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Migrating from functorch to torch.func
torch.func, previously known as “functorch”, is JAX-like composable function transforms for PyTorch. functorch started as an out-of-tree library over at the pytorch/functorch repository. Our goal has ...
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UX Limitations
torch.func, like JAX , has restrictions around what can be transformed. In general, JAX’s limitations are that transforms only work with pure functions: that is, functions where the output is complete...
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Patching Batch Norm
What’s happening? Batch Norm requires in-place updates to running_mean and running_var of the same size as the input. Functorch does not support inplace update to a regular tensor that takes in a batc...
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torch.func.replace_all_batch_norm_modules_
In place updates root by setting the running_mean and running_var to be None and setting track_running_stats to be False for any nn.BatchNorm module in root Module
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torch.func.stack_module_state
Prepares a list of torch.nn.Modules for ensembling with vmap() . Given a list of M nn.Modules of the same class, returns two dictionaries that stack all of their parameters and buffers together, index...
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POE0004:operator-supported-in-newer-opset-version
Operator is supported in newer opset version. Example:
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torch.func.functional_call
Performs a functional call on the module by replacing the module parameters and buffers with the provided ones. Note If the module has active parametrizations, passing a value in the parameters_and_bu...
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POE0003:missing-standard-symbolic-function
Missing symbolic function for standard PyTorch operator, cannot translate node to ONNX.
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torch.func.functionalize
functionalize is a transform that can be used to remove (intermediate) mutations and aliasing from a function, while preserving the function’s semantics. functionalize(func) returns a new function wit...
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POE0002:missing-custom-symbolic-function
Missing symbolic function for custom PyTorch operator, cannot translate node to ONNX.
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torch.signal.windows.nuttall
Computes the minimum 4-term Blackman-Harris window according to Nuttall. where z_n = 2 π n/ M . The window is normalized to 1 (maximum value is 1). However, the 1 doesn’t appear if M is even and sym i...
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torch.func.hessian
Computes the Hessian of func with respect to the arg(s) at index argnum via a forward-over-reverse strategy. The forward-over-reverse strategy (composing jacfwd(jacrev(func)) ) is a good default for g...
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