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Refactoring move_constant_data in the scheduler. The use case currently
only work for LUT tensor, so simplifying the logic. In order to make it
work for other tensors one would also have to take into consideration
memory usage when building cascades and also the
use_fast_storage_for_feature_maps would be effected.
Change-Id: Ic8de53b65a2c17d34515002d7f184d0ab1830222
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
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- Additional overflow checks are performed when running under
Microsoft Windows compared to Linux. These checks happen when
converting from Python int to NumPy int/uint
- The problem is that the lut activation values are int32 type,
however they are defined as Python ints. If these are converted to
numpy.int32 it could result in an overflow error
- The fix is to convert these values to uint32 but keep the
operator's IFM tensor type the same (as this will allow them to be
interpreted correctly)
- Fixing this highlighted another problem where convert_to_lut
always calls create_lut_tensor() with an int8 datatype, whereas it
should be using the IFM datatype
Change-Id: I781a9d850f654267aa4a67754438607c4bb95685
Signed-off-by: Tim Hall <tim.hall@arm.com>
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- The issue is due to undefined behaviour when casting a NumPy float
to a NumPy unsigned integer which occurs in create_const_tensor()
- The fix is to make sure that the values are first cast to a Python
float
- In addition, the values datatype argument has been removed from
create_const_tensor() to stop the tensor and values datatypes getting
out of sync
Change-Id: I134b9be8c941b361929a5ae7db8cb35f2e9728f2
Signed-off-by: Tim Hall <tim.hall@arm.com>
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- Update copyright notices to use SPDX format and add OSS mail as contact.
- Update years on files where it had been missed.
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: I7e9715ea4e17b76252728c708e46df12ad67ab1f
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- Merged dev/scheduler at 83639f90e8c828f70de6e29142355a940224959b
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I0050529d4b42da93768c7264296434dd877fb5b4
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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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Added a static class TensorAddressMap that stores all Tensor addresses
based on their equivalence_id. Made the "address" field into a property
which getter and setter looks up/sets the tensor's address in
TensorAddressMap.
This makes the references to cpu_tensor/npu_tensor obsolete and they
have been removed.
Addition to scheduler: avoid SRAM spilling if an op has consumers in
other subgraphs.
Minor rework in LUTState; it will now assign a unique equivalence_id to
the SHRAM lut tensor to avoid issues with addressing. The equivalent
checks in LUTState now compares the values of the LUT instead of the the
equivalence_id.
Updated LUT unit tests accordingly.
Signed-off-by: Jacob Bohlin <jacob.bohlin@arm.com>
Change-Id: I41de5a8a4e5f07b77d6544d8d4034b754993e503
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Removed CLI-option permanent-storage
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I03e03205a183bd538292a73a07b095546fa3d95a
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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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