- 16 Feb, 2020 1 commit
-
-
Tomasz Dołbniak authored
* Constify the onnx importer conv * Extract and fix the groups attribute validation for Conv * Check if the convolution's data input rank is static * Validate the groups attribute against channels and filters * Validate the conv operation in a separate function * Dynamically broadcast the conv bias if needed * Import a test model with dynamic batch conv op * Run a conv test with dynamic batch * Cleanup of conv bias handling code * Use a proper Broadcast constructor for bias in onnx conv * Handle dynamic ReduceMean with statically defined rank * Use the target shape rank to construct the default output shape for Broadcast * Handle ONNX Squeeze with dynamic input and static rank * Handle ONNX Shape with dynamic input and static rank * Handle the dynamic target shape in ONNX Reshape * Fix for the ONNX Shape input validation * Handle ONNX Softmax with dynamic input and static rank * Fix the failing Broadcast type prop test * Code formatting * Dont broadcast bias before adding it to the conv node * Drop the conv node validation and rely on the core op implementation checks * Code review feedback * Revert the Broadcast op changes * More code review feedback * Dynamic conv test using ng test case * Obsolete headers removal * Code formatting * Variable names refactor * Disable model_conv_with_dynamic_batch test on GPU * Code formatting Co-authored-by:
Sang Ik Lee <sang.ik.lee@intel.com>
-
- 22 Jan, 2020 1 commit
-
-
Mateusz Bencer authored
* Resolved problems with too restrictive data type * Apply suggestions from code review Code review remarks introduced Co-Authored-By:
Tomasz Socha <tomasz.socha@intel.com> * Code review remarks. Part.2 Co-authored-by:
Tomasz Socha <tomasz.socha@intel.com> Co-authored-by:
Adam Rogowiec <adam.osewski@intel.com> Co-authored-by:
Sang Ik Lee <sang.ik.lee@intel.com>
-
- 01 Jan, 2020 1 commit
-
-
Robert Kimball authored
* Update license to new year * Pick up some strays
-
- 17 Oct, 2019 1 commit
-
-
Jayaram Bobba authored
* - Added support for v1 Broadcast op specification - Added upgrade/downgrade conversions between v0 and v1 * Added unit test for pdpd broadcast * Make numpy default autobroadcast type and some style fixes * Added support in Dynamic wrapper for dyn elimination and copied over unit tests from DynBroadcast * Addressed PR feedback * Addressed PR feedback on documentation
-
- 15 Jul, 2019 1 commit
-
-
Adam Procter authored
* Start splitting type_prop.cpp (just a few for now, to get feedback on general pattern) * Split out some more type_prop stuff * A bunch more * Move one test out of type_prop into build_graph * Split Reverse from ReverseSequence (oops), and fix a typo I noticed in dyn_reshape.cpp * fix EOF newline * Style. * Add newline at eof.
-