- 02 Jul, 2023 1 commit
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Charlie Lin authored
Updates ref version of clip to work with dynamic shapes Encountered in agentmodel
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- 16 Jun, 2023 1 commit
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Charlie Lin authored
* initial * Added tests and new functionality * Update optimals handling * Simplify conditionals * Ref test, update docs * Remove comment, suggestion unclear --------- Co-authored-by:Umang Yadav <29876643+umangyadav@users.noreply.github.com>
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- 15 Jun, 2023 1 commit
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Brian Pickrell authored
* fix parse_instancenorm to create broadcast and multibroadcast instructions with two dynamic shape arguments instead of 1. Their make_op() functions don't support dynamic shapes when called with one input. This caused an error when parsing an ONNX 3duunet model * Use add_common_op() to create multibroadcast op. * add verification and parsing test for instance_norm with dynamic input. Parse test doesn't pass. * fix for test; still doesn't pass * another fix for test; still doesn't pass * work in progress, instance_norm_dyn_batch_test works but instance_norm_test doesn't * fix onnx instancenorm tests to match parser changes. Passes all check tests * Updated comments explaining usage of add_common_op() * hand-merged conflicts with develop * fix instance_norm_half_test after merge * add Onnx test instance_norm_dyn_batch_half_test * add shape test cases broadcast_1in_dyn_error and multibroadcast_1in_dyn_error_0
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- 07 Apr, 2023 1 commit
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Paul Fultz II authored
Converts can be inserted when the scales and input differ in the onnx file(we are already doing this implicit conversion in the ref implementation). This will also improve the compile-time of quantizelinear.hpp since we can remove the nested visit method.
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- 04 Apr, 2023 1 commit
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Charlie Lin authored
Makes the optimals into a std::set<std::size_t> Changes shape object functions to handle the opts change Changes to convolution, flatten, pooling, and convolution in that they no longer calculate the output optimal dimensions. Instead returns empty opts. Will need to change this in the future if we want to support dynamic shapes fully. Many changes to tests and shape calls with respect to the new optimals
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- 13 Dec, 2022 1 commit
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Charlie Lin authored
Implements the operator==(dynamic_dimension, size_t) functions
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- 13 Nov, 2022 1 commit
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Charlie Lin authored
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
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- 22 Jun, 2022 1 commit
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Ted Themistokleous authored
Updated each source file in the repo with the existing license.
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- 08 Oct, 2021 1 commit
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Umang Yadav authored
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.
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- 17 Sep, 2021 2 commits
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Paul Fultz II authored
This reverts commit 9e43cb8b.
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Umang Yadav authored
This PR aims to remove alpha and beta attributes from dot operator completely. 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.
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- 24 Aug, 2021 1 commit
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Umang Yadav authored
* 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
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- 09 Jul, 2021 1 commit
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Paul Fultz II authored
* Add implicit type conversion for broadcastable operators * Formatting * Fix warnings
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