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⚡️ Speed up function compute_expand_dims_output_shape by 503% #158

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⚡️ Speed up function compute_expand_dims_output_shape by 503% #158

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4 changes: 1 addition & 3 deletions keras/src/backend/common/backend_utils.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
import functools
import operator
import re
import warnings

Expand Down Expand Up @@ -262,14 +261,13 @@ def compute_conv_transpose_output_shape(

def canonicalize_axis(axis, num_dims):
"""Canonicalize an axis in [-num_dims, num_dims) to [0, num_dims)."""
axis = operator.index(axis)
if not -num_dims <= axis < num_dims:
raise ValueError(
f"axis {axis} is out of bounds for an array with dimension "
f"{num_dims}."
)
if axis < 0:
axis = axis + num_dims
axis += num_dims
return axis


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3 changes: 2 additions & 1 deletion keras/src/ops/operation_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -68,9 +68,10 @@ def compute_expand_dims_output_shape(input_shape, axis):
axis = to_tuple_or_list(axis)
out_ndim = len(axis) + len(input_shape)
axis = [canonicalize_axis(a, out_ndim) for a in axis]
axis_set = set(axis)
shape_iter = iter(input_shape)
new_shape = [
1 if ax in axis else next(shape_iter) for ax in range(out_ndim)
1 if ax in axis_set else next(shape_iter) for ax in range(out_ndim)
]
return tuple(new_shape)

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