Qonnx only c4ml (#22)

* Removed brevitas as main dependency.

* brevitas tests working by comparing qonnx/c4ml

* Removed qkeras and tensorflow stuff.

* Generate now takes only lbir.

added stub functional equivalnce op checker.

audio tests now use qonnx models, but are failing becouse of custom ops

* Made fft into an PyOp

disabled fft tests until qonnx is updated.

* Commented out op with onnxrt-extensions.

* Fixed linting issues.

* Updated gh workflows for newly added audio option at installation.

---------

Co-authored-by: jvreca <jure.vreca@ijs.si>
Co-authored-by: Jure Vreca (jure.vreca@ijs.si <jvreca@jastreb.ijs.si>

Author: jurevreca12

.github/workflows/publish-to-pypi.yml

@@ -29,7 +29,7 @@ jobs:
     - name: Install python dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install .[dev]
+        python -m pip install .[dev,audio]
 
     - name: Make protobuf
       run: make protobuf

.github/workflows/tests.yml

@@ -35,7 +35,7 @@ jobs:
     - name: Install python dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install .[dev]
+        python -m pip install .[dev,audio]
 
     - name: Setup JDK
       uses: actions/setup-java@v4
@@ -65,7 +65,7 @@ jobs:
       run: java -jar ./out/chisel4ml/assembly.dest/out.jar &> chisel4ml_sever.log &
 
     - name: Lint
-      run: flake8 -v --max-line-length=88 chisel4ml tests
+      run: tox -e lint
 
     - name: Run tests
       run: python -m pytest -x --use-verilator -n 4

chisel4ml/circuit.py

@@ -16,10 +16,10 @@
 import numpy as np
 
 import chisel4ml.lbir.services_pb2 as services
-from chisel4ml import transforms
 from chisel4ml.chisel4ml_server import Chisel4mlServer
 from chisel4ml.chisel4ml_server import connect_to_server
 from chisel4ml.lbir.qtensor_pb2 import QTensor
+from chisel4ml.transforms.numpy_transforms import numpy_to_qtensor
 from chisel4ml.transforms.qonnx_utils import qtensor_to_quantizer
 
 log = logging.getLogger(__name__)
@@ -54,9 +54,7 @@ def __init__(
 
     def __call__(self, np_arr, sim_timeout_sec=200):
         "Simulate the circuit, timeout in seconds."
-        qtensors = transforms.numpy_transforms.numpy_to_qtensor(
-            np_arr, self.input_quantizer, self.input_qtensor
-        )
+        qtensors = numpy_to_qtensor(np_arr, self.input_quantizer, self.input_qtensor)
         run_sim_params = services.RunSimulationParams(
             circuit_id=self.circuit_id, inputs=qtensors
         )

chisel4ml/generate.py

@@ -12,15 +12,12 @@
 import logging
 
 import numpy as np
-import tensorflow as tf
-import torch
 from ortools.sat.python import cp_model
-from qonnx.core.modelwrapper import ModelWrapper
 
 from chisel4ml import chisel4ml_server
-from chisel4ml import transform
 from chisel4ml.accelerator import ACCELERATORS
 from chisel4ml.circuit import Circuit
+import chisel4ml.lbir.lbir_pb2 as lbir
 from chisel4ml.lbir.services_pb2 import Accelerator
 from chisel4ml.lbir.services_pb2 import GenerateCircuitParams
 from chisel4ml.lbir.services_pb2 import GenerateCircuitReturn
@@ -80,16 +77,12 @@ def solution_to_accelerators(solution, lbir_layers):
     return new_accels
 
 
-def accelerators(model, ishape=None, num_layers=None, minimize="area", debug=False):
-    if isinstance(model, tf.keras.Model):
-        qonnx_model = transform.qkeras_to_qonnx(model)
-    elif isinstance(model, torch.nn.Module):
-        qonnx_model = transform.brevitas_to_qonnx(model, ishape)
-    elif isinstance(model, ModelWrapper):
-        qonnx_model = model
-    else:
-        raise TypeError(f"Model of type {type(model)} not supported.")
-    lbir_model = transform.qonnx_to_lbir(qonnx_model, debug=debug)
+def accelerators(lbir_model, num_layers=None, minimize="area"):
+    if not isinstance(lbir_model, lbir.Model):
+        raise TypeError(
+            f"Model of type {type(lbir_model)} not supported. "
+            "Please provide a LBIR model."
+        )
     if num_layers is not None:
         assert num_layers <= len(lbir_model.layers)
         for _ in range(len(lbir_model.layers) - num_layers):
@@ -132,7 +125,7 @@ def accelerators(model, ishape=None, num_layers=None, minimize="area", debug=Fal
     assert solution_status in (cp_model.FEASIBLE, cp_model.OPTIMAL)
     solution = solution_collector.solution_list[0]
     accels = solution_to_accelerators(solution, lbir_model.layers)
-    return accels, lbir_model
+    return accels
 
 
 def circuit(