[2.8 backport] Resolve bug with re-saving Estimator-exported SavedModel #53676
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…g a TF1 model in TF2.
Signatures are saved using nest.flatten, which sorts the keys alphabetically for determinism. This can cause a mismatch between the lifted signature function's arg_keywords and structured_input_signature, resulting in users not being able to re-save the signature.
Detailed example below.
Say there is a SavedModel signature with the inputs:
```
inputs['a'] tensor_info:
dtype: DT_FLOAT
shape: (-1, 1)
name: input_2:0
inputs['b'] tensor_info:
dtype: DT_FLOAT
shape: (-1, 2)
name: input_1:0
```
When this signature is loaded using the TF2 API, it becomes a concrete function with arg keywords = `['b', 'a']` (sorted by tensor name)
The `structured_input_signature` becomes `([], {'b': spec_for_b, 'a': spec_for_a})`
When this function is exported as a signature in a new SavedModel, the structured inputs are flattened and zipped with the arg keywords. However, the flattened `structured_input_signature` is `[spec_for_a, spec_for_b]`, since `nest.flatten` sorts the keys for determinism. This results in the wrong spec being mapped to the wrong arguments.
PiperOrigin-RevId: 417889747
Change-Id: Icdce72a43033027c18f5530068f2d6fd47e8e32d
mihaimaruseac
approved these changes
Jan 7, 2022
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Change description
Sort signature inputs by input key instead of tensor name when loading a TF1 model in TF2.
Signatures are saved using nest.flatten, which sorts the keys alphabetically for determinism. This can cause a mismatch between the lifted signature function's arg_keywords and structured_input_signature, resulting in users not being able to re-save the signature.
Detailed example below.
Say there is a SavedModel signature with the inputs:
When this signature is loaded using the TF2 API, it becomes a concrete function with arg keywords =
['b', 'a'](sorted by tensor name)The
structured_input_signaturebecomes([], {'b': spec_for_b, 'a': spec_for_a})When this function is exported as a signature in a new SavedModel, the structured inputs are flattened and zipped with the arg keywords. However, the flattened
structured_input_signatureis[spec_for_a, spec_for_b], sincenest.flattensorts the keys for determinism. This results in the wrong spec being mapped to the wrong arguments.PiperOrigin-RevId: 417889747
Change-Id: Icdce72a43033027c18f5530068f2d6fd47e8e32d