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Fix resize methods with kernel #554

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Feb 16, 2024
Merged

Fix resize methods with kernel #554

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034764d
Fix resize methods with kernel
jonatanklosko Feb 16, 2024
b1f35e1
Move more logic to defn
jonatanklosko Feb 16, 2024
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43 changes: 23 additions & 20 deletions lib/axon/layers.ex
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Original file line number Diff line number Diff line change
Expand Up @@ -2041,32 +2041,35 @@ defmodule Axon.Layers do
deftransformp resize_with_kernel(input, out_shape, spatial_axes, kernel_fun) do
for axis <- spatial_axes, reduce: input do
input ->
input_shape = Nx.shape(input)
input_size = elem(input_shape, axis)
output_size = elem(out_shape, axis)
resize_axis_with_kernel(input,
axis: axis,
output_size: elem(out_shape, axis),
kernel_fun: kernel_fun
)
end
end

inv_scale = input_size / output_size
kernel_scale = Nx.max(1, inv_scale)
defnp resize_axis_with_kernel(input, opts) do
axis = opts[:axis]
output_size = opts[:output_size]
kernel_fun = opts[:kernel_fun]

sample_f =
Nx.add(Nx.iota({1, output_size}), 0.5) |> Nx.multiply(Nx.subtract(inv_scale, 0.5))
input_size = Nx.axis_size(input, axis)

x = Nx.abs(Nx.subtract(sample_f, Nx.iota({input_size, 1}))) |> Nx.divide(kernel_scale)
weights = kernel_fun.(x)
inv_scale = input_size / output_size
kernel_scale = max(1, inv_scale)

weights_sum = Nx.sum(weights, axes: [0], keep_axes: true)
sample_f = (Nx.iota({1, output_size}) + 0.5) * inv_scale - 0.5
x = Nx.abs(sample_f - Nx.iota({input_size, 1})) / kernel_scale
weights = kernel_fun.(x)

weights =
Nx.select(
Nx.greater(Nx.abs(weights), 1000 * @f32_eps),
safe_divide(weights, weights_sum),
0
)
weights_sum = Nx.sum(weights, axes: [0], keep_axes: true)

input = Nx.dot(input, [axis], weights, [0])
# The transformed axis is moved to the end, so we transpose back
reorder_axis(input, -1, axis)
end
weights = Nx.select(Nx.abs(weights) > 1000 * @f32_eps, safe_divide(weights, weights_sum), 0)

input = Nx.dot(input, [axis], weights, [0])
# The transformed axis is moved to the end, so we transpose back
reorder_axis(input, -1, axis)
end

defnp fill_linear_kernel(x) do
Expand Down
65 changes: 65 additions & 0 deletions test/axon/layers_test.exs
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Original file line number Diff line number Diff line change
Expand Up @@ -944,6 +944,71 @@ defmodule Axon.LayersTest do
Axon.Layers.resize(inp)
end
end

# Adapted from NxImage
test "methods" do
# Reference values computed in jax

image = Nx.iota({1, 2, 2, 3}, type: :f32)

assert_equal(
Axon.Layers.resize(image, size: {3, 3}, method: :nearest),
Nx.tensor([
[
[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0], [3.0, 4.0, 5.0]],
[[6.0, 7.0, 8.0], [9.0, 10.0, 11.0], [9.0, 10.0, 11.0]],
[[6.0, 7.0, 8.0], [9.0, 10.0, 11.0], [9.0, 10.0, 11.0]]
]
])
)

assert_equal(
Axon.Layers.resize(image, size: {3, 3}, method: :bilinear),
Nx.tensor([
[
[[0.0, 1.0, 2.0], [1.5, 2.5, 3.5], [3.0, 4.0, 5.0]],
[[3.0, 4.0, 5.0], [4.5, 5.5, 6.5], [6.0, 7.0, 8.0]],
[[6.0, 7.0, 8.0], [7.5, 8.5, 9.5], [9.0, 10.0, 11.0]]
]
])
)

assert_all_close(
Axon.Layers.resize(image, size: {3, 3}, method: :bicubic),
Nx.tensor([
[
[[-0.5921, 0.4079, 1.4079], [1.1053, 2.1053, 3.1053], [2.8026, 3.8026, 4.8026]],
[[2.8026, 3.8026, 4.8026], [4.5, 5.5, 6.5], [6.1974, 7.1974, 8.1974]],
[[6.1974, 7.1974, 8.1974], [7.8947, 8.8947, 9.8947], [9.5921, 10.5921, 11.5921]]
]
]),
atol: 1.0e-4
)

assert_all_close(
Axon.Layers.resize(image, size: {3, 3}, method: :lanczos3),
Nx.tensor([
[
[[-1.1173, -0.1173, 0.8827], [0.7551, 1.7551, 2.7551], [2.6276, 3.6276, 4.6276]],
[[2.6276, 3.6276, 4.6276], [4.5, 5.5, 6.5], [6.3724, 7.3724, 8.3724]],
[[6.3724, 7.3724, 8.3724], [8.2449, 9.2449, 10.2449], [10.1173, 11.1173, 12.1173]]
]
]),
atol: 1.0e-4
)

assert_all_close(
Axon.Layers.resize(image, size: {3, 3}, method: :lanczos5),
Nx.tensor([
[
[[-1.3525, -0.3525, 0.6475], [0.5984, 1.5984, 2.5984], [2.5492, 3.5492, 4.5492]],
[[2.5492, 3.5492, 4.5492], [4.5, 5.5, 6.5], [6.4508, 7.4508, 8.4508]],
[[6.4508, 7.4508, 8.4508], [8.4016, 9.4016, 10.4016], [10.3525, 11.3525, 12.3525]]
]
]),
atol: 1.0e-4
)
end
end

describe "lstm_cell" do
Expand Down
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