); \
255 REGISTER_COMPUTE_FN(Selu); in UnaryOpsCompositionSupport()
320 REGISTER_COMPUTE_FN(Selu); in UnaryOpsCompositionSupport()
384 REGISTER_COMPUTE_FN(Selu); in UnaryOpsCompositionSupport()
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| /external/tensorflow/tensorflow/python/keras/ |
| D | activations.py | 146 @keras_export('keras.activations.selu')
148 def selu(x): function
149 """Scaled Exponential Linear Unit (SELU).
151 The Scaled Exponential Linear Unit (SELU) activation function is defined as:
159 Basically, the SELU activation function multiplies `scale` (> 1) with the
175 ... activation='selu'))
177 ... activation='selu'))
179 ... activation='selu'))
197 return nn.selu(x)
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | elu_op.cc | 35 XlaOp Selu(XlaOp x) { in Selu() function
82 ctx->SetOutput(0, xla::Selu(ctx->Input(0))); in Compile()
107 REGISTER_XLA_OP(Name("Selu"), SeluOp);
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| D | elu_op.h | 23 XlaOp Selu(XlaOp x);
|
| /external/pytorch/torch/nn/modules/ |
| D | __init__.py | 21 SELU,
300 "SELU",
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| /external/pytorch/torch/_refs/nn/functional/ |
| D | __init__.py | 57 "selu",
119 # alpha = - SELU.alpha * SELU.scale, here
120 # SELU.alpha = 1.6732632423543772848170429916717 and
121 # SELU.scale = 1.0507009873554804934193349852946
400 @register_decomposition(aten.selu)
407 def selu(a: TensorLikeType, inplace: bool = False) -> TensorLikeType: function
409 Reference implementation of torch.nn.functional.selu
1278 selu_ = _make_inplace(selu)
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| /external/tensorflow/tensorflow/core/kernels/mlir_generated/op_definitions/ |
| D | selu.mlir.tmpl | 3 %0 = "tf.Selu"(%arg0) : (tensor<*xelem_type>) -> tensor<*xoutput_type>
|
| /external/pytorch/test/onnx/expect/ |
| D | TestOperators.test_selu.expect | 9 op_type: "Selu"
|
| /external/pytorch/functorch/dim/ |
| D | op_properties.py | 271 torch.selu,
272 torch.nn.functional.selu,
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| /external/pytorch/torch/ao/pruning/_experimental/pruner/ |
| D | base_structured_sparsifier.py | 53 F.selu,
80 nn.SELU,
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| /external/pytorch/torch/csrc/api/include/torch/nn/modules/ |
| D | activation.h | 49 // ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SELU ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
51 /// Applies the selu function element-wise.
52 /// See https://pytorch.org/docs/main/nn.html#torch.nn.SELU to learn
60 /// SELU model(SELUOptions().inplace(true));
70 /// Pretty prints the `SELU` module into the given `stream`.
79 /// provides, and examples of how to use `SELU` with `torch::nn::SELUOptions`.
82 TORCH_MODULE(SELU);
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| /external/tensorflow/tensorflow/python/kernel_tests/nn_ops/ |
| D | relu_op_test.py | 519 tf_selu = nn_ops.selu(np_features)
537 nn_ops.selu, [x], delta=1.0 / 1024))
545 *gradient_checker_v2.compute_gradient(nn_ops.selu, [x]))
555 y = nn_ops.selu(x)
573 y = nn_ops.selu(x)
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| /external/pytorch/torch/csrc/jit/passes/ |
| D | restore_mutation.h | 28 {aten::selu, false},
|