This document is relevant for: Inf1, Inf2, Trn1, Trn1n

NeuronPerf Framework Notes#

PyTorch#

  • Requires: torch-neuron or torch-neuronx

    • Versions: 1.7.x, 1.8.x, 1.9.x, 1.10.x, 1.11.x, 1.12.x, 1.13.x

  • Input to compile: torch.nn.Module

  • Model inputs: Any.

TensorFlow 1.x#

  • Requires: tensorflow-neuron

    • Versions: All

  • Input to compile: Path to uncompiled model dir from saved_model.simple_save

  • Model inputs: Tensors must be provided as numpy.ndarray

Note

Although TensorFlow tensors must be ndarray, this doesn’t stop you from wrapping them inside of data structures that traverse process boundaries safely. For example, you can still pass an input dict like {'input_0': np.zeros((2, 1))}.

TensorFlow 2.x#

  • Requires: tensorflow-neuron or tensorflow-neuronx

    • Versions: All

  • Input to compile: tf.keras.Model

  • Model inputs: Tensors must be provided as numpy.ndarray

Note

Although TensorFlow tensors must be ndarray, this doesn’t stop you from wrapping them inside of data structures that traverse process boundaries safely. For example, you can still pass an input dict like {'input_0': np.zeros((2, 1))}.

Apache MXNet#

  • Requires: mxnet-neuron

    • Versions 1.5, 1.8

  • Input to compile: tuple(sym, args, aux)

  • Inputs: Tensors must be provided as mxnet.ndarray or numpy.ndarray

This document is relevant for: Inf1, Inf2, Trn1, Trn1n