einops

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We don't write:
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    y = x.transpose(0, 2, 3, 1)
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We write comprehensible code:
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    y = rearrange(x, 'b c h w -> b h w c')
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Also:
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    rearrange(ims, "b h w c -> h (b w) c").shape
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    rearrange(ims, "(b1 b2) h w c -> b1 b2 h w c ", b1=2).shape
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    reduce(ims, "b h w c -> h w c", "mean") # Average overbatch
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    reduce(ims, "b h w c -> h w", "min")

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z = einx.id("a (b c) -> (b a) c", x, b=2)             # Permute and (un)flatten axes
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z = einx.id("b (q + k) -> b q, b k", x, q=2)          # Split
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z = einx.id("b c, -> b (c + 1)", x, 42)               # Append number to each channel
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z = einx.sum("a [b]", x)                              # Sum-reduction along second axis
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z = einx.flip("... (g [c])", x, c=2)                  # Flip pairs of values along the last axis
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z = einx.mean("b [...] c", x)                         # Spatial mean-pooling
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z = einx.multiply("a..., b... -> (a b)...", x, y)     # Kronecker product
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z = einx.sum("b (s [ds])... c", x, ds=(2, 2))         # Sum-pooling with 2x2 kernel
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z = einx.add("a, b -> a b", x, y)                     # Outer sum
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z = einx.dot("a [b], [b] c -> a c", x, y)             # Matrix multiplication
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z = einx.get_at("b [h w] c, b i [2] -> b i c", x, y)  # Gather values at coordinates