GitLab

Implements dynamic shapes in reduce_op and all its child operator classes (reduce_max etc.)

Extends dot MIGX operator to handle dynamic input shapes
Only allow dot between two dynamic shapes that have exactly matching outer dimensions
Inner dimensions must also match correspondingly
Updates dot related tests
Change check_shapes to use shape.ndim()
ONNX parsers for GEMM and MatMult will be updated in a separate PR

No major changes required, use dyn_output and pass dynamic shape when calling compute_shape()
Adds dynamic shape tests

Changes flatten's compute_shape() to handle dynamic shapes
Calculates the flattened shape with the min, max, and opt

Extends the Argmax operator to handle dynamic input shapes.
Only shape function changes

Extends unsqueeze and squeeze to work for dynamic input shapes
Does not handle the steps parameter
Adds some additional negative axes shape tests

Extends the pooling operators for dynamic shape inputs

AveragePooling
GlobalAveragePooling
MaxPooling
GlobalMaxPooling
LpNormPooling
GlobalLpNormPooling
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Extends ref transpose operator for dynamic shapes
Make dynamic tests more consistent naming

Extends the ref contiguous operator to handle dynamic shapes
Updates the eliminate_contiguous pass to use the dyn_output struct

Updated Multibroadcast op to have a two input version for dynamic shapes
Current dynamic shape broadcasting logic
dynamic_dimensions must be the same or one of them is {1, 1, 0} or {1, 1, 1}
Works for dyn-dyn, dyn-static, and static-static shape combinations
Changed common.cpp for multibroadcasting for binary ops with dynamic shapes
Extended binary.hpp for dynamic shapes to test the new common.cpp stuff

Removes use_dynamic_same_auto_pad
Change padding_mode to be used for dynamic padding
Move compute_padded_shape to pad_calc.cpp as it will be used in other dynamic padding cases
Fix same_lower compute_padded_shape bug and add a test.

Rewrites the TF batch norm like operators to other MIGX operators
Removes the code related to batch_norm_inference

Has NMS op output a dynamic shape (ONNX spec behavior)
Allows for dynamic input shape to NMS op

* Dynamic shape handling in shape object

* rewrite empty lens multibroadcast test

* Shape class changes to handle dynamic
* More throw errors for functions that don't make sense for dynamic shape
* Print output changes
* Serialization changes

* Fixing serialization errors

* Remove const on dyn_dim copy getters

* Dynamic shape tests

* Fix serialize errors

* Add dyn_data struct to avoid ambiguous constructor

* Tidy fix: emplace_back() over for loop

* Tidy fix: use move

* Use std::initializer_list in constructor
Reverts the dyn_data struct change
Should get around the ambiguous braced initialization list error

* avoid typedef

* element_space, min,max,opt _lens change

* formatting

* Comments fix

* dynamic bytes() test

* Seralize and reflect changes

* formatting

* Test the dynamic lens functions

* progress

* Formatting

* Dynamic conv draft progress

* Add operator<< tests for coverage

* Coverage update

* Add to conv dynamic batch test

* Dynamic image size test

* Dynamic weight handling

* Dyn image shape test change, fix dyn weight cond

* Comment update

* Dynamic weights shape test and fix

* Use ternary operator

* Tidy fixes

* Handle dynamic graph input shapes in ONNX parser

* Formatting

* Handle dynamic shape for convolution

* formatting

* cppcheck fixes

* Add onnx test files

* Fix typo

* Disable auto_pad for dynamic input shape

* check_shapes object checks for allowing dynamic shapes

* Fix any_of

* Change to maintain const objectness

* Formatting

* Check shapes allow dynamic

* Refactor compute_shape() call into op.compute()
Allows for per operator differences with handling dynamic shape
Fix operation.hpp change to use the generator

* Comment fix

* Refactor normalize_attributes() calls to use max_lens()

* Comment addition

* Update other normalize_attributes() calls

* Change to using constructor and add tests

* Use const member function

* Add more dynamic shape support

* Add tests for error code coverage

* Fix opt shape bug and add shape tests

* capture all by ref

* Fix typo with img shape calculation

* Add more tests

* dynamic auto pad attempt
Linker error with pad_calc.cpp

* Fix parse dyn auto_pad
Should only need to use dynamic auto pad when the image shape or kernel
shape are dynamic. For a dynamic batch size, the auto pad calculation is
the same.

* Fix linking error

* Fix auto_pad bug
Fixed input tensor with auto_pad setting on

* auto_pad onnx tests

* Fix auto_pad calculation, evaluate in ref_conv
add ref_ops tests

* Add shape tests, fix bugs

* Refactor first two output dynamic len calculation

* Conv MLIR test update

* i64 MLIR test fix

* Fix MLIR test typo
Co-authored-by: Chris Austen <causten@users.noreply.github.com>

Initial sketch for changes to shape to handle dynamic dimensions

Instead of just unsqueezing to an axis of 1 a step can be set to use instead. So instead of unsqueezing {3, 12} to {3, 1, 12} a step of 2 will unsqeeze to {3, 2, 6} instead

Updated each source file in the repo with the existing license.

Changed the pooling values for two structures from strings to specialized enum classes. Many test and operator parsing changes to support this. Introduces one new source file, op_enums.cpp.

Add onnx parser and ref and gpu implementations of ONNX op ScatterND

Support nonstandard shapes like slice, broadcast and transpose for the unsqueeze op

Support slice, broadcast and transpose shapes for the squeeze op.

Implementation of the roialign operator. For now, we have only the ref implementation. When we run a model on the GPU, we fall back the execution to use the ref implementation.

Previously dot operator was defined as C = alpha * A . B + beta * C where * is scalar multiplication and . is dot product or matrix multiplication depending on dimension of the inputs.

Aim is to have the definition of dot operator as C = A . B without having alpha or beta.

In order to achieve the same effect as alpha and beta (1) it multiplies the one of the inputs to the dot operator with alpha value. (2) if beta is present then, multiplies the C with beta and then adds into the output from step 1.

Add multinomial op to onnx parser with ref and GPU implementations.

The onnx parser inserts a literal of shape {batch_size, sample_size} with random values in the range [0, 1) and inserts existing ops to compute the cumulative density function. The multinomial operator multiplies the random values by the sum of the CDF and returns the index of the first element of the CDF that is greater than the result, representing samples randomly drawn from [0, class_size) that follow the log-probability distribution.

Resolves #821
Co-authored-by: Shucai Xiao <shucai@gmail.com>

Implement the Where operator for the CPU and GPU.  This is for better performance.

* fix two asserts for debug build

* add unit test for copy parameters

* clang format

* add a unit test for reorder_dims

* change tranpose to always require perm not be empty

* clang format

* remove an unnecessary line

* fix tidy error

* fix review comments

* rename broadcast and multibroadcast output_lens attribute to out_lens attribute, and change tests and source code to reflect the same

* change the reshape attribute from dims to out_lens

* change transpose attribute's name from dims to perm to reflect better meaning

* use permutation instead of perm for transpose

clang formaating

* use dims instead of out_lens for reshape

clang formatting

* unary scalar input processing

* remove an unnecessary change

* remove unnecessary blank line

* Add definitions for all pointwise operators

* Formatting

* Add cpp generator class

* Formatting

* Move compilation to core

* Formatting

* Add clock to tmp name

* Add dynamic loader

* Formatting

* Add tests for code gen

* Formatting

* Add test for literals

* Formatting

* Use with_char

* Add missing header

* Fix mismerge

* Ignore tidy warning

* Fxx gcc 5 errors

* Apply fixits

* Skip signed bitwise of status

* Remove unused parameters

* Explicitly add c++14 flag

* Fix tidy warning

* unify the compute function signature

* clang format

* make another change

* unify the compute function

* clang format

* remove unnecessary code

* more refinement about the operator compute funciton

* clang format

* add an overload function

* clang format

* add support for axes inputs for sequeeze/unsqueeze/reduce_sum

* clang format

* fix build problems

* backup code changes

* clang format

* Add tuple type to shape class

* Formatting

* fix a bug in parsing quantizelinear operator

* clang format

* fix a cppcheck error

* disable different versions of unit tests for different onnx version

* clang format

* upgrade onnx to 1.8

* update onnx to 1.8.1

* disable two more real models

* clang format

* Make data member private

* Formatting

* Add sub arguments

* Formatting

* Trun clang format off

* Disable clang-format

* fix review comments

* fix the function of assign axes in parsing the squeeze operator

* add unit tests and fix a bug

* clang format

* fix review comments

* clang format

* fix a build error

* backup code changes

* clang format

* add more unit tests and add parsing opset version

* clang format

* Improve visiting tuples

* Formatting

* fix cppcheck error

* adding installing the onnx package

* resolve no protobuf compiler

* add an inline subgraph pass

* clang format

* Add more argument tests

* Formatting

* Handle tuple in load

* Formatting

* code backup

* clang format

* Remove .o files

* Add tuple type to api

* Formatting

* fix build errors

* clang format

* code backup

* code backup

* add unit tests for the inline subgraph

* clang format

* refine the inline subgraph and parse if operator

* clang format

* fix cppcheck issue

* clang format

* add unit test for inline subgraph pass

* clang format

* fix format issue

* remove the context from the if operator

* clang format

* simplify the compute functions

* Fix tidy warnings

* fix cppcheck error

* clang format

* fix cppcheck error

* Fix tidy warnings

* fix a cppcheck error

* clang format

* Add a test for share method

* Formatting

* Add a test cpp_type

* add unit tests for more code coverage

* clang format

* add unit tests to have more code coverage

* clang format

* try a comment in jenkins build

* include the install onnnx line

* code backup

* reorder the dependenciesd installed

* refine dockerfile

* fix review comments

* clang format

* remove unnecessary overload function

* fix cppcheck error

* change back the argument test

* Suppress tidy warning

* add the operator get_tuple_elem

* clang format

* add get_tuple_elem to operator include file

* chang if to support multiple operation outputs

* clang format

* optimize inline subgraph

* clang format

* code backup

* clang format

* fix bug

* refine unit tests for tuple output of the if operator

* clang format

* refine a instruction replacement code

* add a unit test and sort all the unit tests alphabetically

* fix cppcheck error

* add more unit tests for multiple op outputs

* clang format

* fix cppcheck error

* Update pass manager to get modules after every pass

* more unit test to cover more scenarios

* clang format

* fixed a bug in a unit test

* add more tests

* clang format

* add more unit tests to have more code coverage

* fix a bug in a unit test

* Add program overload for module

* Formatting

* Hash modules for quicker lookup of modules

* Bump file version

* Add methods to remove modules

* Formatting

* add the tuple type to the support list

* Eliminate unused modules

* Formatting

* Fix test errors

* Foramtting

* Fix tidy issues

* fix problem related to inline subgraph

* clang format

* fix review comments

* fix review comments

* fix review comments

* fix review comments

* clang format

* fix a unit test

* one more code change

* remove an optimization related to the if operator

* clang format

* fix review comments
Co-authored-by: Paul <pfultz2@yahoo.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* add the operator step

* clang formatJ

* add unit tests

* clang format

* add more unit test for step op

* clang format

* add more unit tests

* clang format

* fix review comments

* clang format

* rename two unit tests
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

* Add scan struct; add initial tests; initial algorithm by cases; refactor into one algorithm; clean up code

* Rename; restructure; begin adding additional attributes

* refactor to use shape_for_each; temporarily drop reverse mode

* Add back reverse mode with shape_for_each_reverse; update tests; add axis bounds check

* Begin adding to onnx parser

* Add to onnx parser

* Fix onnx test

* Fix CI warnings

* Update algorithm to use slice+par_for; update gen_onnx; remove .o files; remove redundant axis normalizing

* Add exclusive mode

* Add reverse mode

* Remove .pyc file

* Fix warning

* Remove shape_for_each_reverse; clean up pointer usage for exclusive cases

* Remove unused variable

* Fix onnx test

* Add test case to op_shape_test

* Formatting

* Formatting

* Fix tidy warning

* Formatting

* Formatting

* Formatting

* Increase code coverage

* Formatting

* refine the script for creating the cumsum onnx file

* Alphabetize includes for operators.hpp

* Revise onnx test

* Remove redundant bounds check

* Formatting and style

* Alphabetize tests

* Remove duplicate tests from merge

* Fix tidy warning for sub_test
Co-authored-by: Shucai Xiao <Shucai.Xiao@amd.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* Add eliminate_data_type pass

* Formatting

* Auto convert quant ops

* Formatting

* Flip the order of decompose

* Compute max size differently

* Formatting

* Clamp values in convert

* Formatting

* Fix loss of precision in reduce

* Formatting

* Fix bugs in reduction

* Fix accumulator type in reference softmax implementation

* Formatting

* Update convert test

* Remove unused variables

* Remove unnecessary quant_dot check

* Formatting

* Add tests

* Formatting

* Remove unused code

* Remove duplicate ops

* Remove blaze dependency

* Use set since shape::type_t is no hashable on gcc 5

* Formatting
Co-authored-by: Shucai Xiao <shucai@gmail.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* Normalize compute functions

* Formatting

* Save normalization flag to the file

* Formatting

* Remove tuned functions

* Formatting

* Use in_index
Co-authored-by: Shucai Xiao <shucai@gmail.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* change transpose func

* formatting

* fix tf file

* add tests, change broadcast

* formatting

* revert if statement

* add nonzero axis test

* formatting

* remove test and add test file

* fix test

* formatting

* add test for more coverage

* change error message

* change error message
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

* Load op when serializing

* Formatting

* Add missing clip field

* Use make_op almost everywhere

* Formatting

* More make ops for rnns

* Get rid of spaces

* Formatting

* Remove operators headers

* Formatting

* Remove unused op headers

* Increase line threshold

* change transpose func

* formatting

* fix tf file

* add tests, change broadcast

* formatting

* revert if statement

* add nonzero axis test

* formatting

* remove test and add test file
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

* code backup

* clang format

* change corresponding tool files

* clang format
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* Enforce op name for check_shapes class

* Add test for scalar

* Formatting
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* support pooling ceil_mode

* clang format

* add unit test for pooling ceil mode

* clang format

* fix review comments

* clang format

* add more unit tests and fixed a bug in cpu pooling implementation

* clang format

* add one more unit test

* clang format

* fix cppcheck error

* fix cppcheck error

* fix cppcheck error

* fix review comments

* clang format

* remove the padding_mode attribute in pooling

* clang format

* clang format

* fix review comments

* clang format

* fix a cppcheck error

* fix review comments
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>