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onnx-diagnostic 0.4.2 documentation
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onnx-diagnostic 0.4.2 documentation

Contents

  • API of onnx_diagnostic
    • onnx_diagnostic.export
      • onnx_diagnostic.export.dynamic_shapes
      • onnx_diagnostic.export.validate
    • onnx_diagnostic.helpers
      • onnx_diagnostic.helpers.args_helper
      • onnx_diagnostic.helpers.bench_run
      • onnx_diagnostic.helpers.cache_helper
      • onnx_diagnostic.helpers.config_helper
      • onnx_diagnostic.helpers.helper
      • onnx_diagnostic.helpers.memory_peak
      • onnx_diagnostic.helpers.onnx_helper
      • onnx_diagnostic.helpers.ort_session
      • onnx_diagnostic.helpers.rt_helper
      • onnx_diagnostic.helpers.torch_test_helper
    • onnx_diagnostic.reference
      • onnx_diagnostic.reference.ops
        • onnx_diagnostic.reference.ops.op_add_add_mul_mul
        • onnx_diagnostic.reference.ops.op_average_pool_grad
        • onnx_diagnostic.reference.ops.op_cast_like
        • onnx_diagnostic.reference.ops.op_complex
        • onnx_diagnostic.reference.ops.op_concat
        • onnx_diagnostic.reference.ops.op_constant_of_shape
        • onnx_diagnostic.reference.ops.op_fused_matmul
        • onnx_diagnostic.reference.ops.op_gather_grad
        • onnx_diagnostic.reference.ops.op_memcpy_host
        • onnx_diagnostic.reference.ops.op_mul_sigmoid
        • onnx_diagnostic.reference.ops.op_negxplus1
        • onnx_diagnostic.reference.ops.op_quick_gelu
        • onnx_diagnostic.reference.ops.op_replace_zero
        • onnx_diagnostic.reference.ops.op_rotary
        • onnx_diagnostic.reference.ops.op_qlinear_average_pool
        • onnx_diagnostic.reference.ops.op_qlinear_conv
        • onnx_diagnostic.reference.ops.op_scatter_elements
        • onnx_diagnostic.reference.ops.op_scatternd_of_shape
        • onnx_diagnostic.reference.ops.op_simplified_layer_normalization
        • onnx_diagnostic.reference.ops.op_skip_layer_normalization
        • onnx_diagnostic.reference.ops.op_slice
        • onnx_diagnostic.reference.ops.op_transpose_cast
        • onnx_diagnostic.reference.ops.op_tri_matrix
      • onnx_diagnostic.reference.evaluator
      • onnx_diagnostic.reference.quantized_tensor
      • onnx_diagnostic.reference.ort_evaluator
    • onnx_diagnostic.tasks
      • onnx_diagnostic.tasks.automatic_speech_recognition
      • onnx_diagnostic.tasks.fill_mask
      • onnx_diagnostic.tasks.feature_extraction
      • onnx_diagnostic.tasks.image_classification
      • onnx_diagnostic.export.image_text_to_text
      • onnx_diagnostic.tasks.mixture_of_expert
      • onnx_diagnostic.tasks.sentence_similarity
      • onnx_diagnostic.tasks.text_classification
      • onnx_diagnostic.tasks.text_generation
      • onnx_diagnostic.tasks.text2text_generation
      • onnx_diagnostic.tasks.zero_shot_image_classification
    • onnx_diagnostic.torch_export_patches
      • onnx_diagnostic.torch_export_patches.patches
        • onnx_diagnostic.torch_export_patches.patches.patch_torch
        • onnx_diagnostic.torch_export_patches.patches.patch_transformers
      • onnx_diagnostic.torch_export_patches.patch_inputs
    • onnx_diagnostic.torch_models
      • onnx_diagnostic.torch_models.hghub
        • onnx_diagnostic.torch_models.hghub.hub_api
        • onnx_diagnostic.torch_models.hghub.hub_data
        • onnx_diagnostic.torch_models.hghub.model_inputs
      • onnx_diagnostic.torch_models.llms
      • onnx_diagnostic.torch_models.test_helper
    • onnx_diagnostic.torch_onnx
      • onnx_diagnostic.torch_onnx.sbs
    • onnx_diagnostic.ext_test_case
  • Command Lines
    • -m onnx_diagnostic config … prints the config for a model id
    • -m onnx_diagnostic validate … validate a model id
  • Examples Gallery
    • Dynamic Shapes for *args, **kwargs
    • Export Tiny-LLM with patches
    • Export a model with a control flow (If)
    • Export with DynamicCache and dynamic shapes
    • Find and fix an export issue due to dynamic shapes
    • Find where a model is failing by running submodels
    • Intermediate results with (ONNX) ReferenceEvaluator
    • Intermediate results with onnxruntime
    • Steel method forward to guess the dynamic shapes (with Tiny-LLM)
    • Test the export on untrained models
    • Untrained microsoft/phi-2
    • Use DYNAMIC or AUTO when exporting if dynamic shapes has constraints
  • Common Export Issues
    • Cannot export torch.sym_max(x.shape[0], y.shape[0])
    • Do not use python int with dynamic shapes
    • Half certain nonzero

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Command Lines¶

python -m onnx_diagnostic
  • -m onnx_diagnostic config … prints the config for a model id
  • -m onnx_diagnostic validate … validate a model id
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-m onnx_diagnostic config … prints the config for a model id
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onnx_diagnostic.ext_test_case
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