GroqFlow™ Examples

This folder contains examples that demonstrate the use of groqit() arguments and GroqModel methods.

You can learn more about the concepts demonstrated in the examples by referencing the GroqFlow User Guide at docs/user_guide.md.

Table Of Contents

• Groq Tool Requirements
• Understanding Examples
• Running Examples
• Hello Worlds
• Hummingbird Examples
• Additional Pytorch Examples

Groq Tool Requirements

The Groq tools packages and the Quick Start Guide can be found at the Groq Customer Portal

• To build a groq_model the groq-devtools package should be installed.
• To run a GroqModel on hardware the groq-runtime package should be installed.
• Both Groq packages should be installed to enable both a build and to run on hardware from the same script.

Understanding Examples

Here are some properties shared by all of the examples:

• Each example will create a build directory in the GroqFlow build cache, which is located at ~/.cache/groqflow by default.
  • Note: Most builds will load from this cache after the first time you run them, as opposed to rebuilding, unless otherwise specified in the example (check out the rebuild argument and its examples to change this behavior).
  • Note: Most examples set torch.manual_seed(0) or tf.random.set_seed(0), unless otherwise specified in the example, which prevents the randomly generated weights in the example from changing between runs.
• The build directory will be named after the example unless the example specifies a name change with the build_name argument (see the build_name.py example).
• The model being built in each example is a small one- or two-layer fully-connected graph.

Running Examples

To run any of the examples, open a terminal and type the following command:

python /path/to/example/example_name.py

Hello Worlds

Example Name	Demonstrates
pytorch/hello_world.py	building and running a model defined in PyTorch
keras/hello_world.py	building and running a model defined in Keras
onnx/hello_world.py	building and running a model defined as an ONNX file

Hummingbird Examples

Example Name	Demonstrates
hummingbird/randomforest.py	building and running a Hummingbird RandomForestClassifier against random data
hummingbird/xgbclassifier.py	building and running a Hummingbird XGBClassifier against random data

Additional PyTorch Examples

Example Name	Demonstrates
pytorch/assembler_flags.py	the assembler_flags argument to groqit()
pytorch/benchmark.py	the benchmark() method of GroqModel
pytorch/benchmark_abunch.py	the benchmark_abunch() method of GroqModel
pytorch/build_name.py	the build_name argument to groqit()
pytorch/cache_dir.py	the cache_dir argument to groqit()
pytorch/compiler_flags.py	the compiler_flags argument to groqit()
pytorch/estimate_performance.py	the performance estimation feature of GroqFlow
pytorch/groqview.py	how to create and open a GroqView visualization using GroqFlow
pytorch/no_monitor.py	the monitor argument to groqit()
pytorch/num_chips.py	the num_chips argument to groqit()
pytorch/rebuild_always.py	groqit()'s caching behavior when the rebuild argument is set to "always"
pytorch/rebuild_never.py	groqit()'s caching behavior when the rebuild argument is set to "never"
pytorch/run_abunch.py	running multiple inputs at a time with the run_abunch() method
pytorch/sequence.py	the sequence argument for changing the default GroqFlow steps for porting your model