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Results 1 - 6 of 6 for SqrtGrad (0.12 sec)
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tensorflow/c/experimental/gradients/math_grad.cc
using tensorflow::ops::Div; using tensorflow::ops::DivNoNan; using tensorflow::ops::MatMul; using tensorflow::ops::Mul; using tensorflow::ops::Neg; using tensorflow::ops::OnesLike; using tensorflow::ops::SqrtGrad; namespace tensorflow { namespace gradients { namespace { static Status SafeConj(AbstractContext* ctx, AbstractTensorHandle* const input, AbstractTensorHandle** output, const char* name) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 13:53:47 UTC 2024 - 15.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.td
)>; //===----------------------------------------------------------------------===// // Sqrt op patterns. //===----------------------------------------------------------------------===// // SqrtGrad(y, dy) = dy * 0.5 / y def LowerSqrtGradOp : Pat< (TF_SqrtGradOp $y, $dy), (TF_DivOp (TF_MulOp $dy, (TF_ConstOp (GetScalarOfFloatType<"0.5"> $dy))), $y )>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 04 13:30:42 UTC 2024 - 24.7K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad.cc
REGISTER_GRADIENT_OP("Square", SquareGrad); Status SqrtGrad(const Scope& scope, const Operation& op, const std::vector<Output>& grad_inputs, std::vector<Output>* grad_outputs) { // Use the built-in operator. grad_outputs->push_back( internal::SqrtGrad(scope, op.output(0), grad_inputs[0])); return scope.status(); } REGISTER_GRADIENT_OP("Sqrt", SqrtGrad);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 50.7K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass.cc
"BitwiseAnd", "BitwiseOr", "BitwiseXor", "LeftShift", "RightShift", "LogicalAnd", "LogicalOr", "Mod", "Maximum", "Minimum", "RealDiv", "ReciprocalGrad", "RsqrtGrad", "SqrtGrad", "TruncateDiv", "TruncateMod", "Equal", "NotEqual", "Greater", "GreaterEqual", "Less", "LessEqual", "SigmoidGrad", "SoftplusGrad", "SoftsignGrad",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 12:19:41 UTC 2024 - 85.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir
// CHECK: %[[RET:.*]] = "tf.Div"(%[[MUL]], %arg0) : (tensor<*xcomplex<f32>>, tensor<*xcomplex<f32>>) -> tensor<*xcomplex<f32>> %0 = "tf.SqrtGrad"(%arg0, %arg1) : (tensor<*xcomplex<f32>>, tensor<*xcomplex<f32>>) -> tensor<*xcomplex<f32>> // CHECK: return %[[RET]] func.return %0 : tensor<*xcomplex<f32>> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 92K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
static bool isCompatibleReturnTypes(TypeRange inferred, TypeRange actual) { return ArraysAreCastCompatible(inferred, actual); } }]; } def TF_SqrtGradOp : TF_Op<"SqrtGrad", [Pure, TF_SameOperandsAndResultTypeResolveRef]> { let summary = "Computes the gradient for the sqrt of `x` wrt its input."; let description = [{
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)