eabdb87f9f
* Add numpy ops (initial batch) and some config * Add unit test * fix call * Revert "fix call" This reverts commit 6748ad183029ff4b97317b77ceed8661916bb9a0. * full unit test coverage * fix setup.py
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
from tensorflow import nest
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from keras_core.backend import KerasTensor
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class SymbolicArguments:
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def __init__(self, *args, **kwargs):
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# TODO: validation
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self.args = nest.map_structure(lambda x: x, args)
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self.kwargs = nest.map_structure(lambda x: x, kwargs)
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self._flat_arguments = nest.flatten((self.args, self.kwargs))
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# Used to avoid expensive `nest` operations in the most common case.
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if (
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not self.kwargs
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and len(self.args) == 1
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and isinstance(self.args[0], KerasTensor)
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):
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self._single_positional_tensor = self.args[0]
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else:
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self._single_positional_tensor = None
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self.keras_tensors = []
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for arg in self._flat_arguments:
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if isinstance(arg, KerasTensor):
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self.keras_tensors.append(arg)
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def convert(self, conversion_fn):
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args = nest.map_structure(conversion_fn, self.args)
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kwargs = nest.map_structure(conversion_fn, self.kwargs)
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return args, kwargs
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def fill_in(self, tensor_dict):
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"""Maps KerasTensors to computed values using `tensor_dict`.
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`tensor_dict` maps `KerasTensor` instances to their current values.
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"""
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if self._single_positional_tensor is not None:
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# Performance optimization for most common case.
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# Approx. 70x faster.
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return (tensor_dict[self._single_positional_tensor],), {}
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def switch_fn(x):
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val = tensor_dict.get(x, None)
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if val is not None:
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return val
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return x
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return self.convert(switch_fn)
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