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Results 1 - 3 of 3 for RecordOperation (0.15 sec)
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tensorflow/c/eager/gradients_internal.h
absl::Status SetAttrFunctionList(AbstractOperation*, const char* attr_name, absl::Span<const AbstractOperation*> values, ForwardOperation*); // Make the call to `Tape::RecordOperation`. absl::Status Execute(AbstractOperation*, AbstractContext*, absl::Span<AbstractTensorHandle*> retvals, int* num_retvals, ForwardOperation*, Tape*,
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 12 05:11:17 UTC 2024 - 4.7K bytes - Viewed (0) -
tensorflow/c/eager/gradients_test.cc
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"); return tape.ComputeGradient(ctx, /*targets=*/{neg_output}, /*sources=*/inputs,
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 12 05:11:17 UTC 2024 - 7K bytes - Viewed (0) -
tensorflow/c/eager/gradients.h
// on the tape and marks all its outputs as watched if at // least one input of the op is watched and has a trainable dtype. // op_name is optional and is used for debugging only. void RecordOperation(absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle* const> outputs, GradientFunction* gradient_function,
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 12 05:11:17 UTC 2024 - 6.9K bytes - Viewed (0)