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⚡️ Speed up function compute_conv_output_shape by 94% #160

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⚡️ Speed up function compute_conv_output_shape by 94% #160

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34 changes: 15 additions & 19 deletions keras/src/ops/operation_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -197,25 +197,18 @@ def compute_conv_output_shape(
f"`dilation_rate={dilation_rate}` and "
f"input of shape {input_shape}."
)
none_dims = []
spatial_shape = np.array(spatial_shape)
for i in range(len(spatial_shape)):
if spatial_shape[i] is None:
# Set `None` shape to a manual value so that we can run numpy
# computation on `spatial_shape`.
spatial_shape[i] = -1
none_dims.append(i)
none_dims = [i for i, s in enumerate(spatial_shape) if s is None]
spatial_calc = tuple(-1 if s is None else s for s in spatial_shape)

kernel_spatial_shape = np.array(kernel_shape[:-2])
dilation_rate = np.array(dilation_rate)
kernel_spatial_shape = kernel_shape[:-2]
if padding == "valid":
output_spatial_shape = (
np.floor(
(spatial_shape - dilation_rate * (kernel_spatial_shape - 1) - 1)
/ strides
)
+ 1
)
output_spatial_shape = [
int(np.floor(
(spatial_calc[i] - dilation_rate[i] * (kernel_spatial_shape[i] - 1) - 1)
/ strides[i] + 1
)) if spatial_calc[i] != -1 else -1
for i in range(len(spatial_shape))
]
for i in range(len(output_spatial_shape)):
if i not in none_dims and output_spatial_shape[i] < 0:
raise ValueError(
Expand All @@ -225,13 +218,16 @@ def compute_conv_output_shape(
f"`dilation_rate={dilation_rate}`."
)
elif padding == "same" or padding == "causal":
output_spatial_shape = np.floor((spatial_shape - 1) / strides) + 1
output_spatial_shape = [
int(np.floor((spatial_calc[i] - 1) / strides[i]) + 1)
if spatial_calc[i] != -1 else -1
for i in range(len(spatial_shape))
]
else:
raise ValueError(
"`padding` must be either `'valid'` or `'same'`. Received "
f"{padding}."
)
output_spatial_shape = [int(i) for i in output_spatial_shape]
for i in none_dims:
output_spatial_shape[i] = None
output_spatial_shape = tuple(output_spatial_shape)
Expand Down