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Results 1 - 10 of 32 for AbstractTensorHandle (0.26 sec)
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tensorflow/c/experimental/gradients/nn_grad.cc
} } private: // TODO(b/174778737): Only hold needed outputs. vector<AbstractTensorHandle*> forward_outputs_; }; Status BroadcastMul(AbstractContext* ctx, AbstractTensorHandle* vec, AbstractTensorHandle* mat, absl::Span<AbstractTensorHandle*> outputs) { if (!isa<ImmediateExecutionContext>(ctx)) { // TODO(b/168850692): Fix this. return errors::Unimplemented(
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_test.cc
absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) { return ops::Relu(ctx, inputs[0], &outputs[0], "Relu"); } Status SparseSoftmaxCrossEntropyWithLogitsModel( AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) { AbstractTensorHandle* loss; AbstractTensorHandle* backprop;
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 8.3K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.cc
absl::Span<AbstractTensorHandle* const> inputs, int input_index, bool use_function, AbstractTensorHandle** numerical_grad) { vector<AbstractTensorHandle*> theta_inputs(inputs.size()); for (int i{}; i < inputs.size(); ++i) { theta_inputs[i] = inputs[i]; } AbstractTensorHandle* theta =
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7.3K bytes - Viewed (0) -
tensorflow/c/eager/unified_api_testutil.h
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Feb 27 13:57:45 GMT 2024 - 4K bytes - Viewed (0) -
tensorflow/c/eager/gradients.cc
TapeTensor TapeVSpace::TapeTensorFromGradient(AbstractTensorHandle* g) const { return TapeTensor(g); } void TapeVSpace::MarkAsResult(AbstractTensorHandle* gradient) const {} void TapeVSpace::DeleteGradient(AbstractTensorHandle* gradient) const { gradient->Unref(); } void Tape::Watch(const AbstractTensorHandle* t) { GradientTape::Watch(ToId(t)); }
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/experimental/gradients/math_grad_test.cc
Status AddModel(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) { return ops::AddV2(ctx, inputs[0], inputs[1], &outputs[0], "Add"); } Status ExpModel(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) { return ops::Exp(ctx, inputs[0], &outputs[0], "Exp");
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Thu Apr 13 17:32:14 GMT 2023 - 16.3K bytes - Viewed (0) -
tensorflow/c/eager/gradients_test.cc
ASSERT_EQ(read_message, message); } Status RecordOperationWithNullGradientFunctionModel( AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) { Tape tape(/*persistent=*/false); tape.Watch(inputs[0]); AbstractTensorHandle* neg_output; TF_RETURN_IF_ERROR(ops::Neg(ctx, inputs[0], &neg_output, "Neg")); tape.RecordOperation(inputs, {neg_output}, nullptr, "Neg");
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/custom_gradient_test.cc
// outputs = [f(inputs[0])] Status ExpWithPassThroughGrad(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) { Tape tape(/*persistent=*/false); tape.Watch(inputs[0]); // Watch x. AbstractTensorHandle* exp_output; TF_RETURN_IF_ERROR(ops::Exp(ctx, inputs[0], &exp_output, "Exp"));
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/experimental/gradients/grad_test_helper.cc
AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) -> Status { Tape tape(/*persistent=*/false); for (size_t i{}; i < inputs.size(); ++i) { tape.Watch(inputs[i]); } std::vector<AbstractTensorHandle*> temp_outputs(1); AbstractContextPtr tape_ctx(new TapeContext(ctx, &tape, grad_registry));
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/array_grad_test.cc
namespace internal { namespace { using tensorflow::TF_StatusPtr; Status IdentityNModel(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) { std::vector<AbstractTensorHandle*> temp_outputs(2); TF_RETURN_IF_ERROR( ops::IdentityN(ctx, inputs, absl::MakeSpan(temp_outputs), "IdentityN"));
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5K bytes - Viewed (0)