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Automatic differentiation package - tensorplay.autograd Automatic Mixed Precision package - tensorplay.amp Distributed communication package - tensorplay.distributed Multiprocessing package - tensorplay.multiprocessing Quantization tensorplay tensorplay.audio tensorplay.compiler tensorplay.cuda tensorplay.fft tensorplay.futures tensorplay.hub tensorplay.library tensorplay.linalg tensorplay.nn tensorplay.nn.functional tensorplay.nn.init tensorplay.optim tensorplay.random tensorplay.sparse tensorplay.special tensorplay.stax tensorplay.utils.checkpoint tensorplay.utils.data tensorplay.vision Upstream anchor labels

detect_anomaly enable_grad Function inference_mode no_grad set_detect_anomaly set_grad_enabled tensorplay.autograd.backward tensorplay.autograd.function.once_differentiable tensorplay.autograd.functional.hessian tensorplay.autograd.functional.hvp tensorplay.autograd.functional.jacobian tensorplay.autograd.functional.jvp tensorplay.autograd.functional.vhp tensorplay.autograd.functional.vjp tensorplay.autograd.grad tensorplay.autograd.grad_mode.is_grad_enabled tensorplay.autograd.gradcheck.get_analytical_jacobian tensorplay.autograd.gradcheck.get_numerical_jacobian tensorplay.autograd.gradcheck.get_numerical_jacobian_wrt_specific_input tensorplay.autograd.gradcheck.gradcheck tensorplay.autograd.gradcheck.GradcheckError tensorplay.autograd.gradcheck.gradgradcheck tensorplay.autograd.jvp

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tensorplay.autograd.backward

tensorplay.autograd.backward(tensors: collections.abc.Sequence[tensorplay._C.TensorBase], grad_tensors: collections.abc.Sequence[tensorplay._C.TensorBase] | None = None, retain_graph: bool | None = None, create_graph: bool = False) → None

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set_grad_enabled

Context-manager that sets gradient calculation on or off.

tensorplay.autograd.function.once_differentiable

Decorator to make a custom autograd Function’s backward run once, with gradients detached and grad-mode disabled inside.