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- Adds missing operators and type conversion recording to DebugDB
Change-Id: If76b0b430bbe73ae1469024c3160ecf0eea26abe
Signed-off-by: wilisa01 <william.isaksson@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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- Added graph optimisation pass to support dilations greater than 2
in either dimension
- Removed supported operators restrictions
- Removed erroneous dilation on TRANSPOSE_CONV
- Updated unit tests and documentation
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: Ide302374b0d5eff25c20501383a63f6aa7625c52
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Change-Id: If871b0fe4dde2ec8f44c356fc6d5f4c1132fc142
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
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- Removed unused variable total_npu_weights to fix summary csv error
Change-Id: Id3c94166a787d2bb094ac6c6612fc866811515c2
Signed-off-by: wilisa01 <william.isaksson@arm.com>
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- Fixed the reporting of the input network operator to correctly
report the original operator type rather than the current one
- Fixed a divide by zero bug when calculating percentages
- Refactored the verbose-performance code so that console and csv
outputs use a single definition of the header and data
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: Ibd3fa99b65f0602dcdcff696f2d565ac13453306
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Fixed by adding an operation to copy the statically optimised
data to the subgraph output.
Change-Id: Ica757e37d5460237973444ffd39c7d2850f319e3
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
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The reference kernel for the MEAN operator has changed.
As a result, the mean implementation can be simplified
and the constraint for mean int8 can be removed.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I318e9b495eefea99e7ac4aea4b8c436c83753405
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- A bug was introduced by using the original_shape attribute that
causes CPU CONV2D ops to fail to run due to an incorrect weight
tensor shape
- This was due to the original_shape not being modified when a
transpose was performed on the weight tensor
- The fix was to transpose the original_shape just like the current
shape
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: Ied72316463d26c502cf931b9dd5784041c42ab66
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- CPU side always needs to work we the original tensor shape.
Due to a bypass memory optimization the IFM, produced by CPU,
was stored with the wrong shape in the optimized file.
- Store the original tensor shape so it can be correctly
written to the optimized file.
Change-Id: I666dbcb0acd806ad208c0f925a51dfc25421688b
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
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- The previous patch the always replaced ifm with ofm
introduced unnecessary avg pool ops for some cases.
That patch has been reverted and this is a new solution.
- Replace ifm with ofm for the following condition:
a) Ops that are dependent that the original ifm tensor
shape is not changed by the bypass memory op function.
b) When the memory op has different IFM and OFM rank.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I16a023e169ae64c5db46f6f88516a5e1ca7ed7ef
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This reverts commit 5060ff53f5ac2382e04a68d7772bd71a36f63845.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I8dd7e9ed8325fd2e8c17509fd9757292706f5ee7
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Always make sure the bias is a 1D tensor.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: Ic0cb85d4fb9d2e07b4d1b7ac6059bffa432e28a3
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- Due to a SPLIT op the following ADD op did get an IFM shape
that is bigger than its original shape but that is handled
by read_offset and read_shapes. The problem was that
the IFM was considered not be primary and an erroneously
swap was done.
- Make it even more clear when the swap is allowed.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I0aefa04234f66c935f269267ae8ed1d77da64c81
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Corrected offset calculation for operator Slice. All values
in tensor begin and tensor size must be used to calculate the
offset range in order to read the correct data.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: Ic463d8f72a2167f8129109b8dcf005f034cce6ed
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- Remove very long live ranges that are standing out compared to
its neighbors. This can be seen on large networks with complex
structure. If they are chosen instead of shorter live ranges,
it will be difficult for the HillClimb Allocator to find a perfect
fit in the final allocation.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I6cf23adfdc06c1e93e12e9cf816453d940ff31f7
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- Refactored erroneously if statement that allowed illegal
swapping between ifm1 and ifm2 for elementwise operators.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: Iec571f710824432edac9104d960f199f33a1b241
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- The algorithm for trying out different stripes in order
to optimize a sub schedule/cascade, have a problem that it
can split the initial cascade into several smaller cascades.
The problem with this is that it will increase IFM/OFM DRAM
bandwith and performance will drop.
- Changed the stripe algorithm to prefer long cascades.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I4f38b381597b7094819e9dd463aa1876e4e6bc62
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- The cascade builder is using the ifm_ifm2_correct_order
function in order to decide if the operator is cascadable or not.
The problem is that this function expects a full shape or no shape
and the cascade builder did not provide that, so the operator was
reported to be non cascadable.
- The fix is to provide a full 4D shape, also refactoring
ifm_ifm2_correct_order to use 4D shape to avoid confusion
in the future.
- Refactoring code so that the scheduler can perform a
correct ifm and ifm2 swap.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I9a86c4690612f332afa428456a07e67698852495
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Change code in cascade builder to instead
use common functionality in live range.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I7bbd7ea3d1e7e085813e9d93256a54e6bab2267b
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- Vela failed to compile networks with multiple subgraphs because
only cascaded passes in the root subgraph were used when
extracting the live ranges. The fix is to extract the subgraph
range live on Ops that have connected subgraphs.
- The tf_writer did not handle multiple subgraphs in a correct way
resulting in corrupt buffer data in the optimized tflite file. The buffer
index must be unique for every tensor.
-Added support to handle multiple subgraphs for the OfflineMemoryAllocation
meta data. The change will not change behavior for single graphs.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I2328dfc1f07e2e4faf43a75423ea95423096ffa3
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- The op contained supported operator checks for both the stride being
in the range 1 to 3, and being equal to 2. Whilst both are correct, only
the later is needed
- Removed the stride in the range 1 to 3 check for TRANSPOSE_CONV
- Regenerated the documentation
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I9789cdbd3ed65ce310f1529036abbac62296d2ca
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In order to be able to add your SSH key there must
exist a valid email address in your account.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I60c70e63ea6ad015d5a10d8e9efec6d61d56cbad
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If IFM operator shape is rewritten so that batching
is greater than one for fully connect, the OFM batch
must also be calculated. This change will fix output diffs
for networks that have fully connect OFM with rank greater
than 2.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I5009edc647a1449a02c8116b45808c1c68beffe6
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- Removed half pixel centers constraint for resize nearest neightbor.
- Supported scale 2x, 4x and 8x.
- Removed test_constraint_resize_half_pixel_centers
- Regenerated SUPPORTED_OPS.md
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: Ic3e02e9c2b2034d537c9a9841b8fb4ee433c96dc
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Fixed output diff when cascading elementwise operators with
reversed operand order.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: Iac2e28cfb53037b929459af213f4fa7715b3e6de
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The problem was that the updated conditions for elementwise
cascading was to permissive after the RescaleAdd removal.
Conditions for elementwise updated and transpose convolution
removed from cascading since it does have issues.
Change-Id: I0151256c4e3905fad39152941eec44bc76035d30
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
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The palette variable located on the stack was not properly
initialized and could potentially overwrite the stack memory
when palette size was increased to 2.
Make sure lut value is initialized.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I9fecfe218dc39c0157d1af015e725d1e4becf2f0
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Removed RescaleAdd and RescaleMul operators in favour of
Operation.explicit_scale and removed Operation.rescale.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: Idccd8851731d4bb8d4e84970e0fd6b409d7d4e45
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- The issue is due to the numpy version needed when installing on
aarch64 with Python 3.8 and TensorFlow
- The fix is to use the python_version variable when specifing the
numpy version
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I6134b6dbccefc3be0b87feb17e3176b7f42641b3
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- Updated to TensorFlow 2.10 and FlatBuffers 2.0.7
- Changed absolute to relative imports in the auto-generated code
- Updated Vela's TFLite writer to support FlatBuffer builder's internal
number of elements count
- Removed use of deprecated numElems argument to FlatBuffer builder's
EndVector()
Signed-off-by: erik.andersson@arm.com <erik.andersson@arm.com>
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: If447778134db81ae0ac374c7397e1140082372fd
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Added unit tests for scaling including saturated multiplier test.
Change-Id: I87bb3a4bed8f62f5ef5cf3851b97f09ce42bf2b6
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
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Cleaned up bias tensor use in graph optimiser for Mean operator.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: Ibcbfa010a4de67d97181df664b420168d6883d1e
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- In order to solve output diffs, the Reshape op was pushed
to the CPU. The problem was that the Mean op ifm shape
was replaced by the Reshape op ifm shape.
- This limitation is now removed. Changed implementation
how memory only ops are bypassed. Always replace the memory
only op ifm tensor with its ofm tensor. By doing this
the ifm tensor for the operator that is after the memory only
op is never changed.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: Ibcdebf33fd9b7a37f90984a129500b5dac52e5ea
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Fixed bug when height is greater than max kernel height. The shape
of the weight must match the ifm shape.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I901a8af2edd5858bb15d53d85ef8e2389049ada7
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Make the address_for_coordinate function a bit easier to read
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: I854e1643a39108edc8b1de95198d30a1891fdfd1
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The test failed since the tanh had batch size > 1.
Added checks for batch size for all supported operators.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: I3570352740c40eb96bd9db965dfa3c91c81ff2ad
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Added LeakyRelu to supported activation ops.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: Icca27730946d02ec16159f988782567be716b594
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Setting bias tensor dtype to DataType.int32 solves rounding issues for
RB HPC int16.
Removing the input data type check also solves the issue of resize
nearest neighbor int16 ops incorrectly getting placed on the CPU.
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: Iee352bcb78e581c0cde3c203dfbe866f1f6fae18
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- Added support for Resize Bilinear with half pixel centers for int8 and
uint8.
- Utilizes the new "TILE" padding mode.
- Utilizes ofm stride multipliers and modified tile base offsets to
write OFMs interleaved.
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: I37fa77c022a368f05fda0ead75d8696c9205f833
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The issue was that the AveragePool in these test cases were
translated to DepthwiseConv2DBias and int16 convolutions
always runs with reduced scale. Fixed so that reduced scale
is not used in this case.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: Ice956eabbb37c8aa1991464870006971c6ecec43
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Fixed PReLU optimisation to LeakyReLU with negative alpha.
Added optimisation of LeakyReLU to ReLU when alpha is zero.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: I5e66f79b29908fffd95b6115799021138ebb401a
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Allow sparse writing of OFM by multiplying H/W/C of the OFM with the
values of ofm_stride_multiplier
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: I65d742ad36ad3154e9914cdd22e2da928ad1f095
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Fixed LeakyReLU regressions for int16 due to scaling introduced
for handling negative alpha.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: I84a494fedf54bd4b47c4632645ded7d6cda445f8
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Removed duplicate code and moved constraint to
the correct file.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I2da3c5b88e1af351751c481217b8183b5948f0f8
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Remove Pipfile support due to lack of testing and maintenance.
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: I93786cdbf22bfa2130601291d23cead177bd8f81
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Added support for int16 LeakyRelu for negative alpha and alpha
greater than one.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: I7f522ebfe014786d0a1d96172e75c7d9bdd76921
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Implement new padding mode which pads two edges of the IFM with the
current values of those edges
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: I8523e0cabdac80b48710703859003e33050cc150
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Changed acc type from int16 to int32. This will solve
saturation problems and the constraint added in
commit "MLBEDSW-5029: Output diff for Mean op"
can be removed.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I05ec8835b43313b1a264d61a2b147fa62da123fe
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- Ethos-U65-512 requires the input to REDUCE_SUM to use NHWC format
- Updated the graph optimiser format check to cover this condition
- Added a exception check to the backend of the compiler to verify that
this condition is not been violated by the external api or Vela internals
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I2f1fabcbd264daf77d5822349d855a3a32b12c64
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