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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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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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- 256 and 512 configuration variants execute 1D convolutions
in an optimised manner compared to their 2x2 microblock
dimensions. This commit takes this into account to improve
Conv1D throughput on these configurations.
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I6ecdf6e4a219e356327b22f8393f50ee8817af23
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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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When a MEAN operator with a single reduction axis
specifies the axis index attribute as an array with
a single element rather than a scalar index, the
operator is placed on the CPU even though it is
technically supported.
This commit fixes this issue and also adds some new
tests for the axis constraints.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: Ia287f3b9cc80a805e972cd4b2962e52526a8dc16
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Check if non linear tensor format can be used is
refactored.
-Flag avoid_NHCWB16 replaced with needs_linear_format
-Checking restrictions located to one function in graph optimiser.
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: Iec5c7996a1a6039cad052197f1ae56f7c0290440
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This is a small commit which changes one of
the four MEAN implementations to a simpler
one, using an AvgPool instead of a
DepthwiseConv.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: I9e8af071e8b820796577ee4792b4812a1212602b
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Bug fix in generation of register command offsets that do not fit in 32 bit.
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
Change-Id: Iabb99cf6536c0f77b934691f8744df61f1eab3ed
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- Tensor allocation verification was O(N^2), is now closer to O(N)
- Removed a sort in HillClimb allocator
Change-Id: I286a269881490c485cc2b0eeab3b1ecffa8f3df0
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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Added checks during command stream generation to make sure
that address boundaries are respected.
Change-Id: I4dbc693b42d54e35c8fcc785e8be88059e409eec
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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This commit adds support for emulating the behavior
of the QuantizedMeanOrSum implementation of MEAN in
TensorFlow Lite.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: Ifd24e0e678e2f85cd66ab82deeaaf010d5351b1e
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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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Previously the keep_dims or keep_num_dims attribute was not supported for Sum and Fully Connected operators and would thus crash for certain tests. With this update, the attribute is extracted correctly and saved to the optimised tflite file.
Signed-off-by: erik.andersson@arm.com <erik.andersson@arm.com>
Change-Id: If33487f6d299bb99788bb3d13332b842ba961641
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All files which have been updated in 2021 and contain a copyright header have had their headers updated.
Signed-off-by: erik.andersson@arm.com <erik.andersson@arm.com>
Change-Id: Ia682111a719d16e690433398ccfb69c7e93c1cd1
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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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- Straight port of the C++ implementation to python.
- Renamed the allocator from "Search" to "HillClimb"
Change-Id: I50797d541f326d0264daf79bf7866aef32350a60
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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-Removed ConcatSliceWrite from the optimised graph.
Always executed as avgpool, which is equivalent with
before the patch.
-Added copy op to enable more removal of reshapes.
Sg input/outputs need to remain. When Reshape input and
outut, are sg input/outputs a copy op is needed to
be inserted, in order to remove the reshape.
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: Id7be9966673ae34499e8518a5544104493fe326b
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Added supported operator check that 32-bit fused activation functions
are not supported.
Change-Id: I01fdafeff8fdb13c71eae4f63be7e6f81b9223df
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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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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Fixed a bug where PAD having no consumers would result in a crash.
Now the constraint doesn't crash and thus the intended error message is shown, resulting in easier debugging.
Change-Id: I1e4403d47a6152e7adbf7bc065db86d4217d39cc
Signed-off-by: erik.andersson@arm.com <erik.andersson@arm.com>
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- Added operator check that OFM scale > smallest float32 number
- Generalized the restriction that IFM/OFM scale must not be infinite
Change-Id: I918f5ea3d8fdec6e8f6bd6780ed13a19d1234ed6
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
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Added handling of input tensors with constant string data.
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
Change-Id: Ieb5164a9d56d580ad08ea834bf2cbb7288cd9539
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Constraints and unit tests were added to check the new pad operator.
Change-Id: Id6d4cf2c4da486928c8f46ba1fa124eec66895a6
Signed-off-by: erik.andersson@arm.com <erik.andersson@arm.com>
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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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