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Ankit Maheshkar a6ea57b8f3
OpenVINO EP Weights Sharing Feature (#23553) 
### Description
These changes are done to ensure that weight sharing happens between two model using session context option ep_weight_sharing.

Key changes introduced in this feature are:

Creating a shared context between two models Extracting external constant initializers and re labelling them back as
inputs to the model to allow weight loading in the direct blob. Creating EP Context Nodes when Subgraph partitioning is happening.

### Motivation and Context
This change was required to ensure that LLM with prefill and kvcache models can use the same share
The change was also required to ensure EP Context nodes can be formed even when model is being subgraph partitioned.

---------

Co-authored-by: jatinwadhwa921 <jatin.wadhwa@intel.com>
Co-authored-by: jatinwadhwa921 <110383850+jatinwadhwa921@users.noreply.github.com>
Co-authored-by: saurabh <saurabh1.kale@intel.com>
Co-authored-by: TejalKhade28 <tejal.khade@intel.com>
Co-authored-by: sfatimar <sahar.fatima@intel.com>
Co-authored-by: Javier E. Martinez <javier.e.martinez@intel.com>
Co-authored-by: Preetha Veeramalai <preetha.veeramalai@intel.com>
Co-authored-by: Eric Crawford <eric.r.crawford@intel.com>
2025-02-06 14:57:38 -08:00
..
attention Extend Attention Bias Broadcast Support (#21710) 2024-08-16 15:40:04 -07:00
cloud_models CloudEP (#13855) 2023-01-03 10:03:15 -08:00
CNTK Target py310 and modernize codebase with ruff (#23401) 2025-01-16 19:10:14 -08:00
custom_execution_provider_library Remove core/common/gsl.h (#20894) 2024-07-08 18:09:39 -07:00
custom_op_get_const_input_test_library Allow disable exceptions to work with ort-extensions (#16536) 2023-06-29 18:24:33 -07:00
custom_op_invalid_library Improve custom op library handle cleanup (#14099) 2023-01-04 17:56:29 -08:00
custom_op_library [ROCm] prefer hip interfaces over roc during hipify (#22394) 2024-10-14 20:34:03 -07:00
custom_op_local_function Enable comprehension simplification in ruff rules (#23414) 2025-01-17 08:43:06 -08:00
custom_op_openvino_wrapper_library Run clang-format in CI (#15524) 2023-04-18 09:26:58 -07:00
float8 Fix float 8 rounding on CPU (#16940) 2023-09-07 20:48:25 +02:00
lora Multi-Lora support (#22046) 2024-09-30 15:59:07 -07:00
mobilenet_v3_small_excerpt_gen [CoreML EP] Enable inputs with dynamic shape (#16915) 2023-08-03 18:15:00 -07:00
multi_stream_models Avoid call to Node::ToProto on first Graph::Resolve to improve session creation performance. (#20296) 2024-04-17 10:07:12 +10:00
ort_minimal_e2e_test_data Changes to support standalone custom ops in a minimal build. (#14497) 2023-03-01 11:22:54 +10:00
ort_minimal_test_models Update kernel matching logic: decouple from op schemas and remove kernel def hashes (#12791) 2022-09-20 14:24:59 -07:00
qnn_ctx Support loading from model with multiple QNN context binary (#20930) 2024-06-06 14:44:57 -07:00
snpe Snpe ep (#11665) 2022-06-03 14:10:02 -07:00
squeezenet Fix handling of nodes that get assigned to kMSInternalNHWCDomain when loading an ORT format model. (#20379) 2024-04-22 18:34:01 -07:00
test_data_generation Use ruff as the formatter to replace black-isort (#23397) 2025-01-16 11:14:15 -08:00
training_api Use ruff as the formatter to replace black-isort (#23397) 2025-01-16 11:14:15 -08:00
transform Update BiasGelu fusion and related ops (#23518) 2025-01-30 22:53:59 -08:00
transformers Some changes to Sampling Op (#14218) 2023-01-12 14:15:26 -08:00
TRTEP_test_model Update engine hash id generator with model name/model content/metadata (#13015) 2022-09-21 11:10:05 -07:00
abs_free_dimensions.onnx
add_opset_314159.onnx
alloc_tensor_reuse.onnx
attention_mask1d_fp16.onnx [CUDA] Add TensorRT fused attention fp16 v2 kernels (#12814) 2022-09-13 15:16:12 -07:00
attention_mask1d_fp32.onnx [CUDA] Add TensorRT fused attention fp16 v2 kernels (#12814) 2022-09-13 15:16:12 -07:00
attention_mask2d_fp32.onnx [CUDA] Add TensorRT fused attention fp16 v2 kernels (#12814) 2022-09-13 15:16:12 -07:00
attention_no_mask_fp16.onnx Flash Attention v2 MHA (#17227) 2023-08-31 13:52:21 -07:00
attention_past_state.onnx
attention_past_state.u8s8.onnx Add non-zero zp support for quant matmul and attention (#7570) 2021-05-14 16:50:31 -07:00
attention_past_state.u8u8.onnx Add non-zero zp support for quant matmul and attention (#7570) 2021-05-14 16:50:31 -07:00
avoid_reuse_of_buffer_for_node_output_with_no_consumers.onnx Avoid reusing buffer for node outputs with no consumers (#21019) 2024-06-13 16:08:16 -07:00
bart_tiny.onnx
bert_toy_optimized.onnx
bert_toy_postprocessed.onnx
capi_symbolic_dims.onnx
capi_symbolic_dims.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
ckpt_mnist.pt
clip_div_shared_initializer.onnx [NNAPI EP] Track skipped initializer usage (#21286) 2024-07-09 13:43:22 -07:00
clip_div_shared_initializer.py [NNAPI EP] Track skipped initializer usage (#21286) 2024-07-09 13:43:22 -07:00
constant_floats.onnx Set dims for constant with multiple values (#11116) 2022-04-06 07:39:07 +10:00
conv.int4_weights.qdq.onnx [QNN EP] Initial INT4 support (#21171) 2024-07-10 10:03:53 -07:00
conv_autopad.onnx
conv_qdq_external_ini.bin enable model with external data be loaded from memory buffer (#19089) 2024-04-17 19:01:01 -07:00
conv_qdq_external_ini.onnx enable model with external data be loaded from memory buffer (#19089) 2024-04-17 19:01:01 -07:00
conv_qdq_s8s8.onnx [xnnpack] basic QDQ operators support (#11912) 2022-08-11 10:12:51 +08:00
conv_qdq_s8s8_perchannel.onnx [xnnpack] basic QDQ operators support (#11912) 2022-08-11 10:12:51 +08:00
conv_qdq_u8u8.onnx [xnnpack] basic QDQ operators support (#11912) 2022-08-11 10:12:51 +08:00
coreml_argmax_cast_test.onnx [CoreML EP] Fix ArgMaxOpBuilder::AddToModelBuilderImpl() nullptr Node access. (#21797) 2024-08-23 10:19:53 -07:00
coreml_argmax_cast_test.py [CoreML EP] Fix ArgMaxOpBuilder::AddToModelBuilderImpl() nullptr Node access. (#21797) 2024-08-23 10:19:53 -07:00
coreml_argmax_unsupported_cast_test.onnx [CoreML EP] Fix ArgMaxOpBuilder::AddToModelBuilderImpl() nullptr Node access. (#21797) 2024-08-23 10:19:53 -07:00
crop_and_resize.onnx Cancel transpose optimizer for resize (#9870) 2021-11-29 22:30:16 -08:00
cuda_graph_with_shape_nodes.onnx Relax node placement check for CUDA Graph usage (#16358) 2023-06-15 14:03:08 -07:00
custom_op_negpos.onnx Integrate onnxruntime-extensions into onnxruntime. (#8143) 2021-07-01 09:34:03 -07:00
custom_op_single_schema_multi_kernel.onnx Single-schema-multi-kernel (#15184) 2023-04-27 13:39:59 -07:00
custom_op_string_lower.onnx Integrate onnxruntime-extensions into onnxruntime. (#8143) 2021-07-01 09:34:03 -07:00
custom_op_variadic_io.onnx Support for custom op variadic inputs/outputs (#13946) 2022-12-23 11:41:15 -08:00
custom_op_variadic_undef_io.onnx Support for custom op variadic inputs/outputs (#13946) 2022-12-23 11:41:15 -08:00
dummy_t5.onnx Fix BeamSearch T5 if initializers are on outer scope (#23044) 2024-12-09 15:15:20 -08:00
dummy_t5_model_generator.py Use ruff as the formatter to replace black-isort (#23397) 2025-01-16 11:14:15 -08:00
dummy_t5_pointer_generator.onnx Enable pointer-generator T5 models in BeamSearch (#23134) 2024-12-22 21:30:49 -08:00
dummy_t5_with_outer_scope_initializers.onnx Fix BeamSearch T5 if initializers are on outer scope (#23044) 2024-12-09 15:15:20 -08:00
dummy_t5_with_sequence_input_ids.onnx [CUDA EP] Fix BeamSearch on T5 with sequence_as_input_ids (#20667) (#20668) 2024-12-10 16:20:47 -08:00
dynamic_quantize_matmul_int8.onnx Add non-zero zp support for quant matmul and attention (#7570) 2021-05-14 16:50:31 -07:00
dynamic_quantize_matmul_int8_bias.onnx Add non-zero zp support for quant matmul and attention (#7570) 2021-05-14 16:50:31 -07:00
dynamic_quantize_matmul_test.py Target py310 and modernize codebase with ruff (#23401) 2025-01-16 19:10:14 -08:00
dynamic_quantize_matmul_uint8.onnx Add non-zero zp support for quant matmul and attention (#7570) 2021-05-14 16:50:31 -07:00
dynamic_quantize_matmul_uint8_bias.onnx Add non-zero zp support for quant matmul and attention (#7570) 2021-05-14 16:50:31 -07:00
ep_dynamic_graph_input_test.onnx Add logic to NNAPI EP to exclude pre-processing involving dynamic shapes when partitioning (#10452) 2022-02-02 15:54:19 -08:00
ep_dynamic_graph_input_test.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
ep_partitioning_test_1.onnx Add enhanced partitioning utils for use by compiling EPs (#7991) 2021-06-11 15:23:21 +10:00
ep_partitioning_test_2.onnx Add enhanced partitioning utils for use by compiling EPs (#7991) 2021-06-11 15:23:21 +10:00
ep_partitioning_tests.py Target py310 and modernize codebase with ruff (#23401) 2025-01-16 19:10:14 -08:00
flatten_broadcast.onnx Fix CoreML Flatten handling of axis attribute (#16046) 2023-05-24 08:27:32 +10:00
foo_1.onnx Fix issue with schema lookup where there are custom ops using the ONNX domain (#14492) 2023-02-03 08:05:18 +10:00
foo_1.onnx.ort Changes to support standalone custom ops in a minimal build. (#14497) 2023-03-01 11:22:54 +10:00
foo_1_clip_11.onnx Fix issue with schema lookup where there are custom ops using the ONNX domain (#14492) 2023-02-03 08:05:18 +10:00
foo_3.onnx Fix issue with schema lookup where there are custom ops using the ONNX domain (#14492) 2023-02-03 08:05:18 +10:00
foo_bar_1.onnx Fix issue with schema lookup where there are custom ops using the ONNX domain (#14492) 2023-02-03 08:05:18 +10:00
foo_bar_2.onnx Fix issue with schema lookup where there are custom ops using the ONNX domain (#14492) 2023-02-03 08:05:18 +10:00
foo_bar_3.onnx Fix issue with schema lookup where there are custom ops using the ONNX domain (#14492) 2023-02-03 08:05:18 +10:00
function_opset_test.onnx
function_with_variadics.onnx Add handling for variadic inputs/outputs in a function. (#13140) 2022-09-30 14:51:17 +10:00
fuse_mul_1.onnx
fuse_select_filter.onnx Versioning for custom op (#18088) 2023-10-31 16:50:27 -07:00
fuse_select_filter_opset_8.onnx Versioning for custom op (#18088) 2023-10-31 16:50:27 -07:00
gather_with_scalar_indices_then_shape.onnx [CoreML EP] Add Shape, Gather, and Slice ops (#17153) 2023-08-18 22:34:34 -07:00
gather_with_scalar_indices_then_shape.py [CoreML EP] Add Shape, Gather, and Slice ops (#17153) 2023-08-18 22:34:34 -07:00
gh_issue_9671.onnx Fix Issue #9671 (#9691) 2021-11-12 07:18:16 +10:00
gh_issue_11717.onnx Skip Constant Folding for ops producing an optional type output (#11839) 2022-06-30 13:38:35 -07:00
identity_9799.onnx Fix potential data race with OrtValue usage in Python (#9841) 2021-11-23 14:34:24 -08:00
identity_opt.onnx io_binding to handle optional input of sequence type_proto (#19273) 2024-01-30 10:25:14 -08:00
identity_string.onnx
initializer_as_output.onnx
invalid_dim_param_value_repetition.onnx Avoid reusing buffer for node outputs with no consumers (#21019) 2024-06-13 16:08:16 -07:00
invalid_dim_param_value_repetition.py Avoid reusing buffer for node outputs with no consumers (#21019) 2024-06-13 16:08:16 -07:00
issue4829.onnx
LabelEncoder.onnx
layernorm.onnx
layernorm_no_bias.onnx
layout_transform_const_folding.qdq.onnx Layout transform: Fix-up QDQ units and add constant folding (#20685) 2024-05-20 20:19:06 -07:00
layout_transform_fix_transpose_without_dq.qdq.onnx Layout transform: Fix-up QDQ units and add constant folding (#20685) 2024-05-20 20:19:06 -07:00
layout_transform_nonconst_broadcast_input.onnx Update transpose optimization to be more QDQ aware (#18444) 2023-11-23 08:27:47 +10:00
layout_transform_reshape.onnx Transpose optimizer enhancements (#15117) 2023-03-28 08:28:17 +10:00
layout_transform_reshape.qdq.onnx Transpose optimizer enhancements (#15117) 2023-03-28 08:28:17 +10:00
logicaland.onnx
make_conv_int4_weights_model.py [QNN EP] Initial INT4 support (#21171) 2024-07-10 10:03:53 -07:00
make_qdq_layout_transform_const_folding.py Layout transform: Fix-up QDQ units and add constant folding (#20685) 2024-05-20 20:19:06 -07:00
make_transpose_optimizer_empty_dq_q_at_output_model.py Remove empty (DQ -> Q -> graph output) sequence in TransposeOptimizer (#22172) 2024-09-24 21:02:17 -07:00
make_transpose_optimizer_per_axis_qdq_models.py [TransposeOptimizer] Support Unsqueeze/Transpose of input consumed by per-axis DQ (#21821) 2024-09-05 17:26:17 -07:00
matmul_1.onnx
matmul_2.onnx
matmul_integer_to_float.py Target py310 and modernize codebase with ruff (#23401) 2025-01-16 19:10:14 -08:00
matmul_integer_to_float_int8.onnx [DML] MatrixMultiplyIntegerToFloat (#19608) 2024-03-04 11:55:35 -08:00
matmul_integer_to_float_int8_bias.onnx [DML] MatrixMultiplyIntegerToFloat (#19608) 2024-03-04 11:55:35 -08:00
matmul_integer_to_float_int8_int8.onnx [DML] MatrixMultiplyIntegerToFloat (#19608) 2024-03-04 11:55:35 -08:00
matmul_integer_to_float_int8_int8_bias.onnx [DML] MatrixMultiplyIntegerToFloat (#19608) 2024-03-04 11:55:35 -08:00
matmul_integer_to_float_uint8.onnx [DML] MatrixMultiplyIntegerToFloat (#19608) 2024-03-04 11:55:35 -08:00
matmul_integer_to_float_uint8_bias.onnx [DML] MatrixMultiplyIntegerToFloat (#19608) 2024-03-04 11:55:35 -08:00
matmul_with_dynamic_input_shape.onnx [CoreML EP] Enable inputs with dynamic shape (#16915) 2023-08-03 18:15:00 -07:00
matmul_with_dynamic_input_shape.py [CoreML EP] Enable inputs with dynamic shape (#16915) 2023-08-03 18:15:00 -07:00
merge.onnx Implement lite custom op API (#15778) 2023-05-04 09:49:17 -07:00
mlnet_encoder.onnx
mnist.basic.ort Update kernel matching logic: decouple from op schemas and remove kernel def hashes (#12791) 2022-09-20 14:24:59 -07:00
mnist.basic.v4.ort Add backwards compatibility for all versions of ORT format model in full build. (#13242) 2022-10-12 17:45:52 +10:00
mnist.internal_testing_ep.ort Update kernel matching logic: decouple from op schemas and remove kernel def hashes (#12791) 2022-09-20 14:24:59 -07:00
mnist.onnx
mnist.readme.txt Update kernel matching logic: decouple from op schemas and remove kernel def hashes (#12791) 2022-09-20 14:24:59 -07:00
mobilenet_v3_small_excerpt.onnx [CoreML EP] Enable inputs with dynamic shape (#16915) 2023-08-03 18:15:00 -07:00
mobilenet_v3_small_excerpt_gen.py [CoreML EP] Enable inputs with dynamic shape (#16915) 2023-08-03 18:15:00 -07:00
model_containing_op_with_function_body.onnx
model_resize_empty_optional_input.onnx skip the placeholder inputs while adding node inputs as sub-graph inputs (#13106) 2022-09-26 21:06:29 -07:00
model_with_external_initializer_come_from_user.onnx Provide an API to supply external initializers data from user buffers (#11109) 2022-04-07 12:21:53 -07:00
model_with_external_initializer_come_from_user.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
model_with_external_initializers.onnx Revert "enable serialize prepacked weights into data file (#22256)" (#22788) 2024-11-11 09:59:05 -08:00
model_with_external_initializers.py Revert "enable serialize prepacked weights into data file (#22256)" (#22788) 2024-11-11 09:59:05 -08:00
model_with_invalid_ort_config_json.onnx
model_with_metadata.onnx Add metadata_props to ORT model (#8340) 2021-07-09 11:28:27 -07:00
model_with_metadata.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
model_with_orig_ext_data.bin Extend saving models optimized by inference session (#16912) 2023-07-31 16:39:35 -07:00
model_with_orig_ext_data.onnx Revert "enable serialize prepacked weights into data file (#22256)" (#22788) 2024-11-11 09:59:05 -08:00
model_with_valid_ort_config_json.onnx
mul_1.noopset.onnx
mul_1.onnx
mul_1_dynamic.onnx cuda graph enhancement (#19636) 2024-03-07 10:15:18 -08:00
mul_16.onnx
nhwc_conv_clip_relu.onnx XNNPACK EP (#11445) 2022-06-03 20:22:34 +10:00
nhwc_conv_clip_relu.txt XNNPACK EP (#11445) 2022-06-03 20:22:34 +10:00
nhwc_resize_scales_opset11.onnx [QNN EP] Fix shape inference of NHWC Resize (#15477) 2023-04-20 07:25:25 -07:00
nhwc_resize_scales_opset18.onnx [QNN EP] Fix shape inference of NHWC Resize (#15477) 2023-04-20 07:25:25 -07:00
nhwc_resize_sizes_opset11.onnx [QNN EP] Fix shape inference of NHWC Resize (#15477) 2023-04-20 07:25:25 -07:00
nhwc_resize_sizes_opset18.onnx [QNN EP] Fix shape inference of NHWC Resize (#15477) 2023-04-20 07:25:25 -07:00
nhwc_resize_sizes_opset18.quant.onnx [QNN EP] Fix shape inference of NHWC Resize (#15477) 2023-04-20 07:25:25 -07:00
nnapi_internal_uint8_support.onnx [NNAPI EP] Fix MaxPool error using uint8 (#9129) 2021-09-21 00:44:43 -07:00
nnapi_internal_uint8_support.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
nnapi_reshape_flatten_test.onnx
nnapi_reshape_flatten_test.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
nnapi_sigmoid_input_rank_test.onnx Add limit input rank <= 4 in NNAPI EP Sigmoid op support checker (#13019) 2022-09-20 16:40:45 -07:00
nnapi_sigmoid_input_rank_test.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
onnx_backend_test_series_filters.jsonc OpenVINO EP Weights Sharing Feature (#23553) 2025-02-06 14:57:38 -08:00
onnx_backend_test_series_overrides.jsonc ONNX 1.15 integration (#17125) 2023-09-26 14:44:48 -07:00
optional_1.onnx Fix issue with schema lookup where there are custom ops using the ONNX domain (#14492) 2023-02-03 08:05:18 +10:00
optional_2.onnx Implement lite custom op API (#15778) 2023-05-04 09:49:17 -07:00
optional_3.onnx Implement lite custom op API (#15778) 2023-05-04 09:49:17 -07:00
optional_inputs_ir3.onnx
optional_inputs_ir4.onnx
optional_sequence_tensor.onnx Fix bug in MemcpyToHost (#10816) 2022-03-10 07:02:27 -08:00
ort_github_issue_4031.onnx
ort_github_issue_4031.onnx.ort Update kernel matching logic: decouple from op schemas and remove kernel def hashes (#12791) 2022-09-20 14:24:59 -07:00
ort_github_issue_4031.py Format all python files under onnxruntime with black and isort (#11324) 2022-04-26 09:35:16 -07:00
ort_github_issue_10305.onnx Fix GH Issue 10305 by adding implicit inputs to consumer nodes map. (#10319) 2022-01-20 07:46:35 +10:00
ort_github_issue_10305.py Format all python files under onnxruntime with black and isort (#11324) 2022-04-26 09:35:16 -07:00
ort_github_issue_11536.onnx Add better error message for subgraph output coming directly from outer scope value. (#11638) 2022-05-28 08:04:27 +10:00
ort_github_issue_12151.onnx Fix GH issue 12151 by using inverse perms for updating DQ axis attribute (#12158) 2022-07-13 18:02:58 +10:00
ort_github_issue_12151_neg_dq_axis.onnx [TransposeOptimizer] Fix axis for QuantizeLinear inserted after DQ (per-channel) -> Unsqueeze (#21793) 2024-08-20 16:26:02 -07:00
ort_github_issue_15949.onnx Fix some issues with NNAPI Softmax (#16095) 2023-06-08 13:56:06 +10:00
ort_github_issue_17000.onnx Two fixes involving minimal builds (#17000) 2023-08-23 16:01:22 +10:00
ort_github_issue_17000.ort Two fixes involving minimal builds (#17000) 2023-08-23 16:01:22 +10:00
ort_github_issue_17000.py Two fixes involving minimal builds (#17000) 2023-08-23 16:01:22 +10:00
ort_github_issue_19590.onnx Make partitioning utils QDQ aware so it does not break up QDQ node units (#19723) 2024-03-12 10:55:49 +10:00
ort_github_issue_19590.py Make partitioning utils QDQ aware so it does not break up QDQ node units (#19723) 2024-03-12 10:55:49 +10:00
overridable_initializer.onnx
packed_attention_fp16.onnx Add PackedAttention for packing mode (#14858) 2023-03-21 12:59:29 -07:00
packed_attention_fp16.rbp.onnx add cutlass fmha support in PackedAttention (#15838) 2023-05-11 13:47:15 -07:00
packed_attention_fp16.rbp.py add cutlass fmha support in PackedAttention (#15838) 2023-05-11 13:47:15 -07:00
packed_attention_fp32.onnx Add PackedAttention for packing mode (#14858) 2023-03-21 12:59:29 -07:00
Pads.bin Disable external initializers build option (#7635) 2021-05-19 14:16:36 -07:00
pipeline_vectorize.onnx
pyop_1.onnx
pyop_2.onnx
pyop_3.onnx
qdq_minimal_model.onnx Fix quantization tools for issue #19529 (#19591) 2024-04-24 19:16:27 +02:00
qdq_with_multi_consumer_dq_nodes.onnx Add helper for optimizing a QDQ format model for usage with ORT. (#10595) 2022-02-21 09:26:19 +10:00
qdq_with_multi_consumer_q_dq_axis.onnx Fix the duplicated QDQ attributes setup issue (#18039) 2024-01-10 18:36:33 -08:00
qnn_ctx_2_inputs_order_test.onnx Fix issue that the generated context cache model inputs/outputs order is not guaranteed (#19195) 2024-01-19 15:16:17 -08:00
qnn_ep_partial_support.onnx [QNN EP] Add session option to disable fallback to default CPU EP (#16016) 2023-05-23 17:56:32 -07:00
reduced_build_test.onnx_model_with_excluded_ops
reduced_build_test.readme.txt
relu_with_optional.onnx #22890 Fix profiling on empty Optional (#22891) 2024-11-26 11:18:47 -08:00
required_ops.config Two fixes involving minimal builds (#17000) 2023-08-23 16:01:22 +10:00
required_ops_and_types.config Two fixes involving minimal builds (#17000) 2023-08-23 16:01:22 +10:00
required_ops_config.readme.txt
scan_1.onnx
sequence_construct.onnx
sequence_insert.onnx
sequence_length.onnx
shape_then_slice_and_gather.onnx [CoreML EP] Add Shape, Gather, and Slice ops (#17153) 2023-08-18 22:34:34 -07:00
shape_then_slice_and_gather.py [CoreML EP] Add Shape, Gather, and Slice ops (#17153) 2023-08-18 22:34:34 -07:00
sklearn_bin_voting_classifier_soft.onnx
sklearn_bin_voting_classifier_soft.onnx.ort Update kernel matching logic: decouple from op schemas and remove kernel def hashes (#12791) 2022-09-20 14:24:59 -07:00
sklearn_bin_voting_classifier_soft.readme.txt
sparse_initializer_as_output.onnx Implement SparseTensor and infrastructure suppport and advance ONNX commit (#8038) 2021-07-22 15:24:36 -07:00
sparse_initializer_as_output.py Target py310 and modernize codebase with ruff (#23401) 2025-01-16 19:10:14 -08:00
sparse_to_dense_matmul.onnx Implement SparseTensor and infrastructure suppport and advance ONNX commit (#8038) 2021-07-22 15:24:36 -07:00
sparse_to_dense_matmul.py Target py310 and modernize codebase with ruff (#23401) 2025-01-16 19:10:14 -08:00
subgraph_implicit_input_from_initializer.onnx
subgraph_input_shadows_outer_scope_value.onnx
test_cast_back_to_back_non_const_mixed_types_origin.onnx
test_conv_follow_convtrans.onnx [XNNPACK] add more computation heavy ops (#13270) 2022-11-29 09:09:26 +08:00
test_conv_follow_convtrans_s8.onnx [XNNPACK] add more computation heavy ops (#13270) 2022-11-29 09:09:26 +08:00
test_kernel_info_get_const_input.onnx FasterTransformer model wrapper using custom op (#15013) 2023-03-20 09:05:30 -07:00
test_kernel_info_get_const_input.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
test_model_with_fullonnxdomain.onnx
test_resize.onnx [XNNPACK] add more computation heavy ops (#13270) 2022-11-29 09:09:26 +08:00
test_training_model.onnx
test_training_model_0.onnx
test_training_model_1.onnx
test_training_model_2.onnx
transpose_optimizer_cancel_squeeze_per_axis_dq.onnx [TransposeOptimizer] Support Unsqueeze/Transpose of input consumed by per-axis DQ (#21821) 2024-09-05 17:26:17 -07:00
transpose_optimizer_cancel_transpose_per_axis_dq.onnx [TransposeOptimizer] Support Unsqueeze/Transpose of input consumed by per-axis DQ (#21821) 2024-09-05 17:26:17 -07:00
transpose_optimizer_empty_dq_q_at_graph_output.onnx Remove empty (DQ -> Q -> graph output) sequence in TransposeOptimizer (#22172) 2024-09-24 21:02:17 -07:00
transpose_optimizer_in_place_transpose_unsqueeze_per_axis_dq.onnx [TransposeOptimizer] Support Unsqueeze/Transpose of input consumed by per-axis DQ (#21821) 2024-09-05 17:26:17 -07:00
transpose_optimizer_qdq_fixup_unsqueeze_per_axis_dq.onnx [TransposeOptimizer] Support Unsqueeze/Transpose of input consumed by per-axis DQ (#21821) 2024-09-05 17:26:17 -07:00
transpose_optimizer_shared_initializers.onnx Update transpose optimization to be more QDQ aware (#18444) 2023-11-23 08:27:47 +10:00
transpose_optimizer_shared_initializers.py Fix typos according to reviewdog report. (#21335) 2024-07-22 13:37:32 -07:00
transpose_optimizer_shared_initializers_broadcast.onnx Make transpose optimizer able to look past DQ node for const initializer (#17618) 2023-09-27 21:17:16 +10:00
transpose_optimizer_shared_initializers_broadcast2.onnx Update transpose optimization to be more QDQ aware (#18444) 2023-11-23 08:27:47 +10:00
tree_ensemble_as_tensor.onnx Implement TreeEnsemble for opset(ai.onnx.ml)==3 (#10821) 2022-03-30 12:53:12 +02:00
trt_plugin_custom_op_test.onnx Add TRT plugins support using custom ops (#13847) 2023-04-18 20:24:32 -07:00
trt_plugin_custom_op_test.py Add TRT plugins support using custom ops (#13847) 2023-04-18 20:24:32 -07:00
trt_reshape.onnx [TensorRT EP] Fix bug for shape tensor input (#18253) 2023-11-03 16:07:50 -07:00
trt_reshape_test.py [TensorRT EP] Fix bug for shape tensor input (#18253) 2023-11-03 16:07:50 -07:00
unused_initializer.onnx Don't remove an unused initializer if it is overridable. (#7649) 2021-05-12 07:03:54 +10:00
VariedInputCustomOp.onnx
zipmap_int64float.onnx
zipmap_stringfloat.onnx