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Minor doc improvements to attributes (#57)
* Minor doc improvements to attributes * Minor fixes
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hls4ml/utils/attribute_descriptions.py

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reuse_factor = (
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'The number of times each multiplier is used by controlling the amount of pipelining/unrolling. '
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'Lower number results in more parallelism and lower latency at the expense of the resources used.'
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'Reuse factor = 1 corresponds to all multiplications executed in parallel, and hence, the lowest possible latency.'
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)
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index = 'Internal node counter used for bookkeeping and variable/tensor naming.'
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trace = 'Enables saving of layer output (tracing).'
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trace = 'Enables saving of layer output (tracing) when using hls_model.predict(...) or hls_model.trace(...)'
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result_type = 'The datatype (precision) of the output tensor.'
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accum_type = 'The datatype (precision) used to store intermediate results of the computation within the layer.'
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'The number of outputs computed in parallel. Essentially the number of multiplications of input window with the '
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'convolution kernel occuring in parallel. '
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'Higher number results in more parallelism (lower latency and II) at the expense of resources used.'
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'Currently only supported in io_parallel.'
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)
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conv_implementation = (
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'"LineBuffer" implementation is preferred over "Encoded" for most use cases. '
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'This attribute only applies to io_stream.'
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)
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conv_implementation = '"LineBuffer" implementation is preferred over "Encoded" for most use cases.'
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# Recurrent-related attributes
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