Age | Commit message (Collapse) | Author |
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- Fixed a bug due to ResizeBilinear modifying the attributes of a
shared IFM
- The ifm_resampling_mode is now an attribute of an operator rather
than a tensor
- Changed all calls to try_block_config() to use the attribute rather
than recalculating it in multiple places
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I4641e9cd6b049bd4186776d98e3e751c5e5bcc06
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Add mypy to pre-commit and clean up all reported errors.
Signed-off-by: Jonas Ohlsson <jonas.ohlsson@arm.com>
Change-Id: If7dc869f5fecdb0e2db40f14e7d9db21aa33df71
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Update the flatbuffers generated code to comply with TensorFlow 2.7
Signed-off-by: Rickard Bolin <rickard.bolin@arm.com>
Change-Id: Iff29b05a6e145245861329b4ff9fc9fbd968da53
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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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Added support for Identity operation.
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: If00b30528932f7531807ce3914d6c1875ab72fa4
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Added support for elementwise operations:
-Support for up to Rank == 6
-Support for Batch > 1 for Rank == 4
-For binary elementwise ops this includes handling
of broadcasting in dimensions above H-dimension
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I73850bbfb288077a99bd2ceecbf989172016da24
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Added support to map TABLE operator to LUT.
Limitations:
-Only supported for int8
-TABLE input must be constant
This also adds the support for TFLite legalisation of
Tanh/Sigmoid (int8/uint8).
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I1a95f61fb02fdd42c4a690494418cc0765c8b275
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Added support for TOSA PAD operator
in line with legacy support
Limitations:
-Rank <= 4
-N = 1 if Rank = 4 for ifms/ofm
-only padding in W and H dimensions
-bool_t not supported
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I511608202b4c9bf6d86285b559c517fb41741fdf
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Added support for ADD, SUB and MUL
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I52acdc126b16e2cf4096bcf7a77023ea7d204998
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This is mainly to add support for depthwise conv2d
with dephmultiplier = 1.
(But there are no testcases suited, all I have sourced
has depth_multiplier set to 2, which is not supported.)
-Added support for depthwise conv2d.
-Added support for removing Transpose of constant data
-Added support for removing reshape
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I143e6246becfa78fd9f7510af0bf0d6b3fbbf2c7
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This commit updates the flatbuffers generated code
to comply with TensorFlow 2.5, as well as stripping
away some legacy code.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: I01fe47ec2bde6e78fdde21ee1bc0a71f560c53ae
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Mapping to internal input indexing has been added to
tflite_reader.py and tosa_reader.py.
And the other way around in tflite_writer.py.
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I4d8596e747cfa7c4203884c4e785eb1977e2bcc1
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Added basic TOSA support, enabling Vela to
read and compile a .tosa file corresponding to
CONV2D + Rescale + Clamp, and writing it to an
optimized .tflite file.
The optimized .tflite file, will in this case, hold
a commandstream where the Rescale and Clamp has been
fused into the CONV2D.
The optimized tflite file is not output from Vela.
-Added support to read .tosa file into Vela
internal structure.
- Added tosa_reader.py, tosa_mapper.py and
helper files stored under tosa/
- Support for this limited to ~10 ops
-Added reader_util.py for functions common
for TOSA and TFLite
-Added tosa_graph_optimiser.py
-Added support to fuse Rescale into convolution
-Modified handling for padding
-Added support to fuse Clamp to previous op
-Added graph_optimiser_util.py
-Moved functions common for TOSA/TFLite graph
optimization to this file.
-Renamed graph_optimiser.py to tflite_graph_optmiser.py
-Added separate tosa_supported_operators.py
-Added supported_operator_util.py
-For functions in common for TOSA/TFLite
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: Ic3c540504ec8c5eb4771397fdc6882050ecf33ab
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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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- Added full support for PAD operator
- Hardware padding is still used whenever possible
- Bug fix Pad followed by max pool if IFM contains negative values
Change-Id: Ifc64d1943737d94466f5e2821009dab12a49a965
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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This commit adds support for the MEAN operator,
with some caveats.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: I165cb26cb5aefd68e70d2cfc68291ccf7b778921
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PAD followed by max/average pool is run on NPU if NPU
padding can be used. Average pool is converted to depthwise.
Change-Id: Icc3652e6d9ecff5ac3dc7d92080313d90c245404
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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Fixed pass through of LSTM operator.
Change-Id: I23140c69ab6cdc83f6bb8129256b4cc6a7c5ffac
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
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Removed SplitSliceRead from subgraph during
graph optimisation.
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I9315d4c2a6767828dd2b4e66823d73b10ebee99c
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Fix check for NHCWB16 for modifying FC input.
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: Ie50c32ca079afadd0af9b7b909820794ceee373c
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Updated tflite loader and mappings from tensorflow 2.3 to tensorflow 2.4
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I55884000ee139baf639bb0377008e0534f72fe94
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- Added checks for unsupported pad sizes in PAD operator
- Bug fix right pad/bottom pad calculation when replacing PAD operator
by hardware padding
Change-Id: Ib84be711277d987052f14352ab386e0e0b774987
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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Change-Id: If49abc31f093f1bd3393bee86f821fd35972086f
Signed-off-by: Diqing Zhong <diqing.zhong@arm.com>
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When FC input is fixed by changing ifm_shape,
avoid_NHCWB16 must be set to ifm.
-Fixed issue with ResizeBilinear
-Changed to post order for concat ops in graph optimisation
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: Ie0c6a86637c210c0833ae9b2f8e7c494c5d4f66e
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-Removed reshapes in the original graph
-Removed the addition of reshapes to the
optimized graph
-Reshapes with different ifm/ofm quantisation will remain
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I94862be53dac0d7434815e2aee5ca678228495f8
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Added RescaleAdd operation to avoid non-standard attribute
"rescale" for Add operation. Also changed ResizeBilinear
in the same way.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: I1d286f63890585c06b8a161df1ff77e3f844a4b9
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Replaces the PAD operator by hardware padding when possible.
Change-Id: I9dce0885e51a4a73715824d7368637222e39b2b3
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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This reverts commit df0a5905177f3a1b836076bc3f9f39b2e86f1794.
Reason for revert: <INSERT REASONING HERE>
Change-Id: I891c66fb29db9d25e942947e8d1c29a10610de51
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This reverts commit bf31d647dc5df47410ee577b12427ddf076d816b.
Reason for revert: <INSERT REASONING HERE>
Change-Id: I7b6c585b7658f94dbaa916c2b6bfe9fb463b8d37
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Add 4D shape class for op Ifm/ofm shapes
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: Ic0a98da9d2f9d085605e39a9ab5a26bad6e702a3
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Add ifm/ofm shapes to op
Changed to rely on these shapes
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I571535a1dcadc2bdb04a3c727a8e1c49703b174d
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Due to an issue with potential cyclical imports, especially when running
individual parts of vela standalone for example with pytest, the
specialised error functions are moved out of errors.py to their
respective locations.
The use of getattr over isinstance prevents the need to import the
tensor/operator class causing the cyclical import issue.
Signed-off-by: Michael McGeagh <michael.mcgeagh@arm.com>
Change-Id: If8cee4b1a2562660c6a47e1c7aeb5d7fd4dd1fca
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Use an Enum instead of a bytestring to specify VALID or SAME padding
Signed-off-by: Michael McGeagh <michael.mcgeagh@arm.com>
Change-Id: I4e87f8c32b3bfac176d822a68de061e85a558fce
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This commit corrects a number of type errors
reported by mypy and refactors some parts of
the code which are no longer necessary after
making adjustments to satisfy mypy.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: I16b880b228e57f2a92fb8936f53e94886e0f9f44
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Move operator generation code to common functions.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: I02e185fd793a96ae435fa7d235c9d1e97f388a03
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Minor fix in SPLITV tensor indexing for supported operators check.
Signed-off-by: Jacob Bohlin <jacob.bohlin@arm.com>
Change-Id: If8fa702bfbb25a4a7e5bdb136a19ef72eec7e1c2
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Added external API to generate register command streams.
Existing code generation has been refactored to make
use of this API.
Change-Id: Ibb4c2b167809869f16470b14da24f08a65c82b7b
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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All existing constraints have now been refactored using the new
framework.
Signed-off-by: Michael McGeagh <michael.mcgeagh@arm.com>
Change-Id: Ic9ba0d7040cb9f114b959a949bfdf777f86752c7
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- Normalise kernel availability by requiring all operators offer a kernel
describing how much data they consume from the source, per OFM element,
regardless of whether kernels are relevant to the operation.
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: Idbcff64879fc2eccf292b6208a7d2038eb388017
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This commit fixes a bug where a rewritten Unpack
operator is placed on the CPU and crashes Vela
during serialisation due to the type having
changed and there not being a mapping for the
modified op type.
The solution is to move the fixup_unpack_output
function to the graph optimisation pass B,
allowing the supported op check to run before it.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: Ic6bd4c70a478fd61adf377cb487f5b9253130314
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This reverts commit 04986c0016e59993563490fe67052371fc0e1ad2.
Reason for revert: Merged by mistake
Change-Id: I150ad9ba7074ad1e80f21180aeba56a454d9f748
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Suppress info print that Const/Placeholder/SubgraphInput are not supported
on the NPU.
Change-Id: I689d25481df0cd10487484c9f639e4253df081ee
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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Change-Id: Idcf1665f95ddecc2a12ff0e714f645263981d501
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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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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Uses LUT for int8/uint8 based tanh/sigmoid.
Change-Id: Ib6ac5a5c958ab9a17e47f620b22c3e22d8d60321
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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Updated supported operator checks for StridedSlice:
- allow negative indices in begin/end values
- added more checks on shapes
Change-Id: I3ac76bfa6b313f0e2250f0749f152fb0e3aa033c
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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In the event we have a relu op with different input and output scales,
we need to fuse it with a nop avgpool.
Also refactor the existing avgpool nop code to a common function.
Signed-off-by: Michael McGeagh <michael.mcgeagh@arm.com>
Change-Id: Iedf4513e7595ee4ee1777ba0b1eb38a8df8aed5e
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Allows fusing of LUT with a preceding operator regardless of
input/output scale.
Change-Id: Ia378adbb3fe61d71299feb085f7313377e0efa39
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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For SplitV sizesplit can contain one -1 indicating that
dimension is to be inferred.
Support added to handle this.
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: Ib9fc8dd2ee1749e81a978d85f2d4a016698bb441
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Allows int64 data type to be used as long as all values can be packed
into a int40 value.
Signed-off-by: Jacob Bohlin <jacob.bohlin@arm.com>
Change-Id: I0e25ec482e3ea765a5fd00bcf7e212a9e65a1461
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