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CHANGELOG.md

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master

  • Added tensor shape tracking to support dynamic shapes for flatten, squeeze, unsqueeze, view, reshape, interpolate, and getitem methods
  • Added EasyOCR example
  • Added the DatasetRecorder context manager, allowing to easily capture of module inputs in large pipeline for calibration and shape inference
  • Added support for legacy max_batch_size using optimization profiles
  • Added support for nested tuple, dict and list module inputs and outputs via. the Flattener class
  • Added ability to accept dataset as inputs argument, and infer optimization profiles from the data
  • Added Dataset, TensorBatchDataset, ListDataset, and FolderDatset classes
  • Added support for dynamic shapes
    • Known limitation: Currently some converters (ie: View) may have unexpected behavior if their arguments are defined with dynamic Tensor shapes.

0.4.0 - 07/22/2022

  • Added converter for torch.nn.functional.group_norm using native TensorRT layers
  • Added converter for torch.nn.ReflectionPad2d using plugin layer
  • Added torch2trt_plugins library
  • Added support for Deep Learning Accelerator (DLA)
  • Added support for explicit batch
  • Added support for TensorRT 8

0.3.0 - 07/15/2021

  • Added converter for torch.nn.functional.adaptive_avg_pool3d
  • Added converter for torch.nn.functional.adaptive_max_pool3d
  • Added converter for torch.maxpool3d and torch.nn.functional.max_pool3d
  • Added Quantization Aware Training (QAT) workflow to contrib
  • Added converter for torch.roll
  • Added converter for torch.nn.functional.layer_norm
  • Added converter for torch.nn.functional.gelu
  • Added converter for torch.nn.functional.linear
  • Added converter for torch.nn.functional.silu

0.2.0 - 03/02/2021

  • Added converter for torch.Tensor.flatten
  • Added converter for torch.nn.functional.conv2d and torch.nn.functional.conv3d
  • Added converter for torch.Tensor.expand
  • Added support for custom converters for methods defined outside of torch module
  • Added names for TensorRT layers
  • Added GroupNorm plugin which internally uses PyTorch aten::group_norm
  • Replaced Tensor.ndim references with len(tensor.shape) to support older pytorch versions
  • Added reduced precision documentation page
  • Added converters for floordiv, mod, ne, and torch.tensor operations
  • Extended relu converter to support Tensor.relu operation
  • Extended sigmoid converter to support Tensor.sigmoid operation