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When encountering a sparse string buffer, Vela fails
both due to missing a mapping for a Numpy string type
and also for not being able to read sparse buffers.
The failing line is attempting to reshape a [100]
buffer into a [3, 5] tensor which does not work due
to Vela treating the buffer as non-sparse.
The solution here is to simply not do the reshape
for string buffers (which all appear to be sparse)
since it is not something that will be supported in
the future anyway.
The related operator can then be pushed to the CPU
as expected.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: Iea0af6cd60a691f975209014b6aa098dde8d6a4b
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- op.type is now an enum instead of a string
- Removed unused operator codes
- Refactored some attributes like npu_block_type, fused_activation_function
- Refactored operator index calculation
- Refactored a number of operator sets
Change-Id: I641f65ee375794b7aec42abc0664251ae37d78e8
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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Includes a number of changes:
* Handle non-existing optional inputs
* Handle disabled optional inputs (-1 indexed)
* Added unit tests for parsing operators
* Add bias tensor to the different Convolutions + FullyConnected if
it's missing.
Signed-off-by: Jacob Bohlin <jacob.bohlin@arm.com>
Change-Id: Ib88d2b610314b1c886fc0aef4f9da87430ce6ae5
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- Support for more than one 256-byte LUT in SHRAM
- No DMA is performed for a LUT that is already located in SHRAM
- Added MemArea.Shram, used for LUT, to avoid false address collision
asserts during SRAM tensor allocation
- Added read access to LUT in memory access calculation
Change-Id: If4d1eded5ed029d253f4f5efb2d80495fc3eac99
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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Moved len1_array_to_scalar from a nested function to a staticmethod
of TFLiteSubgraph.
Change-Id: I182f0b70f03070855c1a4478d26644892c1ebb15
Signed-off-by: Diego Russo <diego.russo@arm.com>
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