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PAD input tensor shape plus paddings must equal output tensor shape.
Change-Id: Icc5dea9bf6a8f6e1c8402f4d9af4d9796e8ef1aa
Signed-off-by: Johan Gunnarsson <johan.gunnarsson@arm.com>
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- checks that cmd1 payloads are legal in
register_command_stream_generator,
- adds unit tests
Change-Id: I2bc23147f60fe090c71703f08d9cbaa279fac86e
Signed-off-by: William Isaksson <william.isaksson@arm.com>
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- Added graph optimiser function to convert convolution groups into
a split followed by separate convolutions and then a concat
- Added semantic check for convolution groups
- Added unit tests for convolution groups semantic checks
- Fixed a minor typing issue with test_constraint_stride_range
Change-Id: I78ade408aa23469a79c9f517c4751da8619b77a9
Signed-off-by: Tim Hall <tim.hall@arm.com>
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- Add support for batch and depth channels when shape is 1
- Refactor reshaping in convert_mean_to_depthwise_conv
Signed-off-by: Alexander Hansson <Alexander.Hansson@arm.com>
Change-Id: If663395934ab58c76ba92b6ebaaf484a389ae699
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* Fix bug in register_command_stream_generator where certain
high-level command streams resulted in missing DMA_WAIT commands
* Add unit-tests for DMA_WAIT and KERNEL_WAIT commands
Signed-off-by: Alexander Hansson <Alexander.Hansson@arm.com>
Change-Id: Iabb3ea3e95fa1ef933c50356d047b6b3f5aeafe3
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* Improve check_cmd functions to return position of the checked commands.
* Update existing unit-tests to validate ordering of commands.
Signed-off-by: Alexander Hansson <Alexander.Hansson@arm.com>
Change-Id: I492487d768e1e80f6ea366e29f2f99441e4f9797
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* Convert Means with large IFMs to several DeptwiseConv2DBias and Add
operations.
* Update tflite supported operator check with new height and width
constraints.
* Update unit-tests to verify supported operator changes.
* Fix output-diff for 2D IFMs (MLBEDSW-7772)
Signed-off-by: Alexander Hansson <Alexander.Hansson@arm.com>
Change-Id: Ifae6fb1cdac475ae7dac5116c5f13631ff82108a
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- A crash occurred due to NoneType subscriptable error when
rewriting a Slice op. The reason was that the Size tensor did
not contain any data.
- Added constraint pushing the Slice operator to the CPU if
begin or size tensor are empty.
- Added test to supported operators
- Updated SUPPORTED_OPS.md
Change-Id: Ide204cae24e5871f0e6ae1fdc98ac68d0ce4d3ae
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
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* Fix bug that caused filter padding to not be added proportionally
compared to the hardware padding added to IFM.
* Update needed_total_padding function that calculates hardware padding
to also account for the cases in which IFM width is not divisible by
the stride width.
* Update supported ops constraint on strides for conv2d to mark ops with
stride width > 3 and IFM width that is not divisible by the
optimization resize factor as not supported.
* Update unit tests that verify correct functionality when checking
whether ops are supported or not.
Change-Id: I62f14cca890b779ca787a9603fa37c873ad522f8
Signed-off-by: Raul Farkas <raul.farkas@arm.com>
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- Added RSQRT int8 support, implemented as LUT.
- Added test to supported operators
- Updated SUPPORTED_OPS.md
Change-Id: I34904772e044be8d22a6dfe426edf85358a205b7
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
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* Fix import order in test_build.py
* Fix setup_tools_scm dependency version. Previously the version was
restricted to < 6, creating a version restriction on Setuptools
library too.
Because an older version of Setuptools was used, running
test_build.py::test_build_correct_readme_links would generate a
UNKNOWN.egg-info directory in the src directory instead of a
ethos_u_vela.egg-info directory.
Change-Id: I113ca25b23b39d43fa288e6eda16377f4f5b4143
Signed-off-by: Raul Farkas <raul.farkas@arm.com>
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* Implement a general optimization solution for strided CONV2D that
supports a stride_w with no upper bound.
* Implement filter zero padding to allow for optimization in those cases
in which the filter width is not divisible by the stride width.
E.g.: Filter width = 8, stride width = 3 ->
Filter width = 8 + 1 (0 padding) = 9, stride width = 3
* Implement partial optimization to reduce the stride to hw supported
strides (i.e. 2 and 3) when optimizing to reach a stride = 1 is not
possible due to the IFM width not being divisible by the stride width.
* Implement optimization for when SAME padding is used. If the pre-opt
and post-opt padding do not match, add zero padding to the filter so
that the post-opt IFM padding matches.
Change-Id: Ia66b0d107281fa9993f6bf4d0c26627ee743253b
Signed-off-by: Raul Farkas <raul.farkas@arm.com>
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We now read operator code version, store it in operator and write it out
to optimized file.
Signed-off-by: wilisa01 <william.isaksson@arm.com>
Change-Id: Idba672531d2e2a0203a85d3ffca9cf65ace85b47
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* Add test to verify that the metadata produced in the PKG-INFO file of
the sdist contains the correctly formatted links extracted from
README.md
Change-Id: I300094470fd115b1143aa8c663837e8a77428f24
Signed-off-by: Raul Farkas <raul.farkas@arm.com>
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Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: Iaeb8f2cea0d3b576a6b138e64a882c701ac88ccb
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- Latest reference has changed implementation for the Mean op
and now only contain one variant.
- Updated Vela implementation to match reference. The full sum
is first calculated and then divided by the numbers of elements.
- Removed the avg pool variant and test case.
- Updated SUPPORTED_OPS.md
Change-Id: I4275e36e3697fa837f119f2cefd7c0ff94231605
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
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Added int8 and int16 UNIDIRECTIONAL_SEQUENCE_LSTM support.
The implementation does not include support for:
* CIFG
* Peephole
* Projection
* Normalisation
This change also:
* Removed unused Op.BlockLSTM operation type.
* Removed the only one consumer limitation on putting the SplitSliceRead
on the tensor consumer(s), if all consumers fullfills the requirements
* Added Op.VariableTensorWrite as a Operation.memory_function to make
sure writes to variable tensors:
* Always use linear mode
* Are not moved to fast scratch
* Are not fused with other elementwise operation tensor ranges
Change-Id: Ief831738924ac3d1f2ba6d41f10bd6dc969911f3
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
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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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Since test works by creating an overflow, sets NumPy to ignore overflow for this test case
Change-Id: I74d03e8d73455295168352542dcb844283d54d33
Signed-off-by: wilisa01 <william.isaksson@arm.com>
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Reinstate constraint for stride height to (1,3) instead of (1,4) for
Conv2D and update unit tests.
Change-Id: I17389ee040eeff0cea08279cab1c038e951569ea
Signed-off-by: Raul Farkas <raul.farkas@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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* Extend stride range from (1,3) to (1,4)
* Add stride 4 support when optimising CONV_2D
* Add some tests for various strides
Change-Id: Iddaeb42c4a6e02695ecdd3740bc8b9dd59a7eb3c
Signed-off-by: Raul Farkas <raul.farkas@arm.com>
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- An assert in Vela is triggered when the number of splits does
not evenly divide the input.shape[axis] value and the split offsets
are calculated wrongly.
- The fix is to add the same constraints as in the reference kernel
and only run the Split op on the NPU when the criterias are fulfilled.
- Modified test to reflect the new constraints
- Updated SUPPORTED_OPS.md
Change-Id: I4103ff4a3fdf9a813f5fcb7f51081b859e611100
Signed-off-by: Johan Alfven <johan.alfven@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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- Only 1D bias shape is supported
- Modified test to reflect the constraint
- Update SUPPORTED_OPS.md
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I00ae4b229d5f89512cb94f87f276af61cc66a6fd
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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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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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- 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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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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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 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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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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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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Fixed three test cases causing output diff compared to
the reference kernel for the Mean operator.
- If there is a possibility that the accumulator could saturate
the Mean op must run CPU
- Use correct rounding for the bias term
- If a Reshape op is followed by a Mean op, push the Reshape op
to the CPU since this cannot be handled by the NPU
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: I734465730372105821a5e2f73a6a125b9eb7d7f4
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- Changed ResizeBilinear to support ResizeNearestNeighbor as well for
1x1 IFM, IFM equal OFM, and non-align corners
- Added support for ResizeNearestNeighbor with align corners by
converting to a DepthwiseConv
- Updated supported operator unit tests
- Added is_resize() helper function and some associated refactoring
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: Id5bdf2a25e8aa6a4f28b7236250abf768141ce37
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- Fixed align corners support when converting in to upscale and average
pool. The problem was due to the wrong ratio ifm to ofm size, causing an
scaling factor that was not 2x/4x/8x. Works for uint8, int8 and int16.
- Fixed checking of align corners in supported operators check
- Added additional supported operators check for the size tensor
- Updated and added more supported operators unit tests
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: Idb78fa9e76ede2c37e8ac6cb1c322154bd156898
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*Quantise op becomes constant if input is known at compile time
*Quantised values calculated if input of op is const and float
*Const inputs to quant op that are int are requantized
Change-Id: Ic94a72a392af709fe6a640d7dacbb5dc2334f16f
Signed-off-by: Ayaan Masood <Ayaan.Masood@arm.com>
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- For allocations that have a hard memory limit the Hill Climb allocator
should be given more attempts to find a solution that would fit
- The fix is to use a memory limit when there is a hard constraint, and
a minimum iteration count, reset on every improvement, when there is a soft
constraint
- Added maximum number iterations CLI option
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I19ff53a0b68412de280263626778a3102cbe52fa
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Removing constraint for negative alpha value in ReLu
for int8 and uint8.
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Change-Id: Id7a3a30bf5d1f0a591f990bd04cd0dbbad5819c6
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*Added generic function which checks if underlying shape of
FullyConnected operation is 2D and performs shape reduction
*Fully connected operation >2 dimensions now run on NPU if the above
case is satisfied
*constraint_fc_output_2d and rewrite_fully_connected_input refactored
*Added unit test to confirm this functionality
Signed-off-by: Ayaan Masood <Ayaan.Masood@arm.com>
Change-Id: I0e29c767e5b84841eb53bbc44464b36a454f7b38
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Update version of Black to 22.3.0 due to updated dependencies.
Updates to fix reported issues due to new version.
Signed-off-by: Jonas Ohlsson <jonas.ohlsson@arm.com>
Change-Id: I60056aae452093ce8dcea1f499ecced22b25eef1
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* 1D optimised block_config was incorrectly beign set to the ArchitectureBlockConfig in try_block_config()
* Write external API test for the reduced block height case (on H256)
Signed-off-by: James Ward <james.ward@arm.com>
Change-Id: I9ced7eb31b23730e4423aabbaf769bc72fac8fc9
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Previously we did not check if half_pixel_centers
was set. Since we do not support it, these cases
should not run on the NPU.
Signed-off-by: erik.andersson@arm.com <erik.andersson@arm.com>
Change-Id: I9d2675f760424d5cfb67e5d581dd1861ad165b85
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* fix indices for tflite mapping of EXP operator
* fix indices for tflite mapping of Transpose operator
* ensure read offset after slice is aligned to 16 bytes for NHCWB16 or force linear format
* add unit test to ensure mapping of indices is consistent across TFLite, TOSA and NNG
Signed-off-by: James Ward <james.ward@arm.com>
Change-Id: I17b6e44bc06853325d5eea62a558418ee1ebefe8
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Memory only operators such as Reshape, Squeeze and ExpandDims are
removed in the graph optimiser step.
- Added semantic check that memory only operators have same
quantisation parameters on ifm/ofm.
- Added support for the ExpandDims operator.
- Addition and cleanup of related unit tests.
- Removed TOSA from the generated SUPPORTED_OPS.md documentation.
Signed-off-by: Jonas Ohlsson <jonas.ohlsson@arm.com>
Change-Id: If848d8afc58c18806e10997ed94e4dae83f30879
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Update to handle the case when the Squeeze Op ifm/ofm are the
subgraph ifm/ofm, to facilitate the removal of the Squeeze Op.
Adding NOP to maintain the original tensors.
Updated pytests for squeeze operator.
Signed-off-by: Jonas Ohlsson <jonas.ohlsson@arm.com>
Change-Id: I623cae05e696fb16ccf29dedc42fd822601e9fd9
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- Changed Ethos-65 AXI port address width from 48 to 40-bits
- Fixed the use of arena_cache_size in mem_type_size() to cover the
arena as well as the cache memory area
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I826462a0cbd0c061cccbc7c83dde446778a2b1ca
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Refactor supported operators by breaking out model semantics
into its own class. Model semantics checked right after model
read.
Signed-off-by: Jonas Ohlsson <jonas.ohlsson@arm.com>
Change-Id: If442b189efcd91dda01af60b2b3adedfacdf2fad
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Remove quant_values attribute from Tensor class.
It only needs a single values attribute, holding either
quantized or unquantized values as appropriate.
Change-Id: Ie96f80ac58061b6077e0f7048dc60209fdfbcafa
Signed-off-by: James Peet <james.peet@arm.com>
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