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recipe(multilingual-e5-small): add CPU fp32/fp16 feature-extraction and sentence-similarity recipes #1182
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Qiong Wu (qiowu) (DingmaomaoBJTU)
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recipe(multilingual-e5-small): add CPU fp32/fp16 feature-extraction and sentence-similarity recipes #1182
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91 changes: 91 additions & 0 deletions
91
examples/recipes/intfloat_multilingual-e5-small/cpu/cpu/feature-extraction_fp16_config.json
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,91 @@ | ||
| { | ||
| "export": { | ||
| "opset_version": 17, | ||
| "batch_size": 1, | ||
| "export_params": true, | ||
| "do_constant_folding": true, | ||
| "verbose": false, | ||
| "dynamo": false, | ||
| "enable_hierarchy_tags": true, | ||
| "clean_onnx": false, | ||
| "hierarchy_tag_format": "full", | ||
| "input_tensors": [ | ||
| { | ||
| "name": "input_ids", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 250037 | ||
| ] | ||
| }, | ||
| { | ||
| "name": "attention_mask", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 2 | ||
| ] | ||
| }, | ||
| { | ||
| "name": "token_type_ids", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 2 | ||
| ] | ||
| } | ||
| ], | ||
| "output_tensors": [ | ||
| { | ||
| "name": "last_hidden_state" | ||
| } | ||
| ], | ||
| "compatibility": { | ||
| "transformers_attention": "eager" | ||
| } | ||
| }, | ||
| "optim": { | ||
| "clamp_constant_values": true | ||
| }, | ||
| "quant": { | ||
| "mode": "fp16", | ||
| "samples": 10, | ||
| "calibration_method": "minmax", | ||
| "weight_type": "uint8", | ||
| "activation_type": "uint8", | ||
| "per_channel": false, | ||
| "symmetric": false, | ||
| "weight_symmetric": null, | ||
| "activation_symmetric": null, | ||
| "save_calibration": false, | ||
| "distribution": "uniform", | ||
| "seed": null, | ||
| "calibration_load_path": null, | ||
| "calibration_save_path": null, | ||
| "op_types_to_quantize": null, | ||
| "nodes_to_exclude": null, | ||
| "task": "feature-extraction", | ||
| "model_id": "intfloat/multilingual-e5-small", | ||
| "model_type": "bert", | ||
| "fp16_keep_io_types": true, | ||
| "fp16_op_block_list": null | ||
| }, | ||
| "compile": null, | ||
| "loader": { | ||
| "task": "feature-extraction", | ||
| "model_class": "AutoModel", | ||
| "model_type": "bert" | ||
| } | ||
| } |
69 changes: 69 additions & 0 deletions
69
examples/recipes/intfloat_multilingual-e5-small/cpu/cpu/feature-extraction_fp32_config.json
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,69 @@ | ||
| { | ||
| "export": { | ||
| "opset_version": 17, | ||
| "batch_size": 1, | ||
| "export_params": true, | ||
| "do_constant_folding": true, | ||
| "verbose": false, | ||
| "dynamo": false, | ||
| "enable_hierarchy_tags": true, | ||
| "clean_onnx": false, | ||
| "hierarchy_tag_format": "full", | ||
| "input_tensors": [ | ||
| { | ||
| "name": "input_ids", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 250037 | ||
| ] | ||
| }, | ||
| { | ||
| "name": "attention_mask", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 2 | ||
| ] | ||
| }, | ||
| { | ||
| "name": "token_type_ids", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 2 | ||
| ] | ||
| } | ||
| ], | ||
| "output_tensors": [ | ||
| { | ||
| "name": "last_hidden_state" | ||
| } | ||
| ], | ||
| "compatibility": { | ||
| "transformers_attention": "eager" | ||
| } | ||
| }, | ||
| "optim": { | ||
| "clamp_constant_values": true | ||
| }, | ||
| "quant": null, | ||
| "compile": null, | ||
| "loader": { | ||
| "task": "feature-extraction", | ||
| "model_class": "AutoModel", | ||
| "model_type": "bert" | ||
| } | ||
| } |
91 changes: 91 additions & 0 deletions
91
examples/recipes/intfloat_multilingual-e5-small/cpu/cpu/sentence-similarity_fp16_config.json
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,91 @@ | ||
| { | ||
| "export": { | ||
| "opset_version": 17, | ||
| "batch_size": 1, | ||
| "export_params": true, | ||
| "do_constant_folding": true, | ||
| "verbose": false, | ||
| "dynamo": false, | ||
| "enable_hierarchy_tags": true, | ||
| "clean_onnx": false, | ||
| "hierarchy_tag_format": "full", | ||
| "input_tensors": [ | ||
| { | ||
| "name": "input_ids", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 250037 | ||
| ] | ||
| }, | ||
| { | ||
| "name": "attention_mask", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 2 | ||
| ] | ||
| }, | ||
| { | ||
| "name": "token_type_ids", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 2 | ||
| ] | ||
| } | ||
| ], | ||
| "output_tensors": [ | ||
| { | ||
| "name": "last_hidden_state" | ||
| } | ||
| ], | ||
| "compatibility": { | ||
| "transformers_attention": "eager" | ||
| } | ||
| }, | ||
| "optim": { | ||
| "clamp_constant_values": true | ||
| }, | ||
| "quant": { | ||
| "mode": "fp16", | ||
| "samples": 10, | ||
| "calibration_method": "minmax", | ||
| "weight_type": "uint8", | ||
| "activation_type": "uint8", | ||
| "per_channel": false, | ||
| "symmetric": false, | ||
| "weight_symmetric": null, | ||
| "activation_symmetric": null, | ||
| "save_calibration": false, | ||
| "distribution": "uniform", | ||
| "seed": null, | ||
| "calibration_load_path": null, | ||
| "calibration_save_path": null, | ||
| "op_types_to_quantize": null, | ||
| "nodes_to_exclude": null, | ||
| "task": "sentence-similarity", | ||
| "model_id": "intfloat/multilingual-e5-small", | ||
| "model_type": "bert", | ||
| "fp16_keep_io_types": true, | ||
| "fp16_op_block_list": null | ||
| }, | ||
| "compile": null, | ||
| "loader": { | ||
| "task": "sentence-similarity", | ||
| "model_class": "AutoModel", | ||
| "model_type": "bert" | ||
| } | ||
| } |
69 changes: 69 additions & 0 deletions
69
examples/recipes/intfloat_multilingual-e5-small/cpu/cpu/sentence-similarity_fp32_config.json
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,69 @@ | ||
| { | ||
| "export": { | ||
| "opset_version": 17, | ||
| "batch_size": 1, | ||
| "export_params": true, | ||
| "do_constant_folding": true, | ||
| "verbose": false, | ||
| "dynamo": false, | ||
| "enable_hierarchy_tags": true, | ||
| "clean_onnx": false, | ||
| "hierarchy_tag_format": "full", | ||
| "input_tensors": [ | ||
| { | ||
| "name": "input_ids", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 250037 | ||
| ] | ||
| }, | ||
| { | ||
| "name": "attention_mask", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 2 | ||
| ] | ||
| }, | ||
| { | ||
| "name": "token_type_ids", | ||
| "dtype": "int32", | ||
| "shape": [ | ||
| 1, | ||
| 512 | ||
| ], | ||
| "value_range": [ | ||
| 0, | ||
| 2 | ||
| ] | ||
| } | ||
| ], | ||
| "output_tensors": [ | ||
| { | ||
| "name": "last_hidden_state" | ||
| } | ||
| ], | ||
| "compatibility": { | ||
| "transformers_attention": "eager" | ||
| } | ||
| }, | ||
| "optim": { | ||
| "clamp_constant_values": true | ||
| }, | ||
| "quant": null, | ||
| "compile": null, | ||
| "loader": { | ||
| "task": "sentence-similarity", | ||
| "model_class": "AutoModel", | ||
| "model_type": "bert" | ||
| } | ||
| } |
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Learn more about bidirectional Unicode characters
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This wrapper cannot infer from tensor shape or ONNX metadata that the request contains only one segment. If a caller passes tokenized paired BERT input without
token_type_ids, segment-B positions require1, but this path silently supplies all zeros and returns incorrect embeddings instead of preserving the missing-input error. Could zero synthesis be gated by explicit preprocessing metadata that establishes a single-text request (or a declarative safe-default policy), rather than applied universally whenever the tensor is omitted?