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tensorflow/c/eager/gradients.h
TapeTensor>::GradientTape; // Returns whether the tape is persistent, i.e., whether the tape will hold // onto its internal state after a call to `ComputeGradient`. using GradientTape<AbstractTensorHandle, GradientFunction, TapeTensor>::IsPersistent; // Adds this tensor to the list of watched tensors. //
Created: Tue Apr 07 12:39:13 GMT 2026 - Last Modified: Sat Oct 12 05:11:17 GMT 2024 - 6.9K bytes - Click Count (0) -
tensorflow/c/eager/gradients.cc
std::vector<int64_t> ids(tensors.size()); for (int i = 0; i < tensors.size(); i++) { ids[i] = ToId(tensors[i]); } return ids; } absl::Status Tape::ComputeGradient( AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> targets, absl::Span<AbstractTensorHandle* const> sources, absl::Span<AbstractTensorHandle* const> output_gradients,
Created: Tue Apr 07 12:39:13 GMT 2026 - Last Modified: Tue Feb 24 06:18:31 GMT 2026 - 19.6K bytes - Click Count (0) -
tensorflow/c/eager/gradients_test.cc
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"); return tape.ComputeGradient(ctx, /*targets=*/{neg_output}, /*sources=*/inputs, /*output_gradients=*/{}, outputs); }
Created: Tue Apr 07 12:39:13 GMT 2026 - Last Modified: Sat Oct 12 05:11:17 GMT 2024 - 7K bytes - Click Count (0)