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docs: update note
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lib/node_modules/@stdlib/blas/ext/sum/README.md

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## Notes
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- Setting the `keepdims` option to `true` can be useful when wanting to ensure that the output [ndarray][@stdlib/ndarray/ctor] is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with ndarrays having the same shape as the input [ndarray][@stdlib/ndarray/ctor].
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- The output data type [policy][@stdlib/ndarray/output-dtype-policies] only applies to the main function and specifies that, by default, the function must return an [ndarray][@stdlib/ndarray/ctor] having the same [data type][@stdlib/ndarray/dtypes] as the input [ndarray][@stdlib/ndarray/ctor]. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] is allowed to have any [data type][@stdlib/ndarray/dtypes].
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- The output data type [policy][@stdlib/ndarray/output-dtype-policies] only applies to the main function and specifies that, by default, in order to avoid issues arising from integer overflow, the function must return an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] amenable to accumulation. This means that, for integer data types having small value ranges (e.g., `int8`, `uint8`, etc), the main function returns an [ndarray][@stdlib/ndarray/ctor] having at least a 32-bit integer data type. By default, if an input [ndarray][@stdlib/ndarray/ctor] has a floating-point data type, the main function returns an [ndarray][@stdlib/ndarray/ctor] having the same data type. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] is allowed to have any [data type][@stdlib/ndarray/dtypes].
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- When summing a large number of lower precision floating-point numbers (e.g., as found in an [ndarray][@stdlib/ndarray/ctor] having a `'float32'` data type), the accumulated numerical error can become significant. In such cases, casting the input [ndarray][@stdlib/ndarray/ctor] to a higher precision floating-point data type, such as `'float64'`, prior to computation is advisable.
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</section>

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