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Results 1 - 10 of 12 for gradient_function (0.23 sec)
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tensorflow/c/eager/gradients.cc
Status TapeVSpace::CallBackwardFunction( const string& op_type, GradientFunction* gradient_function, const std::vector<int64_t>& unneeded_gradients, gtl::ArraySlice<AbstractTensorHandle*> output_gradients, absl::Span<AbstractTensorHandle*> result) const { if (gradient_function == nullptr) { return errors::InvalidArgument( "Provided null gradient_function for '", op_type, "'.\n",
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 19.3K bytes - Viewed (0) -
tensorflow/c/eager/gradients.h
using GradientFunctionFactory = std::function<GradientFunction*(const ForwardOperation& op)>; // Map from op name to a `GradientFunctionFactory`. class GradientRegistry { public: Status Register(const string& op, GradientFunctionFactory gradient_function_factory); Status Lookup(const ForwardOperation& op, std::unique_ptr<GradientFunction>* gradient_function) const; private:
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Sep 26 10:27:05 GMT 2022 - 6.9K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/custom_gradient_test.cc
tape.Watch(inputs[0]); // Watch x. AbstractTensorHandle* exp_output; TF_RETURN_IF_ERROR(ops::Exp(ctx, inputs[0], &exp_output, "Exp")); std::unique_ptr<GradientFunction> gradient_function( new PassThroughGradientFunction); tape.RecordOperation(inputs, {exp_output}, gradient_function.release()); TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx, /*targets*/ {exp_output},
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 4.8K bytes - Viewed (0) -
tensorflow/c/eager/gradients_test.cc
{x.get()}, absl::MakeSpan(outputs), /*use_function=*/!std::get<2>(GetParam())); ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); ASSERT_EQ( "Provided null gradient_function for 'Neg'.\nIf the intent is to treat " "this op as non-differentiable consider using RegisterNotDifferentiable " "or NotDifferentiableGradientFunction.", s.message()); ASSERT_EQ(nullptr, outputs[0]);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/tape/tape_operation.cc
// Consider getting rid of this and making the behavior between number types // and string consistent. forward_op_.attrs.BuildNodeDef(); // TODO(b/170307493): Populate skip_input_indices here. std::unique_ptr<GradientFunction> backward_fn; TF_RETURN_IF_ERROR(registry_.Lookup(forward_op_, &backward_fn)); tape_->RecordOperation(forward_op_.inputs, forward_op_.outputs, backward_fn.release(), parent_op_->Name());
C++ - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Tue Jun 07 01:53:35 GMT 2022 - 9K bytes - Viewed (1) -
tensorflow/c/experimental/gradients/nn_grad.cc
}; } // namespace GradientFunction* ReluRegisterer(const ForwardOperation& op) { return new ReluGradientFunction(op.outputs); } GradientFunction* SparseSoftmaxCrossEntropyWithLogitsRegisterer( const ForwardOperation& op) { return new SparseSoftmaxCrossEntropyWithLogitsGradientFunction(op.outputs); } GradientFunction* BiasAddRegisterer(const ForwardOperation& op) {
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5.7K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/nn_grad.h
#include "tensorflow/c/eager/gradients.h" namespace tensorflow { namespace gradients { GradientFunction* ReluRegisterer(const ForwardOperation& op); GradientFunction* SparseSoftmaxCrossEntropyWithLogitsRegisterer( const ForwardOperation& op); GradientFunction* BiasAddRegisterer(const ForwardOperation& op); } // namespace gradients } // namespace tensorflow
C - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Thu Dec 03 22:28:48 GMT 2020 - 1.2K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/math_grad.h
namespace tensorflow { namespace gradients { GradientFunction* AddRegisterer(const ForwardOperation& op); GradientFunction* ExpRegisterer(const ForwardOperation& op); GradientFunction* MatMulRegisterer(const ForwardOperation& op); GradientFunction* SqrtRegisterer(const ForwardOperation& op); GradientFunction* NegRegisterer(const ForwardOperation& op); GradientFunction* SubRegisterer(const ForwardOperation& op);
C - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Thu Dec 03 22:28:48 GMT 2020 - 1.5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/math_grad.cc
} GradientFunction* SqrtRegisterer(const ForwardOperation& op) { return new SqrtGradientFunction(op.outputs[0]); } GradientFunction* NegRegisterer(const ForwardOperation& op) { return new NegGradientFunction; } GradientFunction* SubRegisterer(const ForwardOperation& op) { return new SubGradientFunction; } GradientFunction* MulRegisterer(const ForwardOperation& op) { return new MulGradientFunction(op.inputs);
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 15.2K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/array_grad.cc
#include "tensorflow/c/experimental/gradients/array_grad.h" #include "tensorflow/c/eager/abstract_context.h" namespace tensorflow { namespace gradients { namespace { class IdentityNGradientFunction : public GradientFunction { public: Status Compute(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> grad_outputs, absl::Span<AbstractTensorHandle*> grad_inputs) override {
C++ - Registered: Tue Apr 09 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 1.6K bytes - Viewed (0)