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docs/src/man/backends.md

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@@ -152,7 +152,7 @@ For convenience, the construction above is also provided in a specialized macro
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@butensor
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```
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When using the `CuTENSORBackend()` and no allocator is specified, it will automatically select the
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When using the `cuTENSORBackend()` and no allocator is specified, it will automatically select the
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allocator `CUDAAllocator()`, which will create new temporaries as `CuArray` objects. However,
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`CUDAAllocator` has three type parameters which can be used to customize the behavior of the allocator
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with respect to temporaries, as well as input and output tensors.
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Users can also define their own allocators, to facilitate experimentation with new implementations.
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Here, no restriction is made on the type of the allocator, and any object can be passed as an allocator.
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The required implementated methods are [`tensoralloc`](@ref) and [`tensorfree!`](@ref).
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The required implemented methods are [`tensoralloc`](@ref) and [`tensorfree!`](@ref).

docs/src/man/indexnotation.md

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@@ -362,7 +362,7 @@ TensorOperations.IndexError
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```
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Once the expression is compiled, there can still be errors that will lead to runtime errors,
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the type of which depends ont he specific type of tensor (e.g. `DimensionMismatch` for
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the type of which depends on the specific type of tensor (e.g. `DimensionMismatch` for
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`AbstractArray` objects). Indeed, indices with the same label, either open indices on the
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two sides of the equation, or contracted indices, need to be compatible. For `AbstractArray`
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objects, this means they must have the same size. Other tensor types might have more complicated
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```
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Whenever an incompatible index structures is detected at runtime, the resulting error will
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originate deep within the implementation, at which point the error message will provide
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little information as to which specific tensors and which indices are producing the mismatch.
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When debugging, it might be useful to add the keyword argument `contractcheck = true` to
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the `@tensor` macro. Explicit checks using `checkcontractible` are then enabled that are run
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before any tensor operation is performed. When a mismatch is detected, these checks still
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originate deep within the implementation, at which point the error message will provide
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little information as to which specific tensors and which indices are producing the mismatch.
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When debugging, it might be useful to add the keyword argument `contractcheck = true` to
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the `@tensor` macro. Explicit checks using `checkcontractible` are then enabled that are run
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before any tensor operation is performed. When a mismatch is detected, these checks still
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have access to the label information and spawn a more informative error message.
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A different type of check is the `costcheck` keyword argument, which can be given the values
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```@docs
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@cutensor
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```
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```

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